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Continuous Glucose Monitoring vs Fingerstick Monitoring for Hemoglobin A1c Control in Veterans
In the United States, 1 in 4 veterans lives with type 2 diabetes mellitus (T2DM), double the rate of the general population.1 Medications are important for the treatment of T2DM and preventing complications that may develop if not properly managed. Common classes of medications for diabetes include biguanides, sodiumglucose cotransporter-2 (SGLT-2) inhibitors, glucagon-like peptide-1 (GLP-1) receptor agonists, dipeptidyl peptidase-4 inhibitors, thiazolidinediones, sulfonylureas, and insulin. The selection of treatment depends on patient-specific factors including hemoglobin A1c (HbA1c) goal, potential effects on weight, risk of hypoglycemia, and comorbidities such as atherosclerotic cardiovascular disease, heart failure, or chronic kidney disease.2
HbA1c level reflects the mean blood glucose over the previous 3 months and serves as an indication of diabetes control. In patients with diabetes, it is recommended that HbA1c is checked ≥ 2 times annually for those meeting treatment goals, or more often if the patient needs to adjust medications to reach their HbA1c goal. The goal HbA1c level for most adults with diabetes is < 7%.3 This target can be adjusted based on age, comorbidities, or other patient factors. It is generally recommended that frequent glucose monitoring is not needed for patients with T2DM who are only taking oral agents and/or noninsulin injectables. However, for those on insulin regimens, it is advised to monitor glucose closely, with even more frequent testing for those with an intensive insulin regimen.3
Most patients with diabetes use fingerstick testing to self-monitor their blood glucose. However, continuous glucose monitors (CGMs) are becoming widely available and offer a solution to those who do not have the ability to check their glucose multiple times a day and throughout the night. The American Diabetes Association recommends that the frequency and timing of blood glucose monitoring, or the consideration of CGM use, should be based on the specific needs and goals of each patient.3 Guidelines also encourage those on intensive insulin regimens to check glucose levels when fasting, before and after meals, prior to exercise, and when hypoglycemia or hyperglycemia is suspected. Frequent testing can become a burden for patients, whereas once a CGM sensor is placed, it can be worn for 10 to 14 days. CGMs are also capable of transmitting glucose readings every 1 to 15 minutes to a receiver or mobile phone, allowing for further adaptability to a patient’s lifestyle.3
CGMs work by measuring the interstitial glucose with a small filament sensor and have demonstrated accuracy when compared to blood glucose readings. The ability of a CGM to accurately reflect HbA1c levels is a potential benefit, reducing the need for frequent testing to determine whether patients have achieved glycemic control.4 Another benefit of a CGM is the ease of sharing data; patient accounts can be linked with a health care site, allowing clinicians to access glucose data even if the patient is not able to be seen in clinic. This allows health care practitioners (HCPs) to more efficiently tailor medications and optimize regimens based on patient-specific data that was not available by fingerstick testing alone.
Vigersky and colleagues provided one of the few studies on the long-term effects of CGM in patients managing T2DM through diet and exercise alone, oral medications, or basal insulin and found significant improvement in HbA1c after only 3 months of CGM use.5
An important aspect of CGM use is the ability to alert the patient to low blood glucose readings, which can be dangerous for those unaware of hypoglycemia. Many studies have investigated the association between CGM use and acute metabolic events, demonstrating the potential for CGMs to prevent these emergencies. Karter and colleagues found a reduction in emergency department visits and hospitalizations for hypoglycemia associated with the use of CGMs in patients with type 1 DM (T1DM) and T2DM.6
There have been few studies on the use of CGM in veterans. Langford and colleagues found a reduction of HbA1c among veterans with T2DM using CGMs. However, > 50% of the patients in the study were not receiving insulin therapy, which currently is a US Department of Veterans Affairs (VA) CGM criteria for use.7 While current studies provide evidence that supports improvement in HbA1c levels with the use of CGMs, data are lacking for veterans with T2DM taking insulin. There is also minimal research that indicates which patients should be offered a CGM. The objective of this study was to evaluate glycemic control in veterans with T2DM on insulin using a CGM who were previously monitoring blood glucose with fingerstick testing. Secondary endpoints were explored to identify subgroups that may benefit from a CGM and other potential advantages of CGMs.
Methods
This was a retrospective study of veterans who transitioned from fingerstick testing to CGM for glucose monitoring. Each veteran served as their own control to limit confounding variables when comparing HbA1c levels. Veterans with an active or suspended CGM order were identified by reviewing outpatient prescription data. All data collection and analysis were done within the Veterans Affairs Sioux Falls Health Care System.
The primary objective of this study was to assess glycemic control from the use of a CGM by evaluating the change in HbA1c after transitioning to a CGM compared to the change in HbA1c with standard fingerstick monitoring. Three HbA1c values were collected for each veteran: before starting CGM, at initiation, and following CGM initiation (Figure 1). CGM start date was the date the CGM prescription order was placed. The pre-CGM HbA1c level was ≥ 1 year prior to the CGM start date or the HbA1c closest to 1 year. The start CGM HbA1c level was within 3 months before or 1 month after the CGM start date. The post-CGM HbA1c level was the most recent time of data collection and at least 6 months after CGM initiation. The change in HbA1c from fingerstick glucose monitoring was the difference between the pre-CGM and start CGM values. The change in HbA1c from use of a CGM was the difference between start CGM and post-CGM values, which were compared to determine HbA1c reduction from CGM use.

This study also explored secondary outcomes including changes in HbA1c by prescriber type, differences in HbA1c reduction based on age, and changes in diabetes medications, including total daily insulin doses. For secondary outcomes, diabetes medication information and the total daily dose of insulin were gathered at the start of CGM use and at the time of data collection. The most recent CGM order prescribed was also collected.
Veterans were included if they were aged ≥ 18 years, had an active order for a CGM, T2DM diagnosis, an insulin prescription, and previously used test strips for glucose monitoring. Patients with T1DM, those who accessed CGMs or care in the community, and patients without HbA1c values pre-CGM, were excluded.
Statistical Analysis
The primary endpoint of change in HbA1c level before and after CGM use was compared using a paired t test. A 0.5% change in HbA1c was considered clinically significant, as suggested in other studies.8,9P < .05 was considered statistically significant. Analysis for continuous baseline characteristics, including age and total daily insulin, were reported as mean values. Nominal characteristics including sex, race, diabetes medications, and prescriber type are reported as percentages.
Results
A total of 402 veterans were identified with an active CGM at the time of initial data collection in January 2024 and 175 met inclusion criteria. Sixty patients were excluded due to diabetes managed through a community HCP, 38 had T1DM, and 129 lacked HbA1c within all specified time periods. The 175 veterans were randomized, and 150 were selected to perform a chart review for data collection. The mean age was 70 years, most were male and identified as White (Table 1). The majority of patients were managed by endocrinology (53.3%), followed by primary care (24.0%), and pharmacy (22.7%) (Table 2). The mean baseline HbA1c was 8.6%.


The difference in HbA1c before and after use of CGM was -0.97% (P = .0001). Prior to use of a CGM the change in HbA1c was minimal, with an increase of 0.003% with the use of selfmonitoring glucose. After use of a CGM, HbA1c decreased by 0.971%. This reduction in HbA1c would also be considered clinically significant as the change was > 0.5%. The mean pre-, at start, and post-CGM HbA1c levels were 8.6%, 8.6%, and 7.6%, respectively (Figure 2). Pharmacy prescribers had a 0.7% reduction in HbA1c post-CGM, the least of all prescribers. While most age groups saw a reduction in HbA1c, those aged ≥ 80 years had an increase of 0.18% (Table 3). There was an overall mean reduction in insulin of 22 units, which was similar between all prescribers.


Discussion
The primary endpoint of difference in change of HbA1c before and after CGM use was found to be statistically and clinically significant, with a nearly 1% reduction in HbA1c, which was similar to the reduction found by Vigersky and colleagues. 5 Across all prescribers, post-CGM HbA1c levels were similar; however, patients with CGM prescribed by pharmacists had the smallest change in HbA1c. VA pharmacists primarily assess veterans taking insulin who have HbA1c levels that are below the goal with the aim of decreasing insulin to reduce the risk of hypoglycemia, which could result in increased HbA1c levels. This may also explain the observed increase in post-CGM HbA1c levels in patients aged ≥ 80 years. Patients under the care of pharmacists also had baseline mean HbA1c levels that were lower than primary care and endocrinology prescribers and were closer to their HbA1c goal at baseline, which likely was reflected in the smaller reduction in post-CGM HbA1c level.
While there was a decrease in HbA1c levels with CGM use, there were also changes to medications during this timeframe that also may have impacted HbA1c levels. The most common diabetes medications started during CGM use were GLP-1 agonists and SGLT2-inhibitors. Additionally, there was a reduction in the total daily dose of insulin in the study population. These results demonstrate the potential benefits of CGMs for prescribers who take advantage of the CGM glucose data available to assist with medication adjustments. Another consideration for differences in changes of HbA1c among prescriber types is the opportunity for more frequent follow- up visits with pharmacy or endocrinology compared with primary care. If veterans are followed more closely, it may be associated with improved HbA1c control. Further research investigating changes in HbA1c levels based on followup frequency may be useful.
Strengths and Limitations
The crossover design was a strength of this study. This design reduced confounding variables by having veterans serve as their own controls. In addition, the collection of multiple secondary outcomes adds to the knowledge base for future studies. This study focused on a unique population of veterans with T2DM who were taking insulin, an area that previously had very little data available to determine the benefits of CGM use.
Although the use of a CGM showed statistical significance in lowering HbA1c, many veterans were started on new diabetes medication during the period of CGM use, which also likely contributed to the reduction in HbA1c and may have confounded the results. The study was limited by its small population size due to time constraints of chart reviews and the limited generalizability of results outside of the VA system. The majority of patients were from a single site, male and identified as White, which may not be reflective of other VA and community health care systems. It was also noted that the time from the initiation of CGM use to the most recent HbA1c level varied from 6 months to several years. Additionally, veterans managed by community-based HCPs with complex diabetes cases were excluded.
Conclusions
This study demonstrated a clinically and statistically significant reduction in HbA1c with the use of a CGM compared to fingerstick monitoring in veterans with T2DM who were being treated with insulin. The change in post-CGM HbA1c levels across prescribers was similar. In the subgroup analysis of change in HbA1c among age groups, there was a lower HbA1c reduction in individuals aged ≥ 80 years. The results from this study support the idea that CGM use may be beneficial for patients who require a reduction in HbA1c by allowing more precise adjustments to medications and optimization of therapy, as well as the potential to reduce insulin requirements, which is especially valuable in the older adult veteran population.
- US Department of Veterans Affairs. VA supports veterans who have type 2 diabetes. VA News. Accessed September 30, 2024. https://news.va.gov/107579/va-supports-veterans-who-have-type-2-diabetes/
- ElSayed NA, Aleppo G, Aroda VR, et al. 9. Pharmacologic approaches to glycemic treatment: standards of care in diabetes-2023. Diabetes Care. 2023;46(Suppl 1):S140- S157. doi:10.2337/dc23-S009
- ElSayed NA, Aleppo G, Aroda VR, et al. 6. Glycemic targets: standards of care in diabetes-2023. Diabetes Care. 2023;46(Suppl 1):S97-S110. doi:10.2337/dc23-S006
- Miller E, Gavin JR, Kruger DF, Brunton SA. Continuous glucose monitoring: optimizing diabetes care: executive summary. Clin Diabetes. 2022;40(4):394-398. doi:10.2337/cd22-0043
- Vigersky RA, Fonda SJ, Chellappa M, Walker MS, Ehrhardt NM. Short- and long-term effects of real-time continuous glucose monitoring in patients with type 2 diabetes. Diabetes Care. 2012;35(1):32-38. doi:10.2337/dc11-1438
- Karter AJ, Parker MM, Moffet HH, Gilliam LK, Dlott R. Association of real-time continuous glucose monitoring with glycemic control and acute metabolic events among patients with insulin-treated diabetes. JAMA. 2021;325(22):2273-2284. doi:10.1001/JAMA.2021.6530
- Langford SN, Lane M, Karounos D. Continuous blood glucose monitoring outcomes in veterans with type 2 diabetes. Fed Pract. 2021;38(Suppl 4):S14-S17. doi:10.12788/fp.0189
- Radin MS. Pitfalls in hemoglobin A1c measurement: when results may be misleading. J Gen Intern Med. 2014;29(2):388-394. doi:10.1007/s11606-013-2595-x.
- Little RR, Rohlfing CL, Sacks DB; National Glycohemoglobin Standardization Program (NGSP) steering committee. Status of hemoglobin A1c measurement and goals for improvement: from chaos to order for improving diabetes care. Clin Chem. 2011;57(2):205-214. doi:10.1373/clinchem.2010.148841
In the United States, 1 in 4 veterans lives with type 2 diabetes mellitus (T2DM), double the rate of the general population.1 Medications are important for the treatment of T2DM and preventing complications that may develop if not properly managed. Common classes of medications for diabetes include biguanides, sodiumglucose cotransporter-2 (SGLT-2) inhibitors, glucagon-like peptide-1 (GLP-1) receptor agonists, dipeptidyl peptidase-4 inhibitors, thiazolidinediones, sulfonylureas, and insulin. The selection of treatment depends on patient-specific factors including hemoglobin A1c (HbA1c) goal, potential effects on weight, risk of hypoglycemia, and comorbidities such as atherosclerotic cardiovascular disease, heart failure, or chronic kidney disease.2
HbA1c level reflects the mean blood glucose over the previous 3 months and serves as an indication of diabetes control. In patients with diabetes, it is recommended that HbA1c is checked ≥ 2 times annually for those meeting treatment goals, or more often if the patient needs to adjust medications to reach their HbA1c goal. The goal HbA1c level for most adults with diabetes is < 7%.3 This target can be adjusted based on age, comorbidities, or other patient factors. It is generally recommended that frequent glucose monitoring is not needed for patients with T2DM who are only taking oral agents and/or noninsulin injectables. However, for those on insulin regimens, it is advised to monitor glucose closely, with even more frequent testing for those with an intensive insulin regimen.3
Most patients with diabetes use fingerstick testing to self-monitor their blood glucose. However, continuous glucose monitors (CGMs) are becoming widely available and offer a solution to those who do not have the ability to check their glucose multiple times a day and throughout the night. The American Diabetes Association recommends that the frequency and timing of blood glucose monitoring, or the consideration of CGM use, should be based on the specific needs and goals of each patient.3 Guidelines also encourage those on intensive insulin regimens to check glucose levels when fasting, before and after meals, prior to exercise, and when hypoglycemia or hyperglycemia is suspected. Frequent testing can become a burden for patients, whereas once a CGM sensor is placed, it can be worn for 10 to 14 days. CGMs are also capable of transmitting glucose readings every 1 to 15 minutes to a receiver or mobile phone, allowing for further adaptability to a patient’s lifestyle.3
CGMs work by measuring the interstitial glucose with a small filament sensor and have demonstrated accuracy when compared to blood glucose readings. The ability of a CGM to accurately reflect HbA1c levels is a potential benefit, reducing the need for frequent testing to determine whether patients have achieved glycemic control.4 Another benefit of a CGM is the ease of sharing data; patient accounts can be linked with a health care site, allowing clinicians to access glucose data even if the patient is not able to be seen in clinic. This allows health care practitioners (HCPs) to more efficiently tailor medications and optimize regimens based on patient-specific data that was not available by fingerstick testing alone.
Vigersky and colleagues provided one of the few studies on the long-term effects of CGM in patients managing T2DM through diet and exercise alone, oral medications, or basal insulin and found significant improvement in HbA1c after only 3 months of CGM use.5
An important aspect of CGM use is the ability to alert the patient to low blood glucose readings, which can be dangerous for those unaware of hypoglycemia. Many studies have investigated the association between CGM use and acute metabolic events, demonstrating the potential for CGMs to prevent these emergencies. Karter and colleagues found a reduction in emergency department visits and hospitalizations for hypoglycemia associated with the use of CGMs in patients with type 1 DM (T1DM) and T2DM.6
There have been few studies on the use of CGM in veterans. Langford and colleagues found a reduction of HbA1c among veterans with T2DM using CGMs. However, > 50% of the patients in the study were not receiving insulin therapy, which currently is a US Department of Veterans Affairs (VA) CGM criteria for use.7 While current studies provide evidence that supports improvement in HbA1c levels with the use of CGMs, data are lacking for veterans with T2DM taking insulin. There is also minimal research that indicates which patients should be offered a CGM. The objective of this study was to evaluate glycemic control in veterans with T2DM on insulin using a CGM who were previously monitoring blood glucose with fingerstick testing. Secondary endpoints were explored to identify subgroups that may benefit from a CGM and other potential advantages of CGMs.
Methods
This was a retrospective study of veterans who transitioned from fingerstick testing to CGM for glucose monitoring. Each veteran served as their own control to limit confounding variables when comparing HbA1c levels. Veterans with an active or suspended CGM order were identified by reviewing outpatient prescription data. All data collection and analysis were done within the Veterans Affairs Sioux Falls Health Care System.
The primary objective of this study was to assess glycemic control from the use of a CGM by evaluating the change in HbA1c after transitioning to a CGM compared to the change in HbA1c with standard fingerstick monitoring. Three HbA1c values were collected for each veteran: before starting CGM, at initiation, and following CGM initiation (Figure 1). CGM start date was the date the CGM prescription order was placed. The pre-CGM HbA1c level was ≥ 1 year prior to the CGM start date or the HbA1c closest to 1 year. The start CGM HbA1c level was within 3 months before or 1 month after the CGM start date. The post-CGM HbA1c level was the most recent time of data collection and at least 6 months after CGM initiation. The change in HbA1c from fingerstick glucose monitoring was the difference between the pre-CGM and start CGM values. The change in HbA1c from use of a CGM was the difference between start CGM and post-CGM values, which were compared to determine HbA1c reduction from CGM use.

This study also explored secondary outcomes including changes in HbA1c by prescriber type, differences in HbA1c reduction based on age, and changes in diabetes medications, including total daily insulin doses. For secondary outcomes, diabetes medication information and the total daily dose of insulin were gathered at the start of CGM use and at the time of data collection. The most recent CGM order prescribed was also collected.
Veterans were included if they were aged ≥ 18 years, had an active order for a CGM, T2DM diagnosis, an insulin prescription, and previously used test strips for glucose monitoring. Patients with T1DM, those who accessed CGMs or care in the community, and patients without HbA1c values pre-CGM, were excluded.
Statistical Analysis
The primary endpoint of change in HbA1c level before and after CGM use was compared using a paired t test. A 0.5% change in HbA1c was considered clinically significant, as suggested in other studies.8,9P < .05 was considered statistically significant. Analysis for continuous baseline characteristics, including age and total daily insulin, were reported as mean values. Nominal characteristics including sex, race, diabetes medications, and prescriber type are reported as percentages.
Results
A total of 402 veterans were identified with an active CGM at the time of initial data collection in January 2024 and 175 met inclusion criteria. Sixty patients were excluded due to diabetes managed through a community HCP, 38 had T1DM, and 129 lacked HbA1c within all specified time periods. The 175 veterans were randomized, and 150 were selected to perform a chart review for data collection. The mean age was 70 years, most were male and identified as White (Table 1). The majority of patients were managed by endocrinology (53.3%), followed by primary care (24.0%), and pharmacy (22.7%) (Table 2). The mean baseline HbA1c was 8.6%.


The difference in HbA1c before and after use of CGM was -0.97% (P = .0001). Prior to use of a CGM the change in HbA1c was minimal, with an increase of 0.003% with the use of selfmonitoring glucose. After use of a CGM, HbA1c decreased by 0.971%. This reduction in HbA1c would also be considered clinically significant as the change was > 0.5%. The mean pre-, at start, and post-CGM HbA1c levels were 8.6%, 8.6%, and 7.6%, respectively (Figure 2). Pharmacy prescribers had a 0.7% reduction in HbA1c post-CGM, the least of all prescribers. While most age groups saw a reduction in HbA1c, those aged ≥ 80 years had an increase of 0.18% (Table 3). There was an overall mean reduction in insulin of 22 units, which was similar between all prescribers.


Discussion
The primary endpoint of difference in change of HbA1c before and after CGM use was found to be statistically and clinically significant, with a nearly 1% reduction in HbA1c, which was similar to the reduction found by Vigersky and colleagues. 5 Across all prescribers, post-CGM HbA1c levels were similar; however, patients with CGM prescribed by pharmacists had the smallest change in HbA1c. VA pharmacists primarily assess veterans taking insulin who have HbA1c levels that are below the goal with the aim of decreasing insulin to reduce the risk of hypoglycemia, which could result in increased HbA1c levels. This may also explain the observed increase in post-CGM HbA1c levels in patients aged ≥ 80 years. Patients under the care of pharmacists also had baseline mean HbA1c levels that were lower than primary care and endocrinology prescribers and were closer to their HbA1c goal at baseline, which likely was reflected in the smaller reduction in post-CGM HbA1c level.
While there was a decrease in HbA1c levels with CGM use, there were also changes to medications during this timeframe that also may have impacted HbA1c levels. The most common diabetes medications started during CGM use were GLP-1 agonists and SGLT2-inhibitors. Additionally, there was a reduction in the total daily dose of insulin in the study population. These results demonstrate the potential benefits of CGMs for prescribers who take advantage of the CGM glucose data available to assist with medication adjustments. Another consideration for differences in changes of HbA1c among prescriber types is the opportunity for more frequent follow- up visits with pharmacy or endocrinology compared with primary care. If veterans are followed more closely, it may be associated with improved HbA1c control. Further research investigating changes in HbA1c levels based on followup frequency may be useful.
Strengths and Limitations
The crossover design was a strength of this study. This design reduced confounding variables by having veterans serve as their own controls. In addition, the collection of multiple secondary outcomes adds to the knowledge base for future studies. This study focused on a unique population of veterans with T2DM who were taking insulin, an area that previously had very little data available to determine the benefits of CGM use.
Although the use of a CGM showed statistical significance in lowering HbA1c, many veterans were started on new diabetes medication during the period of CGM use, which also likely contributed to the reduction in HbA1c and may have confounded the results. The study was limited by its small population size due to time constraints of chart reviews and the limited generalizability of results outside of the VA system. The majority of patients were from a single site, male and identified as White, which may not be reflective of other VA and community health care systems. It was also noted that the time from the initiation of CGM use to the most recent HbA1c level varied from 6 months to several years. Additionally, veterans managed by community-based HCPs with complex diabetes cases were excluded.
Conclusions
This study demonstrated a clinically and statistically significant reduction in HbA1c with the use of a CGM compared to fingerstick monitoring in veterans with T2DM who were being treated with insulin. The change in post-CGM HbA1c levels across prescribers was similar. In the subgroup analysis of change in HbA1c among age groups, there was a lower HbA1c reduction in individuals aged ≥ 80 years. The results from this study support the idea that CGM use may be beneficial for patients who require a reduction in HbA1c by allowing more precise adjustments to medications and optimization of therapy, as well as the potential to reduce insulin requirements, which is especially valuable in the older adult veteran population.
In the United States, 1 in 4 veterans lives with type 2 diabetes mellitus (T2DM), double the rate of the general population.1 Medications are important for the treatment of T2DM and preventing complications that may develop if not properly managed. Common classes of medications for diabetes include biguanides, sodiumglucose cotransporter-2 (SGLT-2) inhibitors, glucagon-like peptide-1 (GLP-1) receptor agonists, dipeptidyl peptidase-4 inhibitors, thiazolidinediones, sulfonylureas, and insulin. The selection of treatment depends on patient-specific factors including hemoglobin A1c (HbA1c) goal, potential effects on weight, risk of hypoglycemia, and comorbidities such as atherosclerotic cardiovascular disease, heart failure, or chronic kidney disease.2
HbA1c level reflects the mean blood glucose over the previous 3 months and serves as an indication of diabetes control. In patients with diabetes, it is recommended that HbA1c is checked ≥ 2 times annually for those meeting treatment goals, or more often if the patient needs to adjust medications to reach their HbA1c goal. The goal HbA1c level for most adults with diabetes is < 7%.3 This target can be adjusted based on age, comorbidities, or other patient factors. It is generally recommended that frequent glucose monitoring is not needed for patients with T2DM who are only taking oral agents and/or noninsulin injectables. However, for those on insulin regimens, it is advised to monitor glucose closely, with even more frequent testing for those with an intensive insulin regimen.3
Most patients with diabetes use fingerstick testing to self-monitor their blood glucose. However, continuous glucose monitors (CGMs) are becoming widely available and offer a solution to those who do not have the ability to check their glucose multiple times a day and throughout the night. The American Diabetes Association recommends that the frequency and timing of blood glucose monitoring, or the consideration of CGM use, should be based on the specific needs and goals of each patient.3 Guidelines also encourage those on intensive insulin regimens to check glucose levels when fasting, before and after meals, prior to exercise, and when hypoglycemia or hyperglycemia is suspected. Frequent testing can become a burden for patients, whereas once a CGM sensor is placed, it can be worn for 10 to 14 days. CGMs are also capable of transmitting glucose readings every 1 to 15 minutes to a receiver or mobile phone, allowing for further adaptability to a patient’s lifestyle.3
CGMs work by measuring the interstitial glucose with a small filament sensor and have demonstrated accuracy when compared to blood glucose readings. The ability of a CGM to accurately reflect HbA1c levels is a potential benefit, reducing the need for frequent testing to determine whether patients have achieved glycemic control.4 Another benefit of a CGM is the ease of sharing data; patient accounts can be linked with a health care site, allowing clinicians to access glucose data even if the patient is not able to be seen in clinic. This allows health care practitioners (HCPs) to more efficiently tailor medications and optimize regimens based on patient-specific data that was not available by fingerstick testing alone.
Vigersky and colleagues provided one of the few studies on the long-term effects of CGM in patients managing T2DM through diet and exercise alone, oral medications, or basal insulin and found significant improvement in HbA1c after only 3 months of CGM use.5
An important aspect of CGM use is the ability to alert the patient to low blood glucose readings, which can be dangerous for those unaware of hypoglycemia. Many studies have investigated the association between CGM use and acute metabolic events, demonstrating the potential for CGMs to prevent these emergencies. Karter and colleagues found a reduction in emergency department visits and hospitalizations for hypoglycemia associated with the use of CGMs in patients with type 1 DM (T1DM) and T2DM.6
There have been few studies on the use of CGM in veterans. Langford and colleagues found a reduction of HbA1c among veterans with T2DM using CGMs. However, > 50% of the patients in the study were not receiving insulin therapy, which currently is a US Department of Veterans Affairs (VA) CGM criteria for use.7 While current studies provide evidence that supports improvement in HbA1c levels with the use of CGMs, data are lacking for veterans with T2DM taking insulin. There is also minimal research that indicates which patients should be offered a CGM. The objective of this study was to evaluate glycemic control in veterans with T2DM on insulin using a CGM who were previously monitoring blood glucose with fingerstick testing. Secondary endpoints were explored to identify subgroups that may benefit from a CGM and other potential advantages of CGMs.
Methods
This was a retrospective study of veterans who transitioned from fingerstick testing to CGM for glucose monitoring. Each veteran served as their own control to limit confounding variables when comparing HbA1c levels. Veterans with an active or suspended CGM order were identified by reviewing outpatient prescription data. All data collection and analysis were done within the Veterans Affairs Sioux Falls Health Care System.
The primary objective of this study was to assess glycemic control from the use of a CGM by evaluating the change in HbA1c after transitioning to a CGM compared to the change in HbA1c with standard fingerstick monitoring. Three HbA1c values were collected for each veteran: before starting CGM, at initiation, and following CGM initiation (Figure 1). CGM start date was the date the CGM prescription order was placed. The pre-CGM HbA1c level was ≥ 1 year prior to the CGM start date or the HbA1c closest to 1 year. The start CGM HbA1c level was within 3 months before or 1 month after the CGM start date. The post-CGM HbA1c level was the most recent time of data collection and at least 6 months after CGM initiation. The change in HbA1c from fingerstick glucose monitoring was the difference between the pre-CGM and start CGM values. The change in HbA1c from use of a CGM was the difference between start CGM and post-CGM values, which were compared to determine HbA1c reduction from CGM use.

This study also explored secondary outcomes including changes in HbA1c by prescriber type, differences in HbA1c reduction based on age, and changes in diabetes medications, including total daily insulin doses. For secondary outcomes, diabetes medication information and the total daily dose of insulin were gathered at the start of CGM use and at the time of data collection. The most recent CGM order prescribed was also collected.
Veterans were included if they were aged ≥ 18 years, had an active order for a CGM, T2DM diagnosis, an insulin prescription, and previously used test strips for glucose monitoring. Patients with T1DM, those who accessed CGMs or care in the community, and patients without HbA1c values pre-CGM, were excluded.
Statistical Analysis
The primary endpoint of change in HbA1c level before and after CGM use was compared using a paired t test. A 0.5% change in HbA1c was considered clinically significant, as suggested in other studies.8,9P < .05 was considered statistically significant. Analysis for continuous baseline characteristics, including age and total daily insulin, were reported as mean values. Nominal characteristics including sex, race, diabetes medications, and prescriber type are reported as percentages.
Results
A total of 402 veterans were identified with an active CGM at the time of initial data collection in January 2024 and 175 met inclusion criteria. Sixty patients were excluded due to diabetes managed through a community HCP, 38 had T1DM, and 129 lacked HbA1c within all specified time periods. The 175 veterans were randomized, and 150 were selected to perform a chart review for data collection. The mean age was 70 years, most were male and identified as White (Table 1). The majority of patients were managed by endocrinology (53.3%), followed by primary care (24.0%), and pharmacy (22.7%) (Table 2). The mean baseline HbA1c was 8.6%.


The difference in HbA1c before and after use of CGM was -0.97% (P = .0001). Prior to use of a CGM the change in HbA1c was minimal, with an increase of 0.003% with the use of selfmonitoring glucose. After use of a CGM, HbA1c decreased by 0.971%. This reduction in HbA1c would also be considered clinically significant as the change was > 0.5%. The mean pre-, at start, and post-CGM HbA1c levels were 8.6%, 8.6%, and 7.6%, respectively (Figure 2). Pharmacy prescribers had a 0.7% reduction in HbA1c post-CGM, the least of all prescribers. While most age groups saw a reduction in HbA1c, those aged ≥ 80 years had an increase of 0.18% (Table 3). There was an overall mean reduction in insulin of 22 units, which was similar between all prescribers.


Discussion
The primary endpoint of difference in change of HbA1c before and after CGM use was found to be statistically and clinically significant, with a nearly 1% reduction in HbA1c, which was similar to the reduction found by Vigersky and colleagues. 5 Across all prescribers, post-CGM HbA1c levels were similar; however, patients with CGM prescribed by pharmacists had the smallest change in HbA1c. VA pharmacists primarily assess veterans taking insulin who have HbA1c levels that are below the goal with the aim of decreasing insulin to reduce the risk of hypoglycemia, which could result in increased HbA1c levels. This may also explain the observed increase in post-CGM HbA1c levels in patients aged ≥ 80 years. Patients under the care of pharmacists also had baseline mean HbA1c levels that were lower than primary care and endocrinology prescribers and were closer to their HbA1c goal at baseline, which likely was reflected in the smaller reduction in post-CGM HbA1c level.
While there was a decrease in HbA1c levels with CGM use, there were also changes to medications during this timeframe that also may have impacted HbA1c levels. The most common diabetes medications started during CGM use were GLP-1 agonists and SGLT2-inhibitors. Additionally, there was a reduction in the total daily dose of insulin in the study population. These results demonstrate the potential benefits of CGMs for prescribers who take advantage of the CGM glucose data available to assist with medication adjustments. Another consideration for differences in changes of HbA1c among prescriber types is the opportunity for more frequent follow- up visits with pharmacy or endocrinology compared with primary care. If veterans are followed more closely, it may be associated with improved HbA1c control. Further research investigating changes in HbA1c levels based on followup frequency may be useful.
Strengths and Limitations
The crossover design was a strength of this study. This design reduced confounding variables by having veterans serve as their own controls. In addition, the collection of multiple secondary outcomes adds to the knowledge base for future studies. This study focused on a unique population of veterans with T2DM who were taking insulin, an area that previously had very little data available to determine the benefits of CGM use.
Although the use of a CGM showed statistical significance in lowering HbA1c, many veterans were started on new diabetes medication during the period of CGM use, which also likely contributed to the reduction in HbA1c and may have confounded the results. The study was limited by its small population size due to time constraints of chart reviews and the limited generalizability of results outside of the VA system. The majority of patients were from a single site, male and identified as White, which may not be reflective of other VA and community health care systems. It was also noted that the time from the initiation of CGM use to the most recent HbA1c level varied from 6 months to several years. Additionally, veterans managed by community-based HCPs with complex diabetes cases were excluded.
Conclusions
This study demonstrated a clinically and statistically significant reduction in HbA1c with the use of a CGM compared to fingerstick monitoring in veterans with T2DM who were being treated with insulin. The change in post-CGM HbA1c levels across prescribers was similar. In the subgroup analysis of change in HbA1c among age groups, there was a lower HbA1c reduction in individuals aged ≥ 80 years. The results from this study support the idea that CGM use may be beneficial for patients who require a reduction in HbA1c by allowing more precise adjustments to medications and optimization of therapy, as well as the potential to reduce insulin requirements, which is especially valuable in the older adult veteran population.
- US Department of Veterans Affairs. VA supports veterans who have type 2 diabetes. VA News. Accessed September 30, 2024. https://news.va.gov/107579/va-supports-veterans-who-have-type-2-diabetes/
- ElSayed NA, Aleppo G, Aroda VR, et al. 9. Pharmacologic approaches to glycemic treatment: standards of care in diabetes-2023. Diabetes Care. 2023;46(Suppl 1):S140- S157. doi:10.2337/dc23-S009
- ElSayed NA, Aleppo G, Aroda VR, et al. 6. Glycemic targets: standards of care in diabetes-2023. Diabetes Care. 2023;46(Suppl 1):S97-S110. doi:10.2337/dc23-S006
- Miller E, Gavin JR, Kruger DF, Brunton SA. Continuous glucose monitoring: optimizing diabetes care: executive summary. Clin Diabetes. 2022;40(4):394-398. doi:10.2337/cd22-0043
- Vigersky RA, Fonda SJ, Chellappa M, Walker MS, Ehrhardt NM. Short- and long-term effects of real-time continuous glucose monitoring in patients with type 2 diabetes. Diabetes Care. 2012;35(1):32-38. doi:10.2337/dc11-1438
- Karter AJ, Parker MM, Moffet HH, Gilliam LK, Dlott R. Association of real-time continuous glucose monitoring with glycemic control and acute metabolic events among patients with insulin-treated diabetes. JAMA. 2021;325(22):2273-2284. doi:10.1001/JAMA.2021.6530
- Langford SN, Lane M, Karounos D. Continuous blood glucose monitoring outcomes in veterans with type 2 diabetes. Fed Pract. 2021;38(Suppl 4):S14-S17. doi:10.12788/fp.0189
- Radin MS. Pitfalls in hemoglobin A1c measurement: when results may be misleading. J Gen Intern Med. 2014;29(2):388-394. doi:10.1007/s11606-013-2595-x.
- Little RR, Rohlfing CL, Sacks DB; National Glycohemoglobin Standardization Program (NGSP) steering committee. Status of hemoglobin A1c measurement and goals for improvement: from chaos to order for improving diabetes care. Clin Chem. 2011;57(2):205-214. doi:10.1373/clinchem.2010.148841
- US Department of Veterans Affairs. VA supports veterans who have type 2 diabetes. VA News. Accessed September 30, 2024. https://news.va.gov/107579/va-supports-veterans-who-have-type-2-diabetes/
- ElSayed NA, Aleppo G, Aroda VR, et al. 9. Pharmacologic approaches to glycemic treatment: standards of care in diabetes-2023. Diabetes Care. 2023;46(Suppl 1):S140- S157. doi:10.2337/dc23-S009
- ElSayed NA, Aleppo G, Aroda VR, et al. 6. Glycemic targets: standards of care in diabetes-2023. Diabetes Care. 2023;46(Suppl 1):S97-S110. doi:10.2337/dc23-S006
- Miller E, Gavin JR, Kruger DF, Brunton SA. Continuous glucose monitoring: optimizing diabetes care: executive summary. Clin Diabetes. 2022;40(4):394-398. doi:10.2337/cd22-0043
- Vigersky RA, Fonda SJ, Chellappa M, Walker MS, Ehrhardt NM. Short- and long-term effects of real-time continuous glucose monitoring in patients with type 2 diabetes. Diabetes Care. 2012;35(1):32-38. doi:10.2337/dc11-1438
- Karter AJ, Parker MM, Moffet HH, Gilliam LK, Dlott R. Association of real-time continuous glucose monitoring with glycemic control and acute metabolic events among patients with insulin-treated diabetes. JAMA. 2021;325(22):2273-2284. doi:10.1001/JAMA.2021.6530
- Langford SN, Lane M, Karounos D. Continuous blood glucose monitoring outcomes in veterans with type 2 diabetes. Fed Pract. 2021;38(Suppl 4):S14-S17. doi:10.12788/fp.0189
- Radin MS. Pitfalls in hemoglobin A1c measurement: when results may be misleading. J Gen Intern Med. 2014;29(2):388-394. doi:10.1007/s11606-013-2595-x.
- Little RR, Rohlfing CL, Sacks DB; National Glycohemoglobin Standardization Program (NGSP) steering committee. Status of hemoglobin A1c measurement and goals for improvement: from chaos to order for improving diabetes care. Clin Chem. 2011;57(2):205-214. doi:10.1373/clinchem.2010.148841

VA Cancer Clinical Trials as a Strategy for Increasing Accrual of Racial and Ethnic Underrepresented Groups
Background
Cancer clinical trials (CCTs) are central to improving cancer care. However, generalizability of findings from CCTs is difficult due to the lack of diversity in most United States CCTs. Clinical trial accrual of underrepresented groups, is low throughout the United States and is approximately 4-5% in most CCTs. Reasons for low accrual in this population are multifactorial. Despite numerous factors related to accruing racial and ethnic underrepresented groups, many institutions have sought to address these barriers. We conducted a scoping review to identify evidence-based approaches to increase participation in cancer treatment clinical trials.
Methods
We reviewed the Salisbury VA Medical Center Oncology clinical trial database from October 2019 to June 2024. The participants in these clinical trials required consent. These clinical trials included treatment interventional as well as non-treatment interventional. Fifteen studies were included and over 260 Veterans participated.
Results
Key themes emerged that included a focus on patient education, cultural competency, and building capacity in the clinics to care for the Veteran population at three separate sites in the Salisbury VA system. The Black Veteran accrual rate of 29% was achieved. This accrual rate is representative of our VA catchment population of 33% for Black Veterans, and is five times the national average.
Conclusions
The research team’s success in enrolling Black Veterans in clinical trials is attributed to several factors. The demographic composition of Veterans served by the Salisbury, Charlotte, and Kernersville VA provided a diverse population that included a 33% Black group. The type of clinical trials focused on patients who were most impacted by the disease. The VA did afford less barriers to access to health care.
Background
Cancer clinical trials (CCTs) are central to improving cancer care. However, generalizability of findings from CCTs is difficult due to the lack of diversity in most United States CCTs. Clinical trial accrual of underrepresented groups, is low throughout the United States and is approximately 4-5% in most CCTs. Reasons for low accrual in this population are multifactorial. Despite numerous factors related to accruing racial and ethnic underrepresented groups, many institutions have sought to address these barriers. We conducted a scoping review to identify evidence-based approaches to increase participation in cancer treatment clinical trials.
Methods
We reviewed the Salisbury VA Medical Center Oncology clinical trial database from October 2019 to June 2024. The participants in these clinical trials required consent. These clinical trials included treatment interventional as well as non-treatment interventional. Fifteen studies were included and over 260 Veterans participated.
Results
Key themes emerged that included a focus on patient education, cultural competency, and building capacity in the clinics to care for the Veteran population at three separate sites in the Salisbury VA system. The Black Veteran accrual rate of 29% was achieved. This accrual rate is representative of our VA catchment population of 33% for Black Veterans, and is five times the national average.
Conclusions
The research team’s success in enrolling Black Veterans in clinical trials is attributed to several factors. The demographic composition of Veterans served by the Salisbury, Charlotte, and Kernersville VA provided a diverse population that included a 33% Black group. The type of clinical trials focused on patients who were most impacted by the disease. The VA did afford less barriers to access to health care.
Background
Cancer clinical trials (CCTs) are central to improving cancer care. However, generalizability of findings from CCTs is difficult due to the lack of diversity in most United States CCTs. Clinical trial accrual of underrepresented groups, is low throughout the United States and is approximately 4-5% in most CCTs. Reasons for low accrual in this population are multifactorial. Despite numerous factors related to accruing racial and ethnic underrepresented groups, many institutions have sought to address these barriers. We conducted a scoping review to identify evidence-based approaches to increase participation in cancer treatment clinical trials.
Methods
We reviewed the Salisbury VA Medical Center Oncology clinical trial database from October 2019 to June 2024. The participants in these clinical trials required consent. These clinical trials included treatment interventional as well as non-treatment interventional. Fifteen studies were included and over 260 Veterans participated.
Results
Key themes emerged that included a focus on patient education, cultural competency, and building capacity in the clinics to care for the Veteran population at three separate sites in the Salisbury VA system. The Black Veteran accrual rate of 29% was achieved. This accrual rate is representative of our VA catchment population of 33% for Black Veterans, and is five times the national average.
Conclusions
The research team’s success in enrolling Black Veterans in clinical trials is attributed to several factors. The demographic composition of Veterans served by the Salisbury, Charlotte, and Kernersville VA provided a diverse population that included a 33% Black group. The type of clinical trials focused on patients who were most impacted by the disease. The VA did afford less barriers to access to health care.

Clinical Accuracy of Skin Cancer Diagnosis: Investigation of Keratinocyte Carcinoma Mismatch Rates
Clinical Accuracy of Skin Cancer Diagnosis: Investigation of Keratinocyte Carcinoma Mismatch Rates
To the Editor:
The incidence of nonmelanoma skin cancer (NMSC) is rapidly increasing worldwide. Due to its highly curable nature when treated early, accurate diagnosis is the cornerstone to good patient outcomes.1 Accurate diagnosis of skin cancer and subsequent treatment decisions rely heavily on the congruence between clinical observations and histopathologic assessments. Clinical misdiagnosis of a malignant lesion can lead to delayed and suboptimal treatment, which may contribute to serious complications such as metastasis or even mortality. In this study, data from clinically diagnosed basal cell carcinomas (BCCs) and squamous cell carcinomas (SCCs) were compared to their identified histopathologic subtype classifications. The accuracy of the clinical diagnosis of these NMSCs was assessed by determining the rate of misdiagnosis and the respective positive predictive value (PPV).
A retrospective review of medical records from a private dermatology practice in Lubbock, Texas, was conducted to identify patients diagnosed with NMSC from January 1, 2017, through December 31, 2021. A total of 11,229 NMSCs were diagnosed and treated in 5877 patients. Of the NMSCs diagnosed, 11,145 were identified as keratinocyte carcinomas and were classified as BCCs or SCCs. The accuracy of the clinical diagnoses was determined by comparison to the histologic subtype identified via biopsy of the lesion. Although the use of a dermatoscope during the clinical encounter was not formally recorded, reports from the examining dermatologists indicated it was not used in the majority of cases.
If a lesion was clinically diagnosed as a BCC but was identified as a subtype of SCC on histology (or vice versa), the lesion was considered to be mismatched. The number of mismatched lesions and the mismatch rate for each lesion type/subtype is recorded in the Table. Of the total 11,145 keratinocyte carcinomas included in our study, there was an overall 10.63% mismatch rate, with 1185 of the malignancies having a differing clinical diagnosis (eg, BCC vs SCC) from the histologic findings. The clinical mismatch rate was notably higher for SCC compared to BCC (15.83% vs 7.03%, respectively).

The Table provides a breakdown of the BCC subtypes identified by histology with their computed mismatch rate and PPV. It is worth clarifying that lesions classified as more than one BCC subtype per the histologic findings were diagnosed as mixed BCC; these were further classified as mixed-aggressive BCC (if at least one aggressive BCC subtype was present) and mixed nonaggressive BCC (if no aggressive BCC subtype was present). Overall, BCCs were less likely to be misdiagnosed, with an average PPV of 92.97% compared to 84.17% for SCCs. Basosquamous BCC was the BCC subtype with the highest mismatch rate (25.48%), while sclerosing BCC has the lowest overall mismatch rate (1.33%). The most common malignancy was BCC, with nodular BCC being the most common subtype.
The Table also breaks down the SCC subtypes, reporting the most commonly misdiagnosed of any BCC or SCC subtype to be poorly differentiated SCC (mismatch rate, 38.46%). The lowest mismatch rate of the SCC subtypes was 5.97% for well-differentiated SCC.
There was an overall PPV of 89.37% in clinically evaluated malignancies and their respective histologic subtypes. Basal cell carcinoma had a lower overall mismatch rate of 7.03% compared to 15.83% in SCC. The most common misdiagnosis was attributed to poorly differentiated SCC (mismatch rate, 38.46%), while the least common misdiagnosed malignancy was sclerosing BCC (1.33%). The high mismatch rate of poorly differentiated SCC may be due to its diverging presentation from a typical SCC as a flat lesion with the absence of scaling, keratin, or bleeding, leading to the misdiagnosis of BCC.2
Accurate clinical diagnosis of NMSCs is the basis for further evaluation and treatment that should ensue in a timely manner; however, accurately identifying BCCs vs SCCs solely based on clinical examination can be challenging due to variable manifestations and overlapping features. Basal cell carcinoma commonly presents as a shiny pink/flesh-colored nodule, macule, or patch with surface telangiectasia, sometimes appearing with ulceration or crusting.3 Alternatively, SCC typically appears as a firm, sharply demarcated, red nodule with a thick overlying scale.4 Definitive diagnoses can be difficult upon clinical examination since these features can be shared between the 2 subtypes. To aid in these uncertainties, a growing number of clinicians are implementing the use of dermoscopy in their everyday practice.
Dermoscopy is an extremely useful tool in improving the diagnostic accuracy of skin cancers compared to examination with the naked eye, as it provides detailed visualization of specific structures and patterns in skin cancer lesions.5 The dermoscopic appearance of BCC is characterized by pearly blue-gray or translucent globules with arborizing vessels, spoke-wheel structures, and leaflike areas.5,6 Conversely, dermoscopic features of SCC may include a milky-red globule with a scaly, sharply demarcated, crusted lesion with polymorphous vasculature, sometimes resembling a persistent sore or nonhealing wound.4,5 Though the use of dermoscopy can aid in diagnosis upon initial examination, certain factors such as trauma, ulceration, and previous treatments that distorted the lesion’s architecture may lead to misdiagnosis. Furthermore, the distinct vascular patterns found in BCC and SCC may be mistaken for each other and therefore lead to misdiagnosis upon examination.7 Other variables that may complicate diagnosis include the location of the lesion, its size, and the presence of other skin conditions or nearby lesions.
The primary limitation of the current study was the limited scope of the data, as they were derived from patients seen at one private dermatology practice, preventing the generalizability of our findings. However, our results show trends similar to those observed in other studies analyzing the clinical accuracy of skin cancer diagnoses, with higher PPVs for BCC compared to SCC. A study by Ahnlide and Bjellerup8 was based in a hospital dermatology department and demonstrated a PPV of 85.5% for BCC compared to 92.97% in our study; for SCC, the PPV was 67.3% compared to 84.17% in our study. In another study by Heal et al,9 data were collected from an Australian registry that included records of all histologically confirmed skin cancers from December 1996 to October 1999 from 202 general practitioners and 42 specialists, including 1 dermatologist. The PPVs for BCC and SCC were 72.7% and 49.4%, respectively. Although our results indicated higher PPVs compared to these 2 studies, some of the discrepancies can be accounted for by the differences in clinical setting as well as the lack of expertise of nondermatologist physicians in identifying skin malignancies in the study by Heal et al.9
The current study was further limited by the lack of data quantifying the number of lesions clinically suspected to be malignant but found to be histologically benign. It is typical for clinicians to have a low threshold to biopsy a suspicious lesion with atypical features (eg, rapid evolution and growth, bleeding, crusting). Furthermore, the identification of risk factors in the patient’s medical and family history (eg, exposure to radiation, personal or family history of skin cancers) can heavily influence a clinician’s decision to biopsy a lesion with an atypical appearance.10 Many benign lesions are biopsied to avoid missing a diagnosis of malignancy. Consequently, our results suggest a high degree of clinical misdiagnosis of BCCs and SCCs. Obtaining data on the number of lesions suspected to be BCC or SCC that were found to be histologically benign would be a valuable addition to our study, as it would provide a measurable insight into the sensitivity of clinicians’ decision-making to identify a lesion as suspicious and warranting biopsy.
While clinical diagnosis plays a vital role in identifying suspected NMSCs such as BCC and SCC, its accuracy can be limited even with the use of dermoscopy. Overall, our data have shown a high rate of diagnostic accuracy upon suspicion of malignancy, but the different variables that affect clinical presentation promote histologic diagnosis to prevail as the gold standard.
- Seyed Ahadi M, Firooz A, Rahimi H, et al. Clinical diagnosis has a high negative predictive value in evaluation of malignant skin lesions. Dermatol Res Pract. 2021;2021:6618990. doi:10.1155/2021/6618990
- Lallas A, Pyne J, Kyrgidis A, et al. The clinical and dermoscopic features of invasive cutaneous squamous cell carcinoma depend on the histopathological grade of differentiation. Br J Dermatol. 2015;172:1308- 1315. doi:10.1111/bjd.13510
- McDaniel B, Badri T, Steele RB. Basal cell carcinoma. September 19, 2022. In: StatPearls. StatPearls Publishing; 2023.
- Suárez AL, Louis P, Kitts J, et al. Clinical and dermoscopic features of combined cutaneous squamous cell carcinoma (SCC)/neuroendocrine [Merkel cell] carcinoma (MCC). J Am Acad Dermatol. 2015;73:968-975. doi:10.1016/j.jaad.2015.08.041
- Wolner ZJ, Yélamos O, Liopyris K, et al. Enhancing skin cancer diagnosis with dermoscopy. Dermatol Clin. 2017;35:417-437. doi:10.1016/j.det.2017.06.003
- Reiter O, Mimouni I, Dusza S, et al. Dermoscopic features of basal cell carcinoma and its subtypes: a systematic review. J Am Acad Dermatol. 2021;85:653-664. doi:10.1016/j.jaad.2019.11.008
- Pruneda C, Ramesh M, Hope L, et al. Nonmelanoma skin cancers: diagnostic accuracy of midlevel providers versus dermatologists. The Dermatologist. March 2023. Accessed March 18, 2025. https://www.hmpgloballearningnetwork.com/site/thederm/feature-story/nonmelanoma-skin-cancers-diagnostic-accuracy-midlevel-providers-vs
- Ahnlide I, Bjellerup M. Accuracy of clinical skin tumour diagnosis in a dermatological setting. Acta Derm Venereol. 2013;93:305-308. doi:10.2340/00015555-1560
- Heal CF, Raasch BA, Buettner PG, et al. Accuracy of clinical diagnosis of skin lesions. Br J Dermatol. 2008;159:661-668.
- Fu S, Kim S, Wasko C. Dermatological guide for primary care physicians: full body skin checks, skin cancer detection, and patient education on self-skin checks and sun protection. Proc (Bayl Univ Med Cent). 2024;37:647-654. doi:10.1080/08998280.2024.2351751
To the Editor:
The incidence of nonmelanoma skin cancer (NMSC) is rapidly increasing worldwide. Due to its highly curable nature when treated early, accurate diagnosis is the cornerstone to good patient outcomes.1 Accurate diagnosis of skin cancer and subsequent treatment decisions rely heavily on the congruence between clinical observations and histopathologic assessments. Clinical misdiagnosis of a malignant lesion can lead to delayed and suboptimal treatment, which may contribute to serious complications such as metastasis or even mortality. In this study, data from clinically diagnosed basal cell carcinomas (BCCs) and squamous cell carcinomas (SCCs) were compared to their identified histopathologic subtype classifications. The accuracy of the clinical diagnosis of these NMSCs was assessed by determining the rate of misdiagnosis and the respective positive predictive value (PPV).
A retrospective review of medical records from a private dermatology practice in Lubbock, Texas, was conducted to identify patients diagnosed with NMSC from January 1, 2017, through December 31, 2021. A total of 11,229 NMSCs were diagnosed and treated in 5877 patients. Of the NMSCs diagnosed, 11,145 were identified as keratinocyte carcinomas and were classified as BCCs or SCCs. The accuracy of the clinical diagnoses was determined by comparison to the histologic subtype identified via biopsy of the lesion. Although the use of a dermatoscope during the clinical encounter was not formally recorded, reports from the examining dermatologists indicated it was not used in the majority of cases.
If a lesion was clinically diagnosed as a BCC but was identified as a subtype of SCC on histology (or vice versa), the lesion was considered to be mismatched. The number of mismatched lesions and the mismatch rate for each lesion type/subtype is recorded in the Table. Of the total 11,145 keratinocyte carcinomas included in our study, there was an overall 10.63% mismatch rate, with 1185 of the malignancies having a differing clinical diagnosis (eg, BCC vs SCC) from the histologic findings. The clinical mismatch rate was notably higher for SCC compared to BCC (15.83% vs 7.03%, respectively).

The Table provides a breakdown of the BCC subtypes identified by histology with their computed mismatch rate and PPV. It is worth clarifying that lesions classified as more than one BCC subtype per the histologic findings were diagnosed as mixed BCC; these were further classified as mixed-aggressive BCC (if at least one aggressive BCC subtype was present) and mixed nonaggressive BCC (if no aggressive BCC subtype was present). Overall, BCCs were less likely to be misdiagnosed, with an average PPV of 92.97% compared to 84.17% for SCCs. Basosquamous BCC was the BCC subtype with the highest mismatch rate (25.48%), while sclerosing BCC has the lowest overall mismatch rate (1.33%). The most common malignancy was BCC, with nodular BCC being the most common subtype.
The Table also breaks down the SCC subtypes, reporting the most commonly misdiagnosed of any BCC or SCC subtype to be poorly differentiated SCC (mismatch rate, 38.46%). The lowest mismatch rate of the SCC subtypes was 5.97% for well-differentiated SCC.
There was an overall PPV of 89.37% in clinically evaluated malignancies and their respective histologic subtypes. Basal cell carcinoma had a lower overall mismatch rate of 7.03% compared to 15.83% in SCC. The most common misdiagnosis was attributed to poorly differentiated SCC (mismatch rate, 38.46%), while the least common misdiagnosed malignancy was sclerosing BCC (1.33%). The high mismatch rate of poorly differentiated SCC may be due to its diverging presentation from a typical SCC as a flat lesion with the absence of scaling, keratin, or bleeding, leading to the misdiagnosis of BCC.2
Accurate clinical diagnosis of NMSCs is the basis for further evaluation and treatment that should ensue in a timely manner; however, accurately identifying BCCs vs SCCs solely based on clinical examination can be challenging due to variable manifestations and overlapping features. Basal cell carcinoma commonly presents as a shiny pink/flesh-colored nodule, macule, or patch with surface telangiectasia, sometimes appearing with ulceration or crusting.3 Alternatively, SCC typically appears as a firm, sharply demarcated, red nodule with a thick overlying scale.4 Definitive diagnoses can be difficult upon clinical examination since these features can be shared between the 2 subtypes. To aid in these uncertainties, a growing number of clinicians are implementing the use of dermoscopy in their everyday practice.
Dermoscopy is an extremely useful tool in improving the diagnostic accuracy of skin cancers compared to examination with the naked eye, as it provides detailed visualization of specific structures and patterns in skin cancer lesions.5 The dermoscopic appearance of BCC is characterized by pearly blue-gray or translucent globules with arborizing vessels, spoke-wheel structures, and leaflike areas.5,6 Conversely, dermoscopic features of SCC may include a milky-red globule with a scaly, sharply demarcated, crusted lesion with polymorphous vasculature, sometimes resembling a persistent sore or nonhealing wound.4,5 Though the use of dermoscopy can aid in diagnosis upon initial examination, certain factors such as trauma, ulceration, and previous treatments that distorted the lesion’s architecture may lead to misdiagnosis. Furthermore, the distinct vascular patterns found in BCC and SCC may be mistaken for each other and therefore lead to misdiagnosis upon examination.7 Other variables that may complicate diagnosis include the location of the lesion, its size, and the presence of other skin conditions or nearby lesions.
The primary limitation of the current study was the limited scope of the data, as they were derived from patients seen at one private dermatology practice, preventing the generalizability of our findings. However, our results show trends similar to those observed in other studies analyzing the clinical accuracy of skin cancer diagnoses, with higher PPVs for BCC compared to SCC. A study by Ahnlide and Bjellerup8 was based in a hospital dermatology department and demonstrated a PPV of 85.5% for BCC compared to 92.97% in our study; for SCC, the PPV was 67.3% compared to 84.17% in our study. In another study by Heal et al,9 data were collected from an Australian registry that included records of all histologically confirmed skin cancers from December 1996 to October 1999 from 202 general practitioners and 42 specialists, including 1 dermatologist. The PPVs for BCC and SCC were 72.7% and 49.4%, respectively. Although our results indicated higher PPVs compared to these 2 studies, some of the discrepancies can be accounted for by the differences in clinical setting as well as the lack of expertise of nondermatologist physicians in identifying skin malignancies in the study by Heal et al.9
The current study was further limited by the lack of data quantifying the number of lesions clinically suspected to be malignant but found to be histologically benign. It is typical for clinicians to have a low threshold to biopsy a suspicious lesion with atypical features (eg, rapid evolution and growth, bleeding, crusting). Furthermore, the identification of risk factors in the patient’s medical and family history (eg, exposure to radiation, personal or family history of skin cancers) can heavily influence a clinician’s decision to biopsy a lesion with an atypical appearance.10 Many benign lesions are biopsied to avoid missing a diagnosis of malignancy. Consequently, our results suggest a high degree of clinical misdiagnosis of BCCs and SCCs. Obtaining data on the number of lesions suspected to be BCC or SCC that were found to be histologically benign would be a valuable addition to our study, as it would provide a measurable insight into the sensitivity of clinicians’ decision-making to identify a lesion as suspicious and warranting biopsy.
While clinical diagnosis plays a vital role in identifying suspected NMSCs such as BCC and SCC, its accuracy can be limited even with the use of dermoscopy. Overall, our data have shown a high rate of diagnostic accuracy upon suspicion of malignancy, but the different variables that affect clinical presentation promote histologic diagnosis to prevail as the gold standard.
To the Editor:
The incidence of nonmelanoma skin cancer (NMSC) is rapidly increasing worldwide. Due to its highly curable nature when treated early, accurate diagnosis is the cornerstone to good patient outcomes.1 Accurate diagnosis of skin cancer and subsequent treatment decisions rely heavily on the congruence between clinical observations and histopathologic assessments. Clinical misdiagnosis of a malignant lesion can lead to delayed and suboptimal treatment, which may contribute to serious complications such as metastasis or even mortality. In this study, data from clinically diagnosed basal cell carcinomas (BCCs) and squamous cell carcinomas (SCCs) were compared to their identified histopathologic subtype classifications. The accuracy of the clinical diagnosis of these NMSCs was assessed by determining the rate of misdiagnosis and the respective positive predictive value (PPV).
A retrospective review of medical records from a private dermatology practice in Lubbock, Texas, was conducted to identify patients diagnosed with NMSC from January 1, 2017, through December 31, 2021. A total of 11,229 NMSCs were diagnosed and treated in 5877 patients. Of the NMSCs diagnosed, 11,145 were identified as keratinocyte carcinomas and were classified as BCCs or SCCs. The accuracy of the clinical diagnoses was determined by comparison to the histologic subtype identified via biopsy of the lesion. Although the use of a dermatoscope during the clinical encounter was not formally recorded, reports from the examining dermatologists indicated it was not used in the majority of cases.
If a lesion was clinically diagnosed as a BCC but was identified as a subtype of SCC on histology (or vice versa), the lesion was considered to be mismatched. The number of mismatched lesions and the mismatch rate for each lesion type/subtype is recorded in the Table. Of the total 11,145 keratinocyte carcinomas included in our study, there was an overall 10.63% mismatch rate, with 1185 of the malignancies having a differing clinical diagnosis (eg, BCC vs SCC) from the histologic findings. The clinical mismatch rate was notably higher for SCC compared to BCC (15.83% vs 7.03%, respectively).

The Table provides a breakdown of the BCC subtypes identified by histology with their computed mismatch rate and PPV. It is worth clarifying that lesions classified as more than one BCC subtype per the histologic findings were diagnosed as mixed BCC; these were further classified as mixed-aggressive BCC (if at least one aggressive BCC subtype was present) and mixed nonaggressive BCC (if no aggressive BCC subtype was present). Overall, BCCs were less likely to be misdiagnosed, with an average PPV of 92.97% compared to 84.17% for SCCs. Basosquamous BCC was the BCC subtype with the highest mismatch rate (25.48%), while sclerosing BCC has the lowest overall mismatch rate (1.33%). The most common malignancy was BCC, with nodular BCC being the most common subtype.
The Table also breaks down the SCC subtypes, reporting the most commonly misdiagnosed of any BCC or SCC subtype to be poorly differentiated SCC (mismatch rate, 38.46%). The lowest mismatch rate of the SCC subtypes was 5.97% for well-differentiated SCC.
There was an overall PPV of 89.37% in clinically evaluated malignancies and their respective histologic subtypes. Basal cell carcinoma had a lower overall mismatch rate of 7.03% compared to 15.83% in SCC. The most common misdiagnosis was attributed to poorly differentiated SCC (mismatch rate, 38.46%), while the least common misdiagnosed malignancy was sclerosing BCC (1.33%). The high mismatch rate of poorly differentiated SCC may be due to its diverging presentation from a typical SCC as a flat lesion with the absence of scaling, keratin, or bleeding, leading to the misdiagnosis of BCC.2
Accurate clinical diagnosis of NMSCs is the basis for further evaluation and treatment that should ensue in a timely manner; however, accurately identifying BCCs vs SCCs solely based on clinical examination can be challenging due to variable manifestations and overlapping features. Basal cell carcinoma commonly presents as a shiny pink/flesh-colored nodule, macule, or patch with surface telangiectasia, sometimes appearing with ulceration or crusting.3 Alternatively, SCC typically appears as a firm, sharply demarcated, red nodule with a thick overlying scale.4 Definitive diagnoses can be difficult upon clinical examination since these features can be shared between the 2 subtypes. To aid in these uncertainties, a growing number of clinicians are implementing the use of dermoscopy in their everyday practice.
Dermoscopy is an extremely useful tool in improving the diagnostic accuracy of skin cancers compared to examination with the naked eye, as it provides detailed visualization of specific structures and patterns in skin cancer lesions.5 The dermoscopic appearance of BCC is characterized by pearly blue-gray or translucent globules with arborizing vessels, spoke-wheel structures, and leaflike areas.5,6 Conversely, dermoscopic features of SCC may include a milky-red globule with a scaly, sharply demarcated, crusted lesion with polymorphous vasculature, sometimes resembling a persistent sore or nonhealing wound.4,5 Though the use of dermoscopy can aid in diagnosis upon initial examination, certain factors such as trauma, ulceration, and previous treatments that distorted the lesion’s architecture may lead to misdiagnosis. Furthermore, the distinct vascular patterns found in BCC and SCC may be mistaken for each other and therefore lead to misdiagnosis upon examination.7 Other variables that may complicate diagnosis include the location of the lesion, its size, and the presence of other skin conditions or nearby lesions.
The primary limitation of the current study was the limited scope of the data, as they were derived from patients seen at one private dermatology practice, preventing the generalizability of our findings. However, our results show trends similar to those observed in other studies analyzing the clinical accuracy of skin cancer diagnoses, with higher PPVs for BCC compared to SCC. A study by Ahnlide and Bjellerup8 was based in a hospital dermatology department and demonstrated a PPV of 85.5% for BCC compared to 92.97% in our study; for SCC, the PPV was 67.3% compared to 84.17% in our study. In another study by Heal et al,9 data were collected from an Australian registry that included records of all histologically confirmed skin cancers from December 1996 to October 1999 from 202 general practitioners and 42 specialists, including 1 dermatologist. The PPVs for BCC and SCC were 72.7% and 49.4%, respectively. Although our results indicated higher PPVs compared to these 2 studies, some of the discrepancies can be accounted for by the differences in clinical setting as well as the lack of expertise of nondermatologist physicians in identifying skin malignancies in the study by Heal et al.9
The current study was further limited by the lack of data quantifying the number of lesions clinically suspected to be malignant but found to be histologically benign. It is typical for clinicians to have a low threshold to biopsy a suspicious lesion with atypical features (eg, rapid evolution and growth, bleeding, crusting). Furthermore, the identification of risk factors in the patient’s medical and family history (eg, exposure to radiation, personal or family history of skin cancers) can heavily influence a clinician’s decision to biopsy a lesion with an atypical appearance.10 Many benign lesions are biopsied to avoid missing a diagnosis of malignancy. Consequently, our results suggest a high degree of clinical misdiagnosis of BCCs and SCCs. Obtaining data on the number of lesions suspected to be BCC or SCC that were found to be histologically benign would be a valuable addition to our study, as it would provide a measurable insight into the sensitivity of clinicians’ decision-making to identify a lesion as suspicious and warranting biopsy.
While clinical diagnosis plays a vital role in identifying suspected NMSCs such as BCC and SCC, its accuracy can be limited even with the use of dermoscopy. Overall, our data have shown a high rate of diagnostic accuracy upon suspicion of malignancy, but the different variables that affect clinical presentation promote histologic diagnosis to prevail as the gold standard.
- Seyed Ahadi M, Firooz A, Rahimi H, et al. Clinical diagnosis has a high negative predictive value in evaluation of malignant skin lesions. Dermatol Res Pract. 2021;2021:6618990. doi:10.1155/2021/6618990
- Lallas A, Pyne J, Kyrgidis A, et al. The clinical and dermoscopic features of invasive cutaneous squamous cell carcinoma depend on the histopathological grade of differentiation. Br J Dermatol. 2015;172:1308- 1315. doi:10.1111/bjd.13510
- McDaniel B, Badri T, Steele RB. Basal cell carcinoma. September 19, 2022. In: StatPearls. StatPearls Publishing; 2023.
- Suárez AL, Louis P, Kitts J, et al. Clinical and dermoscopic features of combined cutaneous squamous cell carcinoma (SCC)/neuroendocrine [Merkel cell] carcinoma (MCC). J Am Acad Dermatol. 2015;73:968-975. doi:10.1016/j.jaad.2015.08.041
- Wolner ZJ, Yélamos O, Liopyris K, et al. Enhancing skin cancer diagnosis with dermoscopy. Dermatol Clin. 2017;35:417-437. doi:10.1016/j.det.2017.06.003
- Reiter O, Mimouni I, Dusza S, et al. Dermoscopic features of basal cell carcinoma and its subtypes: a systematic review. J Am Acad Dermatol. 2021;85:653-664. doi:10.1016/j.jaad.2019.11.008
- Pruneda C, Ramesh M, Hope L, et al. Nonmelanoma skin cancers: diagnostic accuracy of midlevel providers versus dermatologists. The Dermatologist. March 2023. Accessed March 18, 2025. https://www.hmpgloballearningnetwork.com/site/thederm/feature-story/nonmelanoma-skin-cancers-diagnostic-accuracy-midlevel-providers-vs
- Ahnlide I, Bjellerup M. Accuracy of clinical skin tumour diagnosis in a dermatological setting. Acta Derm Venereol. 2013;93:305-308. doi:10.2340/00015555-1560
- Heal CF, Raasch BA, Buettner PG, et al. Accuracy of clinical diagnosis of skin lesions. Br J Dermatol. 2008;159:661-668.
- Fu S, Kim S, Wasko C. Dermatological guide for primary care physicians: full body skin checks, skin cancer detection, and patient education on self-skin checks and sun protection. Proc (Bayl Univ Med Cent). 2024;37:647-654. doi:10.1080/08998280.2024.2351751
- Seyed Ahadi M, Firooz A, Rahimi H, et al. Clinical diagnosis has a high negative predictive value in evaluation of malignant skin lesions. Dermatol Res Pract. 2021;2021:6618990. doi:10.1155/2021/6618990
- Lallas A, Pyne J, Kyrgidis A, et al. The clinical and dermoscopic features of invasive cutaneous squamous cell carcinoma depend on the histopathological grade of differentiation. Br J Dermatol. 2015;172:1308- 1315. doi:10.1111/bjd.13510
- McDaniel B, Badri T, Steele RB. Basal cell carcinoma. September 19, 2022. In: StatPearls. StatPearls Publishing; 2023.
- Suárez AL, Louis P, Kitts J, et al. Clinical and dermoscopic features of combined cutaneous squamous cell carcinoma (SCC)/neuroendocrine [Merkel cell] carcinoma (MCC). J Am Acad Dermatol. 2015;73:968-975. doi:10.1016/j.jaad.2015.08.041
- Wolner ZJ, Yélamos O, Liopyris K, et al. Enhancing skin cancer diagnosis with dermoscopy. Dermatol Clin. 2017;35:417-437. doi:10.1016/j.det.2017.06.003
- Reiter O, Mimouni I, Dusza S, et al. Dermoscopic features of basal cell carcinoma and its subtypes: a systematic review. J Am Acad Dermatol. 2021;85:653-664. doi:10.1016/j.jaad.2019.11.008
- Pruneda C, Ramesh M, Hope L, et al. Nonmelanoma skin cancers: diagnostic accuracy of midlevel providers versus dermatologists. The Dermatologist. March 2023. Accessed March 18, 2025. https://www.hmpgloballearningnetwork.com/site/thederm/feature-story/nonmelanoma-skin-cancers-diagnostic-accuracy-midlevel-providers-vs
- Ahnlide I, Bjellerup M. Accuracy of clinical skin tumour diagnosis in a dermatological setting. Acta Derm Venereol. 2013;93:305-308. doi:10.2340/00015555-1560
- Heal CF, Raasch BA, Buettner PG, et al. Accuracy of clinical diagnosis of skin lesions. Br J Dermatol. 2008;159:661-668.
- Fu S, Kim S, Wasko C. Dermatological guide for primary care physicians: full body skin checks, skin cancer detection, and patient education on self-skin checks and sun protection. Proc (Bayl Univ Med Cent). 2024;37:647-654. doi:10.1080/08998280.2024.2351751
Clinical Accuracy of Skin Cancer Diagnosis: Investigation of Keratinocyte Carcinoma Mismatch Rates
Clinical Accuracy of Skin Cancer Diagnosis: Investigation of Keratinocyte Carcinoma Mismatch Rates
PRACTICE POINTS
- Malignant lesions may be misdiagnosed when assessments are guided by clinical features that align with typical presentations of other lesion types, potentially leading to diagnostic errors among experienced clinicians.
- Although dermoscopy is a beneficial tool in examining potential skin cancers, clinical observations should not bypass the gold standard of histopathologic examination.
Exploring the Relationship Between Psoriasis and Mobility Among US Adults
Exploring the Relationship Between Psoriasis and Mobility Among US Adults
To the Editor:
Psoriasis is a chronic inflammatory condition that affects individuals in various extracutaneous ways.1 Prior studies have documented a decrease in exercise intensity among patients with psoriasis2; however, few studies have specifically investigated baseline mobility in this population. Baseline mobility denotes an individual’s fundamental ability to walk or move around without assistance of any kind. Impaired mobility—when baseline mobility is compromised—is an aspect of the wider diversity, equity, and inclusion framework that underscores the significance of recognizing challenges and promoting inclusive measures, both at the point of care and in research.3 study sought to analyze the relationship between psoriasis and baseline mobility among US adults (aged 45 to 80 years) utilizing the latest data from the National Health and Nutrition Examination Survey (NHANES) database for psoriasis.4 We used three 2-year cycles of NHANES data to create a 2009-2014 dataset.
The overall NHANES response rate among adults aged 45 to 80 years between 2009 and 2014 was 67.9%. Patients were categorized as having impaired mobility if they responded “yes” to the following question: “Because of a health problem, do you have difficulty walking without using any special equipment?” Psoriasis status was assessed by the following question: “Have you ever been told by a doctor or other health professional that you had psoriasis?” Multivariable logistic regression analyses were performed using Stata/SE 18.0 software (StataCorp LLC) to assess the relationship between psoriasis and impaired mobility. Age, income, education, sex, race, tobacco use, diabetes status, body mass index, and arthritis status were controlled for in our models.
Our analysis initially included 9982 participants; 14 did not respond to questions assessing psoriasis and impaired mobility and were excluded. The prevalence of impaired mobility in patients with psoriasis was 17.1% compared with 10.9% among those without psoriasis (Table 1). There was a significant association between psoriasis and impaired mobility among patients aged 45 to 80 years after adjusting for potential confounding variables (adjusted odds ratio [AOR], 1.54; 95% CI, 1.04- 2.29; P=.032)(Table 2). Analyses of subgroups yielded no statistically significant results.



Our study demonstrated a statistically significant difference in mobility between individuals with psoriasis compared with the general population, which remained significant when controlling for arthritis, obesity, and diabetes (P=.032). This may be the result of several influences. First, the location of the psoriasis may impact mobility. Plantar psoriasis—a manifestation on the soles of the feet—can cause discomfort and pain, which can hinder walking and standing.5 Second, a study by Lasselin et al6 found that systemic inflammation contributes to mobility impairment through alterations in gait and posture, which suggests that the inflammatory processes inherent in psoriasis could intrinsically modify walking speed and stride, potentially exacerbating mobility difficulties independent of other comorbid conditions. These findings suggest that psoriasis may disproportionately affect individuals with impaired mobility, independent of comorbid arthritis, obesity, and diabetes.
These findings have broad implications for diversity, equity, and inclusion. They should prompt us to consider the practical challenges faced by this patient population and the ways that we can address barriers to care. Offering telehealth appointments, making primary care referrals for impaired mobility workups, and advising patients of direct-to-home delivery of prescriptions are good places to start.
Limitations to our study include the lack of specificity in the survey question, self-reporting bias, and the inability to control for the psoriasis location. Further investigations are warranted in large, representative US adult populations to assess the implications of impaired mobility in patients with psoriasis.
- Elmets CA, Leonardi CL, Davis DMR, et al. Joint AAD-NPF guidelines of care for the management and treatment of psoriasis with awareness and attention to comorbidities. J Am Acad Dermatol. 2019;80:1073-1113. doi: 10.1016/j.jaad.2018.11.058
- Zheng Q, Sun XY, Miao X, et al. Association between physical activity and risk of prevalent psoriasis: A MOOSE-compliant meta-analysis. Medicine (Baltimore). 2018;97:e11394. doi: 10.1097 /MD.0000000000011394
- Mullin AE, Coe IR, Gooden EA, et al. Inclusion, diversity, equity, and accessibility: from organizational responsibility to leadership competency. Healthc Manage Forum. 2021;34311-315. doi: 10.1177/08404704211038232
- Centers for Disease Control and Prevention. National Health and Nutrition Examination Survey. NHANES questionnaires, datasets, and related documentation. Accessed October 21, 2023. https://wwwn.cdc.gov/nchs/nhanes/
- Romani M, Biela G, Farr K, et al. Plantar psoriasis: a review of the literature. Clin Podiatr Med Surg. 2021;38:541-552. doi: 10.1016 /j.cpm.2021.06.009
- Lasselin J, Sundelin T, Wayne PM, et al. Biological motion during inflammation in humans. Brain Behav Immun. 2020;84:147-153. doi: 10.1016/j.bbi.2019.11.019
To the Editor:
Psoriasis is a chronic inflammatory condition that affects individuals in various extracutaneous ways.1 Prior studies have documented a decrease in exercise intensity among patients with psoriasis2; however, few studies have specifically investigated baseline mobility in this population. Baseline mobility denotes an individual’s fundamental ability to walk or move around without assistance of any kind. Impaired mobility—when baseline mobility is compromised—is an aspect of the wider diversity, equity, and inclusion framework that underscores the significance of recognizing challenges and promoting inclusive measures, both at the point of care and in research.3 study sought to analyze the relationship between psoriasis and baseline mobility among US adults (aged 45 to 80 years) utilizing the latest data from the National Health and Nutrition Examination Survey (NHANES) database for psoriasis.4 We used three 2-year cycles of NHANES data to create a 2009-2014 dataset.
The overall NHANES response rate among adults aged 45 to 80 years between 2009 and 2014 was 67.9%. Patients were categorized as having impaired mobility if they responded “yes” to the following question: “Because of a health problem, do you have difficulty walking without using any special equipment?” Psoriasis status was assessed by the following question: “Have you ever been told by a doctor or other health professional that you had psoriasis?” Multivariable logistic regression analyses were performed using Stata/SE 18.0 software (StataCorp LLC) to assess the relationship between psoriasis and impaired mobility. Age, income, education, sex, race, tobacco use, diabetes status, body mass index, and arthritis status were controlled for in our models.
Our analysis initially included 9982 participants; 14 did not respond to questions assessing psoriasis and impaired mobility and were excluded. The prevalence of impaired mobility in patients with psoriasis was 17.1% compared with 10.9% among those without psoriasis (Table 1). There was a significant association between psoriasis and impaired mobility among patients aged 45 to 80 years after adjusting for potential confounding variables (adjusted odds ratio [AOR], 1.54; 95% CI, 1.04- 2.29; P=.032)(Table 2). Analyses of subgroups yielded no statistically significant results.



Our study demonstrated a statistically significant difference in mobility between individuals with psoriasis compared with the general population, which remained significant when controlling for arthritis, obesity, and diabetes (P=.032). This may be the result of several influences. First, the location of the psoriasis may impact mobility. Plantar psoriasis—a manifestation on the soles of the feet—can cause discomfort and pain, which can hinder walking and standing.5 Second, a study by Lasselin et al6 found that systemic inflammation contributes to mobility impairment through alterations in gait and posture, which suggests that the inflammatory processes inherent in psoriasis could intrinsically modify walking speed and stride, potentially exacerbating mobility difficulties independent of other comorbid conditions. These findings suggest that psoriasis may disproportionately affect individuals with impaired mobility, independent of comorbid arthritis, obesity, and diabetes.
These findings have broad implications for diversity, equity, and inclusion. They should prompt us to consider the practical challenges faced by this patient population and the ways that we can address barriers to care. Offering telehealth appointments, making primary care referrals for impaired mobility workups, and advising patients of direct-to-home delivery of prescriptions are good places to start.
Limitations to our study include the lack of specificity in the survey question, self-reporting bias, and the inability to control for the psoriasis location. Further investigations are warranted in large, representative US adult populations to assess the implications of impaired mobility in patients with psoriasis.
To the Editor:
Psoriasis is a chronic inflammatory condition that affects individuals in various extracutaneous ways.1 Prior studies have documented a decrease in exercise intensity among patients with psoriasis2; however, few studies have specifically investigated baseline mobility in this population. Baseline mobility denotes an individual’s fundamental ability to walk or move around without assistance of any kind. Impaired mobility—when baseline mobility is compromised—is an aspect of the wider diversity, equity, and inclusion framework that underscores the significance of recognizing challenges and promoting inclusive measures, both at the point of care and in research.3 study sought to analyze the relationship between psoriasis and baseline mobility among US adults (aged 45 to 80 years) utilizing the latest data from the National Health and Nutrition Examination Survey (NHANES) database for psoriasis.4 We used three 2-year cycles of NHANES data to create a 2009-2014 dataset.
The overall NHANES response rate among adults aged 45 to 80 years between 2009 and 2014 was 67.9%. Patients were categorized as having impaired mobility if they responded “yes” to the following question: “Because of a health problem, do you have difficulty walking without using any special equipment?” Psoriasis status was assessed by the following question: “Have you ever been told by a doctor or other health professional that you had psoriasis?” Multivariable logistic regression analyses were performed using Stata/SE 18.0 software (StataCorp LLC) to assess the relationship between psoriasis and impaired mobility. Age, income, education, sex, race, tobacco use, diabetes status, body mass index, and arthritis status were controlled for in our models.
Our analysis initially included 9982 participants; 14 did not respond to questions assessing psoriasis and impaired mobility and were excluded. The prevalence of impaired mobility in patients with psoriasis was 17.1% compared with 10.9% among those without psoriasis (Table 1). There was a significant association between psoriasis and impaired mobility among patients aged 45 to 80 years after adjusting for potential confounding variables (adjusted odds ratio [AOR], 1.54; 95% CI, 1.04- 2.29; P=.032)(Table 2). Analyses of subgroups yielded no statistically significant results.



Our study demonstrated a statistically significant difference in mobility between individuals with psoriasis compared with the general population, which remained significant when controlling for arthritis, obesity, and diabetes (P=.032). This may be the result of several influences. First, the location of the psoriasis may impact mobility. Plantar psoriasis—a manifestation on the soles of the feet—can cause discomfort and pain, which can hinder walking and standing.5 Second, a study by Lasselin et al6 found that systemic inflammation contributes to mobility impairment through alterations in gait and posture, which suggests that the inflammatory processes inherent in psoriasis could intrinsically modify walking speed and stride, potentially exacerbating mobility difficulties independent of other comorbid conditions. These findings suggest that psoriasis may disproportionately affect individuals with impaired mobility, independent of comorbid arthritis, obesity, and diabetes.
These findings have broad implications for diversity, equity, and inclusion. They should prompt us to consider the practical challenges faced by this patient population and the ways that we can address barriers to care. Offering telehealth appointments, making primary care referrals for impaired mobility workups, and advising patients of direct-to-home delivery of prescriptions are good places to start.
Limitations to our study include the lack of specificity in the survey question, self-reporting bias, and the inability to control for the psoriasis location. Further investigations are warranted in large, representative US adult populations to assess the implications of impaired mobility in patients with psoriasis.
- Elmets CA, Leonardi CL, Davis DMR, et al. Joint AAD-NPF guidelines of care for the management and treatment of psoriasis with awareness and attention to comorbidities. J Am Acad Dermatol. 2019;80:1073-1113. doi: 10.1016/j.jaad.2018.11.058
- Zheng Q, Sun XY, Miao X, et al. Association between physical activity and risk of prevalent psoriasis: A MOOSE-compliant meta-analysis. Medicine (Baltimore). 2018;97:e11394. doi: 10.1097 /MD.0000000000011394
- Mullin AE, Coe IR, Gooden EA, et al. Inclusion, diversity, equity, and accessibility: from organizational responsibility to leadership competency. Healthc Manage Forum. 2021;34311-315. doi: 10.1177/08404704211038232
- Centers for Disease Control and Prevention. National Health and Nutrition Examination Survey. NHANES questionnaires, datasets, and related documentation. Accessed October 21, 2023. https://wwwn.cdc.gov/nchs/nhanes/
- Romani M, Biela G, Farr K, et al. Plantar psoriasis: a review of the literature. Clin Podiatr Med Surg. 2021;38:541-552. doi: 10.1016 /j.cpm.2021.06.009
- Lasselin J, Sundelin T, Wayne PM, et al. Biological motion during inflammation in humans. Brain Behav Immun. 2020;84:147-153. doi: 10.1016/j.bbi.2019.11.019
- Elmets CA, Leonardi CL, Davis DMR, et al. Joint AAD-NPF guidelines of care for the management and treatment of psoriasis with awareness and attention to comorbidities. J Am Acad Dermatol. 2019;80:1073-1113. doi: 10.1016/j.jaad.2018.11.058
- Zheng Q, Sun XY, Miao X, et al. Association between physical activity and risk of prevalent psoriasis: A MOOSE-compliant meta-analysis. Medicine (Baltimore). 2018;97:e11394. doi: 10.1097 /MD.0000000000011394
- Mullin AE, Coe IR, Gooden EA, et al. Inclusion, diversity, equity, and accessibility: from organizational responsibility to leadership competency. Healthc Manage Forum. 2021;34311-315. doi: 10.1177/08404704211038232
- Centers for Disease Control and Prevention. National Health and Nutrition Examination Survey. NHANES questionnaires, datasets, and related documentation. Accessed October 21, 2023. https://wwwn.cdc.gov/nchs/nhanes/
- Romani M, Biela G, Farr K, et al. Plantar psoriasis: a review of the literature. Clin Podiatr Med Surg. 2021;38:541-552. doi: 10.1016 /j.cpm.2021.06.009
- Lasselin J, Sundelin T, Wayne PM, et al. Biological motion during inflammation in humans. Brain Behav Immun. 2020;84:147-153. doi: 10.1016/j.bbi.2019.11.019
Exploring the Relationship Between Psoriasis and Mobility Among US Adults
Exploring the Relationship Between Psoriasis and Mobility Among US Adults
PRACTICE POINTS
- Mobility issues are more common in patients who have psoriasis than in those who do not.
- It is important to assess patients with psoriasis for mobility issues regardless of age or comorbid conditions such as arthritis, obesity, and diabetes.
- Dermatologists can help patients with psoriasis and impaired mobility overcome potential barriers to care by incorporating telehealth services into their practices and informing patients of direct-to-home delivery of prescriptions.
Dermatologists’ Perspectives Toward Disability Assessment: A Nationwide Survey Report
Dermatologists’ Perspectives Toward Disability Assessment: A Nationwide Survey Report
To the Editor:
Cutaneous medical conditions can have a substantial impact on patients’ functioning and quality of life. Many patients with severe skin disease are eligible to receive disability assistance that can provide them with essential income and health care. Previous research has highlighted disability assessment as one of the most important ways physicians can help mitigate the health consequences of poverty.1 Dermatologists can play an important role in the disability assessment process by documenting the facts associated with patients’ skin conditions.
Although skin conditions have a relatively high prevalence, they remain underrepresented in disability claims. Between 1997 and 2004, occupational skin diseases accounted for 12% to 17% of nonfatal work-related illnesses; however, during that same period, skin conditions comprised only 0.21% of disability claims in the United States.2,3 Historically, there has been hesitancy among dermatologists to complete disability paperwork; a 1976 survey of dermatologists cited extensive paperwork, “troublesome patients,” and fee schedule issues as reasons.4 The lack of training regarding disability assessment in medical school and residency also has been noted.5
To characterize modern attitudes toward disability assessments, we conducted a survey of dermatologists across the United States. Our study was reviewed and declared exempt by the institutional review board of the Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center (Torrance, California)(approval #18CR-32242-01). Using convenience sampling, we emailed dermatologists from the Association of Professors of Dermatology and dermatology state societies in all 50 states inviting them to participate in our voluntary and anonymous survey, which was administered using SurveyMonkey. The use of all society mailing lists was approved by the respective owners. The 15-question survey included multiple choice, Likert scale, and free response sections. Summary and descriptive statistics were used to describe respondent demographics and identify any patterns in responses.
For each Likert-based question, participants ranked their degree of agreement with a statement as: 1=strongly disagree, 2=somewhat disagree, 3=neither agree nor disagree/neutral, 4=somewhat agree, and 5=strongly agree. The mean response and standard deviation were reported for each Likert scale prompt. Preplanned 1-sample t testing was used to analyze Likert scale data, in which the mean response for each prompt was compared to a baseline response of 3 (neutral). A P value <.05 was considered statistically significant. Statistical analyses were performed using SPSS Statistics for MacOS, version 27 (IBM).
Seventy-eight dermatologists agreed to participate, and 70 completed the survey, for a response rate of 89.7% (Table 1). The dermatologists we surveyed practiced in a variety of clinical settings, including academic public hospitals (46.2% [36/78]), academic private hospitals (33.3% [26/78]), and private practices (32.1% [25/78]), and 60.3% (47/78) reported providing disability documentation at some point. Most of the respondents (64.3% [45/70]) did not perform assessments in an average month (Table 2). Medical assessment documentation was provided most frequently for workers’ compensation (50.0% [35/70]), private insurance (27.1% [19/70]), and Social Security Disability Insurance (25.7% [18/70]). Dermatologists overwhelmingly reported no formal training for disability assessment in medical school (94.3% [66/70]), residency (97.1% [68/70]), or clinical practice (81.4% [57/70]).


In the Likert scale prompts, respondents agreed that they were uncertain of their role in disability assessment (mean response, 3.6; P<.001). Moreover, they were uncomfortable providing assessments (mean response, 3.5; P<.001) and felt that they did not have sufficient time to perform them (mean response, 3.6; P<.001). Dermatologists disagreed that they received adequate compensation for performing assessments (mean response, 2.2; P<.001) and felt that they did not have enough time to participate in assessments (mean response, 3.6; P<.001). Respondents generally did not feel distrustful of patients seeking disability assessment (mean response, 2.8; P=.043). Dermatologists neither agreed nor disagreed when asked if they thought that physicians can determine disability status (mean response, 3.2; P=.118). The details of the Likert scale responses are described in Table 3. Respondents also were uncertain as to which dermatologic conditions were eligible for disability. When asked to select which conditions from a list of 10 were eligible per the Social Security Administration listing of disability impairments, only 15.4% (12/70) of respondents correctly identified that all the conditions qualified; these included ichthyosis, pemphigus vulgaris, allergic contact dermatitis, hidradenitis suppurativa, systemic lupus erythematosus, chromoblastomycosis, xeroderma pigmentosum, burns, malignant melanoma, and scleroderma.6

In the free-response prompts, respondents frequently described extensive paperwork, inadequate time, and lack of reimbursement as barriers to providing documentation. Often, dermatologists found that the forms were not well matched to the skin conditions they were evaluating and rather had a musculoskeletal focus. Multiple individuals commented on the challenge in assessing the percentage of disability and functional/psychosocial impairment in skin conditions. One respondent noted that workers’ compensation forms ask if the patient is “…permanent and stationary…for most conditions this has no meaning in dermatology.” Some felt hesitant to provide documentation because they had insufficient patient history, especially regarding employment, and opted to defer to primary care providers who might be more familiar with the full patient history.
A dermatologist described their perspective as follows:
“…As a specialist I feel that I don’t have a complete look into all the factors that could contribute to a patient[’]s need to go on disability, and I don’t have experience with filling out disability requests. That being said, if a patient[’]s request for disability was due to a skin disease that I know way more about than [a] primary care [physician] would, I would do the disability assessment.”
Another respondent noted the complexity in “establishing causality” for workers’ compensation. Another dermatologist reported,
“The most frequent challenging situation I encounter is being asked to evaluate for maximum medical improvement after patch testing. If the patient is not fully avoiding contact allergens either at home or at work, then I typically document that they are not at [maximum medical improvement]. The reality is that most frequently it is due to exposure to allergens at home so the line between what is a legitimate worker’s comp[ensation] issue and what is a home life choice is blurry.”
Nevertheless, respondents expressed interest in learning more about disability assessment procedures. Summary guides, lectures, and prefilled paperwork were the most popular initiatives that respondents agreed would be beneficial toward becoming educated regarding disability assessment (78.6%, 58.6%, and 58.6%, respectively)(Table 2). One respondent noted that “previous [internal medicine] history help[ed]” them in performing cutaneous disability assessments.
As with any survey, our study did have some inherent limitations. Only a relatively small sample size was willing to complete the survey. There was a predominance of respondents from California (34.6% [27/78]), as well as those practicing for less than 15 years (58.9% [46/78])(Figure). This could limit generalizability to the national population of dermatologists. In addition, there was potential for recall bias and errors in responding given the self-reported nature of the study. Different individuals may interpret the Likert scale options in various ways, which could skew results unintentionally. However, the survey was largely qualitative in nature, making it a legitimate tool for answering our research questions. Moreover, we were able to hear the perspectives of dermatologists across diverse practice settings, with free response prompts to increase the depth of the survey.

Almost 50 years later, our survey echoes common themes from Adams’ 1976 survey.4 Inadequate compensation, limited time, and burdensome paperwork all continue to hinder dermatologists’ ability to perform disability assessments. Our participants frequently commented that the current disability forms are not congruent with the nature of skin conditions, making it challenging to accurately document the facts.
Moreover, respondents felt uncertain in their role in disability assessment and occasionally noted distrust of patients or insufficient patient history as barriers to completing assessments. They also were unsure if physicians can grant disability status. This is a common misconception among physicians that leads to discomfort in helping with disability assessment.7 The role of physicians in disability assessment is to document the facts of a patient’s illness, not to determine whether they are eligible for benefits. We discovered uncertainty in our respondents’ ability to identify conditions eligible for disability, highlighting an area in need of greater education for physicians.
Despite these obstacles, respondents were interested in learning more about disability assessment and highlighted several practical approaches that could help them better perform this task. As skin specialists, dermatologists are the best-equipped physicians to assess cutaneous conditions and should play a greater role in performing disability assessments, which could be achieved through increased educational initiatives and individual physician motivation.7 We call for greater collaboration and reflection on the importance of disability assistance among dermatologists to increase participation in the disability-assessment process.
- O’Connell JJ, Zevin BD, Quick PD, et al. Documenting disability: simple strategies for medical providers. Health Care for the Homeless Clinicians’ Network. September 2007. Accessed March 31, 2025. https://nhchc.org/wp-content/uploads/2019/08/DocumentingDisability2007.pdf
- US Bureau of Labor Statistics. Injuries, illnesses, and fatalities. Accessed March 31, 2025. https://www.bls.gov/iif/
- Meseguer J. Outcome variation in the Social Security Disability Insurance Program: the role of primary diagnoses. Soc Secur Bull. 2013;73:39-75.
- Adams RM. Attitudes of California dermatologists toward Worker’s Compensation: results of a survey. West J Med. 1976;125:169-175.
- Talmage J, Melhorn J, Hyman M. AMA Guides to the Evaluation of Work Ability and Return to Work. 2nd ed. American Medical Association; 2011.
- Social Security Administration. Disability evaluation under Social Security. 8.00 skin disorders - adult. March 31, 2025. https://www.ssa.gov/disability/professionals/bluebook/8.00-Skin-Adult.htm
- Dawson J, Smogorzewski J. Demystifying disability assessments for dermatologists—a call to action. JAMA Dermatol. 2021;157:903-904. doi:10.1001/jamadermatol.2021.1767
To the Editor:
Cutaneous medical conditions can have a substantial impact on patients’ functioning and quality of life. Many patients with severe skin disease are eligible to receive disability assistance that can provide them with essential income and health care. Previous research has highlighted disability assessment as one of the most important ways physicians can help mitigate the health consequences of poverty.1 Dermatologists can play an important role in the disability assessment process by documenting the facts associated with patients’ skin conditions.
Although skin conditions have a relatively high prevalence, they remain underrepresented in disability claims. Between 1997 and 2004, occupational skin diseases accounted for 12% to 17% of nonfatal work-related illnesses; however, during that same period, skin conditions comprised only 0.21% of disability claims in the United States.2,3 Historically, there has been hesitancy among dermatologists to complete disability paperwork; a 1976 survey of dermatologists cited extensive paperwork, “troublesome patients,” and fee schedule issues as reasons.4 The lack of training regarding disability assessment in medical school and residency also has been noted.5
To characterize modern attitudes toward disability assessments, we conducted a survey of dermatologists across the United States. Our study was reviewed and declared exempt by the institutional review board of the Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center (Torrance, California)(approval #18CR-32242-01). Using convenience sampling, we emailed dermatologists from the Association of Professors of Dermatology and dermatology state societies in all 50 states inviting them to participate in our voluntary and anonymous survey, which was administered using SurveyMonkey. The use of all society mailing lists was approved by the respective owners. The 15-question survey included multiple choice, Likert scale, and free response sections. Summary and descriptive statistics were used to describe respondent demographics and identify any patterns in responses.
For each Likert-based question, participants ranked their degree of agreement with a statement as: 1=strongly disagree, 2=somewhat disagree, 3=neither agree nor disagree/neutral, 4=somewhat agree, and 5=strongly agree. The mean response and standard deviation were reported for each Likert scale prompt. Preplanned 1-sample t testing was used to analyze Likert scale data, in which the mean response for each prompt was compared to a baseline response of 3 (neutral). A P value <.05 was considered statistically significant. Statistical analyses were performed using SPSS Statistics for MacOS, version 27 (IBM).
Seventy-eight dermatologists agreed to participate, and 70 completed the survey, for a response rate of 89.7% (Table 1). The dermatologists we surveyed practiced in a variety of clinical settings, including academic public hospitals (46.2% [36/78]), academic private hospitals (33.3% [26/78]), and private practices (32.1% [25/78]), and 60.3% (47/78) reported providing disability documentation at some point. Most of the respondents (64.3% [45/70]) did not perform assessments in an average month (Table 2). Medical assessment documentation was provided most frequently for workers’ compensation (50.0% [35/70]), private insurance (27.1% [19/70]), and Social Security Disability Insurance (25.7% [18/70]). Dermatologists overwhelmingly reported no formal training for disability assessment in medical school (94.3% [66/70]), residency (97.1% [68/70]), or clinical practice (81.4% [57/70]).


In the Likert scale prompts, respondents agreed that they were uncertain of their role in disability assessment (mean response, 3.6; P<.001). Moreover, they were uncomfortable providing assessments (mean response, 3.5; P<.001) and felt that they did not have sufficient time to perform them (mean response, 3.6; P<.001). Dermatologists disagreed that they received adequate compensation for performing assessments (mean response, 2.2; P<.001) and felt that they did not have enough time to participate in assessments (mean response, 3.6; P<.001). Respondents generally did not feel distrustful of patients seeking disability assessment (mean response, 2.8; P=.043). Dermatologists neither agreed nor disagreed when asked if they thought that physicians can determine disability status (mean response, 3.2; P=.118). The details of the Likert scale responses are described in Table 3. Respondents also were uncertain as to which dermatologic conditions were eligible for disability. When asked to select which conditions from a list of 10 were eligible per the Social Security Administration listing of disability impairments, only 15.4% (12/70) of respondents correctly identified that all the conditions qualified; these included ichthyosis, pemphigus vulgaris, allergic contact dermatitis, hidradenitis suppurativa, systemic lupus erythematosus, chromoblastomycosis, xeroderma pigmentosum, burns, malignant melanoma, and scleroderma.6

In the free-response prompts, respondents frequently described extensive paperwork, inadequate time, and lack of reimbursement as barriers to providing documentation. Often, dermatologists found that the forms were not well matched to the skin conditions they were evaluating and rather had a musculoskeletal focus. Multiple individuals commented on the challenge in assessing the percentage of disability and functional/psychosocial impairment in skin conditions. One respondent noted that workers’ compensation forms ask if the patient is “…permanent and stationary…for most conditions this has no meaning in dermatology.” Some felt hesitant to provide documentation because they had insufficient patient history, especially regarding employment, and opted to defer to primary care providers who might be more familiar with the full patient history.
A dermatologist described their perspective as follows:
“…As a specialist I feel that I don’t have a complete look into all the factors that could contribute to a patient[’]s need to go on disability, and I don’t have experience with filling out disability requests. That being said, if a patient[’]s request for disability was due to a skin disease that I know way more about than [a] primary care [physician] would, I would do the disability assessment.”
Another respondent noted the complexity in “establishing causality” for workers’ compensation. Another dermatologist reported,
“The most frequent challenging situation I encounter is being asked to evaluate for maximum medical improvement after patch testing. If the patient is not fully avoiding contact allergens either at home or at work, then I typically document that they are not at [maximum medical improvement]. The reality is that most frequently it is due to exposure to allergens at home so the line between what is a legitimate worker’s comp[ensation] issue and what is a home life choice is blurry.”
Nevertheless, respondents expressed interest in learning more about disability assessment procedures. Summary guides, lectures, and prefilled paperwork were the most popular initiatives that respondents agreed would be beneficial toward becoming educated regarding disability assessment (78.6%, 58.6%, and 58.6%, respectively)(Table 2). One respondent noted that “previous [internal medicine] history help[ed]” them in performing cutaneous disability assessments.
As with any survey, our study did have some inherent limitations. Only a relatively small sample size was willing to complete the survey. There was a predominance of respondents from California (34.6% [27/78]), as well as those practicing for less than 15 years (58.9% [46/78])(Figure). This could limit generalizability to the national population of dermatologists. In addition, there was potential for recall bias and errors in responding given the self-reported nature of the study. Different individuals may interpret the Likert scale options in various ways, which could skew results unintentionally. However, the survey was largely qualitative in nature, making it a legitimate tool for answering our research questions. Moreover, we were able to hear the perspectives of dermatologists across diverse practice settings, with free response prompts to increase the depth of the survey.

Almost 50 years later, our survey echoes common themes from Adams’ 1976 survey.4 Inadequate compensation, limited time, and burdensome paperwork all continue to hinder dermatologists’ ability to perform disability assessments. Our participants frequently commented that the current disability forms are not congruent with the nature of skin conditions, making it challenging to accurately document the facts.
Moreover, respondents felt uncertain in their role in disability assessment and occasionally noted distrust of patients or insufficient patient history as barriers to completing assessments. They also were unsure if physicians can grant disability status. This is a common misconception among physicians that leads to discomfort in helping with disability assessment.7 The role of physicians in disability assessment is to document the facts of a patient’s illness, not to determine whether they are eligible for benefits. We discovered uncertainty in our respondents’ ability to identify conditions eligible for disability, highlighting an area in need of greater education for physicians.
Despite these obstacles, respondents were interested in learning more about disability assessment and highlighted several practical approaches that could help them better perform this task. As skin specialists, dermatologists are the best-equipped physicians to assess cutaneous conditions and should play a greater role in performing disability assessments, which could be achieved through increased educational initiatives and individual physician motivation.7 We call for greater collaboration and reflection on the importance of disability assistance among dermatologists to increase participation in the disability-assessment process.
To the Editor:
Cutaneous medical conditions can have a substantial impact on patients’ functioning and quality of life. Many patients with severe skin disease are eligible to receive disability assistance that can provide them with essential income and health care. Previous research has highlighted disability assessment as one of the most important ways physicians can help mitigate the health consequences of poverty.1 Dermatologists can play an important role in the disability assessment process by documenting the facts associated with patients’ skin conditions.
Although skin conditions have a relatively high prevalence, they remain underrepresented in disability claims. Between 1997 and 2004, occupational skin diseases accounted for 12% to 17% of nonfatal work-related illnesses; however, during that same period, skin conditions comprised only 0.21% of disability claims in the United States.2,3 Historically, there has been hesitancy among dermatologists to complete disability paperwork; a 1976 survey of dermatologists cited extensive paperwork, “troublesome patients,” and fee schedule issues as reasons.4 The lack of training regarding disability assessment in medical school and residency also has been noted.5
To characterize modern attitudes toward disability assessments, we conducted a survey of dermatologists across the United States. Our study was reviewed and declared exempt by the institutional review board of the Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center (Torrance, California)(approval #18CR-32242-01). Using convenience sampling, we emailed dermatologists from the Association of Professors of Dermatology and dermatology state societies in all 50 states inviting them to participate in our voluntary and anonymous survey, which was administered using SurveyMonkey. The use of all society mailing lists was approved by the respective owners. The 15-question survey included multiple choice, Likert scale, and free response sections. Summary and descriptive statistics were used to describe respondent demographics and identify any patterns in responses.
For each Likert-based question, participants ranked their degree of agreement with a statement as: 1=strongly disagree, 2=somewhat disagree, 3=neither agree nor disagree/neutral, 4=somewhat agree, and 5=strongly agree. The mean response and standard deviation were reported for each Likert scale prompt. Preplanned 1-sample t testing was used to analyze Likert scale data, in which the mean response for each prompt was compared to a baseline response of 3 (neutral). A P value <.05 was considered statistically significant. Statistical analyses were performed using SPSS Statistics for MacOS, version 27 (IBM).
Seventy-eight dermatologists agreed to participate, and 70 completed the survey, for a response rate of 89.7% (Table 1). The dermatologists we surveyed practiced in a variety of clinical settings, including academic public hospitals (46.2% [36/78]), academic private hospitals (33.3% [26/78]), and private practices (32.1% [25/78]), and 60.3% (47/78) reported providing disability documentation at some point. Most of the respondents (64.3% [45/70]) did not perform assessments in an average month (Table 2). Medical assessment documentation was provided most frequently for workers’ compensation (50.0% [35/70]), private insurance (27.1% [19/70]), and Social Security Disability Insurance (25.7% [18/70]). Dermatologists overwhelmingly reported no formal training for disability assessment in medical school (94.3% [66/70]), residency (97.1% [68/70]), or clinical practice (81.4% [57/70]).


In the Likert scale prompts, respondents agreed that they were uncertain of their role in disability assessment (mean response, 3.6; P<.001). Moreover, they were uncomfortable providing assessments (mean response, 3.5; P<.001) and felt that they did not have sufficient time to perform them (mean response, 3.6; P<.001). Dermatologists disagreed that they received adequate compensation for performing assessments (mean response, 2.2; P<.001) and felt that they did not have enough time to participate in assessments (mean response, 3.6; P<.001). Respondents generally did not feel distrustful of patients seeking disability assessment (mean response, 2.8; P=.043). Dermatologists neither agreed nor disagreed when asked if they thought that physicians can determine disability status (mean response, 3.2; P=.118). The details of the Likert scale responses are described in Table 3. Respondents also were uncertain as to which dermatologic conditions were eligible for disability. When asked to select which conditions from a list of 10 were eligible per the Social Security Administration listing of disability impairments, only 15.4% (12/70) of respondents correctly identified that all the conditions qualified; these included ichthyosis, pemphigus vulgaris, allergic contact dermatitis, hidradenitis suppurativa, systemic lupus erythematosus, chromoblastomycosis, xeroderma pigmentosum, burns, malignant melanoma, and scleroderma.6

In the free-response prompts, respondents frequently described extensive paperwork, inadequate time, and lack of reimbursement as barriers to providing documentation. Often, dermatologists found that the forms were not well matched to the skin conditions they were evaluating and rather had a musculoskeletal focus. Multiple individuals commented on the challenge in assessing the percentage of disability and functional/psychosocial impairment in skin conditions. One respondent noted that workers’ compensation forms ask if the patient is “…permanent and stationary…for most conditions this has no meaning in dermatology.” Some felt hesitant to provide documentation because they had insufficient patient history, especially regarding employment, and opted to defer to primary care providers who might be more familiar with the full patient history.
A dermatologist described their perspective as follows:
“…As a specialist I feel that I don’t have a complete look into all the factors that could contribute to a patient[’]s need to go on disability, and I don’t have experience with filling out disability requests. That being said, if a patient[’]s request for disability was due to a skin disease that I know way more about than [a] primary care [physician] would, I would do the disability assessment.”
Another respondent noted the complexity in “establishing causality” for workers’ compensation. Another dermatologist reported,
“The most frequent challenging situation I encounter is being asked to evaluate for maximum medical improvement after patch testing. If the patient is not fully avoiding contact allergens either at home or at work, then I typically document that they are not at [maximum medical improvement]. The reality is that most frequently it is due to exposure to allergens at home so the line between what is a legitimate worker’s comp[ensation] issue and what is a home life choice is blurry.”
Nevertheless, respondents expressed interest in learning more about disability assessment procedures. Summary guides, lectures, and prefilled paperwork were the most popular initiatives that respondents agreed would be beneficial toward becoming educated regarding disability assessment (78.6%, 58.6%, and 58.6%, respectively)(Table 2). One respondent noted that “previous [internal medicine] history help[ed]” them in performing cutaneous disability assessments.
As with any survey, our study did have some inherent limitations. Only a relatively small sample size was willing to complete the survey. There was a predominance of respondents from California (34.6% [27/78]), as well as those practicing for less than 15 years (58.9% [46/78])(Figure). This could limit generalizability to the national population of dermatologists. In addition, there was potential for recall bias and errors in responding given the self-reported nature of the study. Different individuals may interpret the Likert scale options in various ways, which could skew results unintentionally. However, the survey was largely qualitative in nature, making it a legitimate tool for answering our research questions. Moreover, we were able to hear the perspectives of dermatologists across diverse practice settings, with free response prompts to increase the depth of the survey.

Almost 50 years later, our survey echoes common themes from Adams’ 1976 survey.4 Inadequate compensation, limited time, and burdensome paperwork all continue to hinder dermatologists’ ability to perform disability assessments. Our participants frequently commented that the current disability forms are not congruent with the nature of skin conditions, making it challenging to accurately document the facts.
Moreover, respondents felt uncertain in their role in disability assessment and occasionally noted distrust of patients or insufficient patient history as barriers to completing assessments. They also were unsure if physicians can grant disability status. This is a common misconception among physicians that leads to discomfort in helping with disability assessment.7 The role of physicians in disability assessment is to document the facts of a patient’s illness, not to determine whether they are eligible for benefits. We discovered uncertainty in our respondents’ ability to identify conditions eligible for disability, highlighting an area in need of greater education for physicians.
Despite these obstacles, respondents were interested in learning more about disability assessment and highlighted several practical approaches that could help them better perform this task. As skin specialists, dermatologists are the best-equipped physicians to assess cutaneous conditions and should play a greater role in performing disability assessments, which could be achieved through increased educational initiatives and individual physician motivation.7 We call for greater collaboration and reflection on the importance of disability assistance among dermatologists to increase participation in the disability-assessment process.
- O’Connell JJ, Zevin BD, Quick PD, et al. Documenting disability: simple strategies for medical providers. Health Care for the Homeless Clinicians’ Network. September 2007. Accessed March 31, 2025. https://nhchc.org/wp-content/uploads/2019/08/DocumentingDisability2007.pdf
- US Bureau of Labor Statistics. Injuries, illnesses, and fatalities. Accessed March 31, 2025. https://www.bls.gov/iif/
- Meseguer J. Outcome variation in the Social Security Disability Insurance Program: the role of primary diagnoses. Soc Secur Bull. 2013;73:39-75.
- Adams RM. Attitudes of California dermatologists toward Worker’s Compensation: results of a survey. West J Med. 1976;125:169-175.
- Talmage J, Melhorn J, Hyman M. AMA Guides to the Evaluation of Work Ability and Return to Work. 2nd ed. American Medical Association; 2011.
- Social Security Administration. Disability evaluation under Social Security. 8.00 skin disorders - adult. March 31, 2025. https://www.ssa.gov/disability/professionals/bluebook/8.00-Skin-Adult.htm
- Dawson J, Smogorzewski J. Demystifying disability assessments for dermatologists—a call to action. JAMA Dermatol. 2021;157:903-904. doi:10.1001/jamadermatol.2021.1767
- O’Connell JJ, Zevin BD, Quick PD, et al. Documenting disability: simple strategies for medical providers. Health Care for the Homeless Clinicians’ Network. September 2007. Accessed March 31, 2025. https://nhchc.org/wp-content/uploads/2019/08/DocumentingDisability2007.pdf
- US Bureau of Labor Statistics. Injuries, illnesses, and fatalities. Accessed March 31, 2025. https://www.bls.gov/iif/
- Meseguer J. Outcome variation in the Social Security Disability Insurance Program: the role of primary diagnoses. Soc Secur Bull. 2013;73:39-75.
- Adams RM. Attitudes of California dermatologists toward Worker’s Compensation: results of a survey. West J Med. 1976;125:169-175.
- Talmage J, Melhorn J, Hyman M. AMA Guides to the Evaluation of Work Ability and Return to Work. 2nd ed. American Medical Association; 2011.
- Social Security Administration. Disability evaluation under Social Security. 8.00 skin disorders - adult. March 31, 2025. https://www.ssa.gov/disability/professionals/bluebook/8.00-Skin-Adult.htm
- Dawson J, Smogorzewski J. Demystifying disability assessments for dermatologists—a call to action. JAMA Dermatol. 2021;157:903-904. doi:10.1001/jamadermatol.2021.1767
Dermatologists’ Perspectives Toward Disability Assessment: A Nationwide Survey Report
Dermatologists’ Perspectives Toward Disability Assessment: A Nationwide Survey Report
PRACTICE POINTS
- As experts in skin conditions, dermatologists are most qualified to assist with disability assessment for dermatologic concerns.
- There are several barriers to dermatologists participating in the disability assessment process, including lack of time, compensation, and education on the subject.
- Many dermatologists may be interested in learning more about disability assessment, and education could be provided in the form of summary guides, lectures, and prefilled paperwork.
Analysis of Errors in the Management of Cutaneous Disorders
Analysis of Errors in the Management of Cutaneous Disorders
Humans are inherently prone to errors. The extent and consequences of medical errors were documented in the 2000 publication of To Err is Human: Building a Safer Health System.1 Published research on medical errors in dermatology has emphasized the heuristic issues involved in diagnosis,2-6 essentially approaching the “why?” and “how?” of such errors. By contrast, the current study aimed to elucidate the “what?”—what are the dermatologic conditions most prone to diagnostic and/or management errors? One study published in 1987 approached this question by analyzing patterns of errors for dermatologic conditions in patients referred for specialty care by primary care physicians.7 The current study aimed to update and expand on the findings of this 1987 report by comparing more recent data on the errors made by providers and patients regarding skin conditions.
Methods
Data were collected prospectively from March 18, 2021, through July 25, 2023. Prospective data were obtained by recording the nature of errors noted for all patients seen by a board-certified dermatologist (R.J.P.) during routine outpatient practice in Norfolk, Virginia. This practice is limited to medical dermatology and accepts patients of any age from any referral source, with or without medical insurance. Retrospective data were obtained by review of electronic medical records for all patients seen by the same board-certified dermatologist from June 5, 2020, through March 12, 2021, who previously had been seen by an outside provider or were self-referred. In this study, the term diagnosis is used to describe providers’ explicit or imputed conclusions as to the nature of a dermatosis, and the term interpretation is used to describe patients' conclusions about their own condition. For this study, the patients’ self-made interpretations of their dermatoses were deemed to be correct when they agreed with those made by the dermatologist using standard clinicopathologic criteria supplemented by rapid bedside diagnostic techniques, as detailed in the 1987 study.7
Cases in which diagnostic or therapeutic errors were noted were entered into a spreadsheet that excluded patients’ names or other identifiers. For each noted case of diagnostic or therapeutic error, the following data were entered: patient’s age and sex; the name of the incorrect diagnosis, interpretation, or treatment; and the name of the correct (missed) diagnosis, along with the source of the error (provider or patient). Provider diagnoses were determined from medical records or patient statements or were imputed from the generally accepted indications for prescribed treatments. A provider was deemed to be any practitioner with prescriptive authority. Patients’ interpretations of their conditions were determined by patient statements or were imputed based on the indications for treatments being used. A treatment error was recorded when a diagnosis or interpretation was deemed to be correct, but treatment was deemed to be inappropriate. The same dermatologist (R.J.P) made all determinations as to the nature of the errors and their source.
Diagnostic errors were determined in several situations: (1) if the interpretation made by the patient of their dermatosis differed from the correct diagnosis in the absence of any additional diagnostic documentation, the correct diagnosis was scored as a missed diagnosis and the incorrect interpretation was scored as such; (2) if the provider’s diagnosis in the patient’s medical record differed from the correct diagnosis, both the correct (missed) and incorrect diagnoses were recorded; and (3) if the indication(s) of the medication(s) prescribed by the provider or used by the patient for their condition differed from the correct diagnosis, an imputed diagnosis based on this indication was scored as the incorrect diagnosis and the correct (missed) diagnosis was recorded; for example, an error would be entered into the spreadsheet for a patient using terbinafine cream for what was actually psoriasis. For a medication with multiple active agents, an error would be entered into the spreadsheet only if none of its indications matched the correct diagnosis; for example, if the patient had been prescribed a betamethasone/clotrimazole product, no error would be scored if the correct diagnosis was a steroid-responsive dermatosis, dermatophytosis, candidiasis, or tinea versicolor. For a single medication with multiple indications, no error would be recorded if the correct diagnosis was any of these indications; for example, in a patient who had been prescribed topical ketoconazole, no error would be scored if the correct diagnosis was dermatophytosis, candidiasis, tinea versicolor, or seborrheic dermatitis. Additionally, no error would be recorded if the correct diagnosis was uncertain at the time of initial patient evaluation or during chart review.
Standard spreadsheet functions and the pandas package8 from the Python programming language9 were used to extract relevant data from the spreadsheet (Tables 1-4).




Results
A total of 446 patient visits (182 males, 264 females) were included in the study, in which a total of 486 errors were found in the combined prospective and retrospective portions of the study. These errors involved 1.4% of all patient visits for the study period—specifically, all in routine practice as well as all patient records retrospectively reviewed. The age of the patients ranged from 4 to 95 years; the mean age was 51.5 years for males and 50.8 years for females.
The study results are outlined in Tables 1 through 4. To minimize the amount of data provided with no appreciable effect on the results, cases in which an incorrect or missed diagnosis/interpretation occurred only once (ie, unique case errors) were excluded from the tables. Tables 1 and 2 indicate the numbers and types of incorrect and missed diagnoses.
In the combined patient and provider cases, there were 434 instances in which provider diagnoses and patient interpretations were incorrect, 320 (73.7%) of which involved infectious disorders. By contrast, of the 413 instances of provider and patient missed diagnoses 289 (70.0%) were inflammatory dermatoses. The pattern was similar for patients’ incorrect interpretations compared to the incorrect diagnoses of the medical providers. Patients incorrectly interpreted their dermatoses as infectious in 79.5% (101/127) of cases. Similarly, providers incorrectly diagnosed their patients’ dermatoses as infectious in 75.4% (211/280) of cases (Table 3). For patients’ missed diagnoses, 70.7% (82/116) involved inflammatory dermatoses. For providers’ missed diagnoses, 63.9% (179/280) involved inflammatory dermatoses (Table 4).
Treatment errors in the context of correct diagnoses were uncommon. Fifteen (3.4%) such cases were noted in the 446 error-containing patient visits. In 4 (26.7%) of the 15 cases, potent topical corticosteroids were used long term on inappropriate cutaneous sites (eg, genital, facial, or intertriginous areas). Another 4 (26.7%) cases involved fungal infections: nystatin used for tinea versicolor in 1 case and for dermatophytosis in another, widespread dermatophytosis treated topically, and use of a nonindicated topical antifungal for onychomycosis. Other examples involved inadequate dosing of systemic corticosteroids for extensive acute contact dermatitis, psoriasis treated with systemic corticosteroids, inadequate dosing of medication for seborrheic dermatitis, and treatment with valacyclovir based solely on serologic testing.
Comment
The results of our study indicate that errors in management of cutaneous disorders are overwhelmingly diagnostic in nature, while treatment errors appear to be unusual when the correct diagnosis is made. Both the current study and the 1987 study indicated a notable tendency of providers to incorrectly diagnose infectious disorders and to miss the diagnosis of inflammatory dermatoses.7 The current study extends this finding to include patients’ interpretive errors.
It is notable that many of the incorrect and missed diagnoses can be confirmed or ruled out by rapid bedside techniques, namely potassium hydroxide (KOH) preparation for dermatophytes, candidiasis, and tinea versicolor; wet preparation for scabies and pediculosis; Tzanck preparation for herpes simplex and herpes zoster; and crush preparation for molluscum contagiosum. Notably, 57.8% (281/486) of cases in which error was noted involved disorders for which the use of one of these bedside diagnostic tests could have correctly established a diagnosis or ruled out an incorrect one; thus in an ideal world in which these tests were performed perfectly in all appropriate cases, more than half of the errors detected in this study could have been avoided. Dermatophytosis was involved in 35.8% (174/486) of the error-containing patient encounters in this study; therefore, if only the KOH preparation is considered, more than one-third of all errors documented in this study could have been avoided. Unfortunately, surveys have suggested that among dermatologists in the United States and some other countries, KOH preparations are used infrequently.10-12
Certain limitations were inherent to this study. The data were derived from a single dermatology practice by one physician in one geographic region over a short period of time. These factors may limit the generalizability of the results. Although the goal was to identify all errors made for the patients seen, some errors likely were missed due to incomplete patient history or inaccurate medication listings. There is no absolute way to determine if the diagnoses or the treatments deemed correct by the dermatologist were, in fact, correct. For cases in which a patient’s interpretation or a provider’s diagnosis was imputed from the indication(s) associated with the medication(s) being used, one cannot exclude the possibility that a medication was used appropriately for a nonlabeled or nonstandard indication. The designation of treatment errors may be subject to different interpretations by different clinicians. Despite these limitations, it is likely that the results of this study can be extrapolated to reasonably similar dermatology practices. The apparently persistent and consistent tendency of clinicians to incorrectly diagnose infectious dermatoses and to miss inflammatory conditions has implications for teaching of medical dermatology in the academic and clinical settings. In particular, given that dermatophytosis is the diagnosis involved in the highest number of errors, special emphasis should be placed on this infection in clinician education.
Acknowledgement—The authors would like to acknowledge the essential contributions to this study by Urvi Jain (Virginia Beach, Virginia), particularly for analysis and interpretation of data and for suggestions to improve the manuscript.
- Institute of Medicine (US) Committee on Quality of Health Care in America. To Err is Human: Building a Safer Health System. Kohn LT, Corrigan JM, Donaldson MS, eds. National Academies Press; 2000.
- Lowenstein EJ, Sidlow R, Ko CJ. Visual perception, cognition, and error in dermatologic diagnosis: diagnosis and error. J Am Acad Dermatol. 2019;81:1237-1245.
- Ko CJ, Braverman I, Sidlow R, et al. Visual perception, cognition, and error in dermatologic diagnosis: key cognitive principles. J Am Acad Dermatol. 2019;81:1227-1234.
- Lowenstein EJ. Dermatology and its unique diagnostic heuristics. J Am Acad Dermatol. 2018;78:1239-1240.
- Elston DM. Cognitive bias and medical errors. J Am Acad Dermatol. 2019;81:1249.
- Costa Filho GB, Moura AS, Brandão PR, et al. Effects of deliberate reflection on diagnostic accuracy, confidence and diagnostic calibration in dermatology. Perspect Med Educ. 2019;8:230-236.
- Pariser RJ, Pariser DM. Primary physicians’ errors in handling cutaneous disorders. J Am Acad Dermatol. 1987;17:239-245.
- van Rossum G, Drake FL Jr. Python Reference Manual. Centrum voor Wiskunde en Informatica; 1995.
- The pandas development team. pandas-dev/pandas: Pandas. Zenodo. February 2020. doi:10.5281/zenodo.3509134
- Murphy EC, Friedman AJ. Use of in-office preparations by dermatologists for the diagnosis of cutaneous fungal infections. J Drugs Dermatol. 2019;18:798-802.
- Dhafiri MA, Alhamed AS, Aljughayman MA. Use of potassium hydroxide in dermatology daily practice: a local study from Saudi Arabia. Cureus. 2022;14:E30612. doi:10.7759/cureus .30612.eCollection
- Chandler JD, Yamamoto R, Hay RJ. Use of direct microscopy to diagnose superficial mycoses: a survey of UK dermatology practice. Br J Dermatol. 2023;189:480-481.
Humans are inherently prone to errors. The extent and consequences of medical errors were documented in the 2000 publication of To Err is Human: Building a Safer Health System.1 Published research on medical errors in dermatology has emphasized the heuristic issues involved in diagnosis,2-6 essentially approaching the “why?” and “how?” of such errors. By contrast, the current study aimed to elucidate the “what?”—what are the dermatologic conditions most prone to diagnostic and/or management errors? One study published in 1987 approached this question by analyzing patterns of errors for dermatologic conditions in patients referred for specialty care by primary care physicians.7 The current study aimed to update and expand on the findings of this 1987 report by comparing more recent data on the errors made by providers and patients regarding skin conditions.
Methods
Data were collected prospectively from March 18, 2021, through July 25, 2023. Prospective data were obtained by recording the nature of errors noted for all patients seen by a board-certified dermatologist (R.J.P.) during routine outpatient practice in Norfolk, Virginia. This practice is limited to medical dermatology and accepts patients of any age from any referral source, with or without medical insurance. Retrospective data were obtained by review of electronic medical records for all patients seen by the same board-certified dermatologist from June 5, 2020, through March 12, 2021, who previously had been seen by an outside provider or were self-referred. In this study, the term diagnosis is used to describe providers’ explicit or imputed conclusions as to the nature of a dermatosis, and the term interpretation is used to describe patients' conclusions about their own condition. For this study, the patients’ self-made interpretations of their dermatoses were deemed to be correct when they agreed with those made by the dermatologist using standard clinicopathologic criteria supplemented by rapid bedside diagnostic techniques, as detailed in the 1987 study.7
Cases in which diagnostic or therapeutic errors were noted were entered into a spreadsheet that excluded patients’ names or other identifiers. For each noted case of diagnostic or therapeutic error, the following data were entered: patient’s age and sex; the name of the incorrect diagnosis, interpretation, or treatment; and the name of the correct (missed) diagnosis, along with the source of the error (provider or patient). Provider diagnoses were determined from medical records or patient statements or were imputed from the generally accepted indications for prescribed treatments. A provider was deemed to be any practitioner with prescriptive authority. Patients’ interpretations of their conditions were determined by patient statements or were imputed based on the indications for treatments being used. A treatment error was recorded when a diagnosis or interpretation was deemed to be correct, but treatment was deemed to be inappropriate. The same dermatologist (R.J.P) made all determinations as to the nature of the errors and their source.
Diagnostic errors were determined in several situations: (1) if the interpretation made by the patient of their dermatosis differed from the correct diagnosis in the absence of any additional diagnostic documentation, the correct diagnosis was scored as a missed diagnosis and the incorrect interpretation was scored as such; (2) if the provider’s diagnosis in the patient’s medical record differed from the correct diagnosis, both the correct (missed) and incorrect diagnoses were recorded; and (3) if the indication(s) of the medication(s) prescribed by the provider or used by the patient for their condition differed from the correct diagnosis, an imputed diagnosis based on this indication was scored as the incorrect diagnosis and the correct (missed) diagnosis was recorded; for example, an error would be entered into the spreadsheet for a patient using terbinafine cream for what was actually psoriasis. For a medication with multiple active agents, an error would be entered into the spreadsheet only if none of its indications matched the correct diagnosis; for example, if the patient had been prescribed a betamethasone/clotrimazole product, no error would be scored if the correct diagnosis was a steroid-responsive dermatosis, dermatophytosis, candidiasis, or tinea versicolor. For a single medication with multiple indications, no error would be recorded if the correct diagnosis was any of these indications; for example, in a patient who had been prescribed topical ketoconazole, no error would be scored if the correct diagnosis was dermatophytosis, candidiasis, tinea versicolor, or seborrheic dermatitis. Additionally, no error would be recorded if the correct diagnosis was uncertain at the time of initial patient evaluation or during chart review.
Standard spreadsheet functions and the pandas package8 from the Python programming language9 were used to extract relevant data from the spreadsheet (Tables 1-4).




Results
A total of 446 patient visits (182 males, 264 females) were included in the study, in which a total of 486 errors were found in the combined prospective and retrospective portions of the study. These errors involved 1.4% of all patient visits for the study period—specifically, all in routine practice as well as all patient records retrospectively reviewed. The age of the patients ranged from 4 to 95 years; the mean age was 51.5 years for males and 50.8 years for females.
The study results are outlined in Tables 1 through 4. To minimize the amount of data provided with no appreciable effect on the results, cases in which an incorrect or missed diagnosis/interpretation occurred only once (ie, unique case errors) were excluded from the tables. Tables 1 and 2 indicate the numbers and types of incorrect and missed diagnoses.
In the combined patient and provider cases, there were 434 instances in which provider diagnoses and patient interpretations were incorrect, 320 (73.7%) of which involved infectious disorders. By contrast, of the 413 instances of provider and patient missed diagnoses 289 (70.0%) were inflammatory dermatoses. The pattern was similar for patients’ incorrect interpretations compared to the incorrect diagnoses of the medical providers. Patients incorrectly interpreted their dermatoses as infectious in 79.5% (101/127) of cases. Similarly, providers incorrectly diagnosed their patients’ dermatoses as infectious in 75.4% (211/280) of cases (Table 3). For patients’ missed diagnoses, 70.7% (82/116) involved inflammatory dermatoses. For providers’ missed diagnoses, 63.9% (179/280) involved inflammatory dermatoses (Table 4).
Treatment errors in the context of correct diagnoses were uncommon. Fifteen (3.4%) such cases were noted in the 446 error-containing patient visits. In 4 (26.7%) of the 15 cases, potent topical corticosteroids were used long term on inappropriate cutaneous sites (eg, genital, facial, or intertriginous areas). Another 4 (26.7%) cases involved fungal infections: nystatin used for tinea versicolor in 1 case and for dermatophytosis in another, widespread dermatophytosis treated topically, and use of a nonindicated topical antifungal for onychomycosis. Other examples involved inadequate dosing of systemic corticosteroids for extensive acute contact dermatitis, psoriasis treated with systemic corticosteroids, inadequate dosing of medication for seborrheic dermatitis, and treatment with valacyclovir based solely on serologic testing.
Comment
The results of our study indicate that errors in management of cutaneous disorders are overwhelmingly diagnostic in nature, while treatment errors appear to be unusual when the correct diagnosis is made. Both the current study and the 1987 study indicated a notable tendency of providers to incorrectly diagnose infectious disorders and to miss the diagnosis of inflammatory dermatoses.7 The current study extends this finding to include patients’ interpretive errors.
It is notable that many of the incorrect and missed diagnoses can be confirmed or ruled out by rapid bedside techniques, namely potassium hydroxide (KOH) preparation for dermatophytes, candidiasis, and tinea versicolor; wet preparation for scabies and pediculosis; Tzanck preparation for herpes simplex and herpes zoster; and crush preparation for molluscum contagiosum. Notably, 57.8% (281/486) of cases in which error was noted involved disorders for which the use of one of these bedside diagnostic tests could have correctly established a diagnosis or ruled out an incorrect one; thus in an ideal world in which these tests were performed perfectly in all appropriate cases, more than half of the errors detected in this study could have been avoided. Dermatophytosis was involved in 35.8% (174/486) of the error-containing patient encounters in this study; therefore, if only the KOH preparation is considered, more than one-third of all errors documented in this study could have been avoided. Unfortunately, surveys have suggested that among dermatologists in the United States and some other countries, KOH preparations are used infrequently.10-12
Certain limitations were inherent to this study. The data were derived from a single dermatology practice by one physician in one geographic region over a short period of time. These factors may limit the generalizability of the results. Although the goal was to identify all errors made for the patients seen, some errors likely were missed due to incomplete patient history or inaccurate medication listings. There is no absolute way to determine if the diagnoses or the treatments deemed correct by the dermatologist were, in fact, correct. For cases in which a patient’s interpretation or a provider’s diagnosis was imputed from the indication(s) associated with the medication(s) being used, one cannot exclude the possibility that a medication was used appropriately for a nonlabeled or nonstandard indication. The designation of treatment errors may be subject to different interpretations by different clinicians. Despite these limitations, it is likely that the results of this study can be extrapolated to reasonably similar dermatology practices. The apparently persistent and consistent tendency of clinicians to incorrectly diagnose infectious dermatoses and to miss inflammatory conditions has implications for teaching of medical dermatology in the academic and clinical settings. In particular, given that dermatophytosis is the diagnosis involved in the highest number of errors, special emphasis should be placed on this infection in clinician education.
Acknowledgement—The authors would like to acknowledge the essential contributions to this study by Urvi Jain (Virginia Beach, Virginia), particularly for analysis and interpretation of data and for suggestions to improve the manuscript.
Humans are inherently prone to errors. The extent and consequences of medical errors were documented in the 2000 publication of To Err is Human: Building a Safer Health System.1 Published research on medical errors in dermatology has emphasized the heuristic issues involved in diagnosis,2-6 essentially approaching the “why?” and “how?” of such errors. By contrast, the current study aimed to elucidate the “what?”—what are the dermatologic conditions most prone to diagnostic and/or management errors? One study published in 1987 approached this question by analyzing patterns of errors for dermatologic conditions in patients referred for specialty care by primary care physicians.7 The current study aimed to update and expand on the findings of this 1987 report by comparing more recent data on the errors made by providers and patients regarding skin conditions.
Methods
Data were collected prospectively from March 18, 2021, through July 25, 2023. Prospective data were obtained by recording the nature of errors noted for all patients seen by a board-certified dermatologist (R.J.P.) during routine outpatient practice in Norfolk, Virginia. This practice is limited to medical dermatology and accepts patients of any age from any referral source, with or without medical insurance. Retrospective data were obtained by review of electronic medical records for all patients seen by the same board-certified dermatologist from June 5, 2020, through March 12, 2021, who previously had been seen by an outside provider or were self-referred. In this study, the term diagnosis is used to describe providers’ explicit or imputed conclusions as to the nature of a dermatosis, and the term interpretation is used to describe patients' conclusions about their own condition. For this study, the patients’ self-made interpretations of their dermatoses were deemed to be correct when they agreed with those made by the dermatologist using standard clinicopathologic criteria supplemented by rapid bedside diagnostic techniques, as detailed in the 1987 study.7
Cases in which diagnostic or therapeutic errors were noted were entered into a spreadsheet that excluded patients’ names or other identifiers. For each noted case of diagnostic or therapeutic error, the following data were entered: patient’s age and sex; the name of the incorrect diagnosis, interpretation, or treatment; and the name of the correct (missed) diagnosis, along with the source of the error (provider or patient). Provider diagnoses were determined from medical records or patient statements or were imputed from the generally accepted indications for prescribed treatments. A provider was deemed to be any practitioner with prescriptive authority. Patients’ interpretations of their conditions were determined by patient statements or were imputed based on the indications for treatments being used. A treatment error was recorded when a diagnosis or interpretation was deemed to be correct, but treatment was deemed to be inappropriate. The same dermatologist (R.J.P) made all determinations as to the nature of the errors and their source.
Diagnostic errors were determined in several situations: (1) if the interpretation made by the patient of their dermatosis differed from the correct diagnosis in the absence of any additional diagnostic documentation, the correct diagnosis was scored as a missed diagnosis and the incorrect interpretation was scored as such; (2) if the provider’s diagnosis in the patient’s medical record differed from the correct diagnosis, both the correct (missed) and incorrect diagnoses were recorded; and (3) if the indication(s) of the medication(s) prescribed by the provider or used by the patient for their condition differed from the correct diagnosis, an imputed diagnosis based on this indication was scored as the incorrect diagnosis and the correct (missed) diagnosis was recorded; for example, an error would be entered into the spreadsheet for a patient using terbinafine cream for what was actually psoriasis. For a medication with multiple active agents, an error would be entered into the spreadsheet only if none of its indications matched the correct diagnosis; for example, if the patient had been prescribed a betamethasone/clotrimazole product, no error would be scored if the correct diagnosis was a steroid-responsive dermatosis, dermatophytosis, candidiasis, or tinea versicolor. For a single medication with multiple indications, no error would be recorded if the correct diagnosis was any of these indications; for example, in a patient who had been prescribed topical ketoconazole, no error would be scored if the correct diagnosis was dermatophytosis, candidiasis, tinea versicolor, or seborrheic dermatitis. Additionally, no error would be recorded if the correct diagnosis was uncertain at the time of initial patient evaluation or during chart review.
Standard spreadsheet functions and the pandas package8 from the Python programming language9 were used to extract relevant data from the spreadsheet (Tables 1-4).




Results
A total of 446 patient visits (182 males, 264 females) were included in the study, in which a total of 486 errors were found in the combined prospective and retrospective portions of the study. These errors involved 1.4% of all patient visits for the study period—specifically, all in routine practice as well as all patient records retrospectively reviewed. The age of the patients ranged from 4 to 95 years; the mean age was 51.5 years for males and 50.8 years for females.
The study results are outlined in Tables 1 through 4. To minimize the amount of data provided with no appreciable effect on the results, cases in which an incorrect or missed diagnosis/interpretation occurred only once (ie, unique case errors) were excluded from the tables. Tables 1 and 2 indicate the numbers and types of incorrect and missed diagnoses.
In the combined patient and provider cases, there were 434 instances in which provider diagnoses and patient interpretations were incorrect, 320 (73.7%) of which involved infectious disorders. By contrast, of the 413 instances of provider and patient missed diagnoses 289 (70.0%) were inflammatory dermatoses. The pattern was similar for patients’ incorrect interpretations compared to the incorrect diagnoses of the medical providers. Patients incorrectly interpreted their dermatoses as infectious in 79.5% (101/127) of cases. Similarly, providers incorrectly diagnosed their patients’ dermatoses as infectious in 75.4% (211/280) of cases (Table 3). For patients’ missed diagnoses, 70.7% (82/116) involved inflammatory dermatoses. For providers’ missed diagnoses, 63.9% (179/280) involved inflammatory dermatoses (Table 4).
Treatment errors in the context of correct diagnoses were uncommon. Fifteen (3.4%) such cases were noted in the 446 error-containing patient visits. In 4 (26.7%) of the 15 cases, potent topical corticosteroids were used long term on inappropriate cutaneous sites (eg, genital, facial, or intertriginous areas). Another 4 (26.7%) cases involved fungal infections: nystatin used for tinea versicolor in 1 case and for dermatophytosis in another, widespread dermatophytosis treated topically, and use of a nonindicated topical antifungal for onychomycosis. Other examples involved inadequate dosing of systemic corticosteroids for extensive acute contact dermatitis, psoriasis treated with systemic corticosteroids, inadequate dosing of medication for seborrheic dermatitis, and treatment with valacyclovir based solely on serologic testing.
Comment
The results of our study indicate that errors in management of cutaneous disorders are overwhelmingly diagnostic in nature, while treatment errors appear to be unusual when the correct diagnosis is made. Both the current study and the 1987 study indicated a notable tendency of providers to incorrectly diagnose infectious disorders and to miss the diagnosis of inflammatory dermatoses.7 The current study extends this finding to include patients’ interpretive errors.
It is notable that many of the incorrect and missed diagnoses can be confirmed or ruled out by rapid bedside techniques, namely potassium hydroxide (KOH) preparation for dermatophytes, candidiasis, and tinea versicolor; wet preparation for scabies and pediculosis; Tzanck preparation for herpes simplex and herpes zoster; and crush preparation for molluscum contagiosum. Notably, 57.8% (281/486) of cases in which error was noted involved disorders for which the use of one of these bedside diagnostic tests could have correctly established a diagnosis or ruled out an incorrect one; thus in an ideal world in which these tests were performed perfectly in all appropriate cases, more than half of the errors detected in this study could have been avoided. Dermatophytosis was involved in 35.8% (174/486) of the error-containing patient encounters in this study; therefore, if only the KOH preparation is considered, more than one-third of all errors documented in this study could have been avoided. Unfortunately, surveys have suggested that among dermatologists in the United States and some other countries, KOH preparations are used infrequently.10-12
Certain limitations were inherent to this study. The data were derived from a single dermatology practice by one physician in one geographic region over a short period of time. These factors may limit the generalizability of the results. Although the goal was to identify all errors made for the patients seen, some errors likely were missed due to incomplete patient history or inaccurate medication listings. There is no absolute way to determine if the diagnoses or the treatments deemed correct by the dermatologist were, in fact, correct. For cases in which a patient’s interpretation or a provider’s diagnosis was imputed from the indication(s) associated with the medication(s) being used, one cannot exclude the possibility that a medication was used appropriately for a nonlabeled or nonstandard indication. The designation of treatment errors may be subject to different interpretations by different clinicians. Despite these limitations, it is likely that the results of this study can be extrapolated to reasonably similar dermatology practices. The apparently persistent and consistent tendency of clinicians to incorrectly diagnose infectious dermatoses and to miss inflammatory conditions has implications for teaching of medical dermatology in the academic and clinical settings. In particular, given that dermatophytosis is the diagnosis involved in the highest number of errors, special emphasis should be placed on this infection in clinician education.
Acknowledgement—The authors would like to acknowledge the essential contributions to this study by Urvi Jain (Virginia Beach, Virginia), particularly for analysis and interpretation of data and for suggestions to improve the manuscript.
- Institute of Medicine (US) Committee on Quality of Health Care in America. To Err is Human: Building a Safer Health System. Kohn LT, Corrigan JM, Donaldson MS, eds. National Academies Press; 2000.
- Lowenstein EJ, Sidlow R, Ko CJ. Visual perception, cognition, and error in dermatologic diagnosis: diagnosis and error. J Am Acad Dermatol. 2019;81:1237-1245.
- Ko CJ, Braverman I, Sidlow R, et al. Visual perception, cognition, and error in dermatologic diagnosis: key cognitive principles. J Am Acad Dermatol. 2019;81:1227-1234.
- Lowenstein EJ. Dermatology and its unique diagnostic heuristics. J Am Acad Dermatol. 2018;78:1239-1240.
- Elston DM. Cognitive bias and medical errors. J Am Acad Dermatol. 2019;81:1249.
- Costa Filho GB, Moura AS, Brandão PR, et al. Effects of deliberate reflection on diagnostic accuracy, confidence and diagnostic calibration in dermatology. Perspect Med Educ. 2019;8:230-236.
- Pariser RJ, Pariser DM. Primary physicians’ errors in handling cutaneous disorders. J Am Acad Dermatol. 1987;17:239-245.
- van Rossum G, Drake FL Jr. Python Reference Manual. Centrum voor Wiskunde en Informatica; 1995.
- The pandas development team. pandas-dev/pandas: Pandas. Zenodo. February 2020. doi:10.5281/zenodo.3509134
- Murphy EC, Friedman AJ. Use of in-office preparations by dermatologists for the diagnosis of cutaneous fungal infections. J Drugs Dermatol. 2019;18:798-802.
- Dhafiri MA, Alhamed AS, Aljughayman MA. Use of potassium hydroxide in dermatology daily practice: a local study from Saudi Arabia. Cureus. 2022;14:E30612. doi:10.7759/cureus .30612.eCollection
- Chandler JD, Yamamoto R, Hay RJ. Use of direct microscopy to diagnose superficial mycoses: a survey of UK dermatology practice. Br J Dermatol. 2023;189:480-481.
- Institute of Medicine (US) Committee on Quality of Health Care in America. To Err is Human: Building a Safer Health System. Kohn LT, Corrigan JM, Donaldson MS, eds. National Academies Press; 2000.
- Lowenstein EJ, Sidlow R, Ko CJ. Visual perception, cognition, and error in dermatologic diagnosis: diagnosis and error. J Am Acad Dermatol. 2019;81:1237-1245.
- Ko CJ, Braverman I, Sidlow R, et al. Visual perception, cognition, and error in dermatologic diagnosis: key cognitive principles. J Am Acad Dermatol. 2019;81:1227-1234.
- Lowenstein EJ. Dermatology and its unique diagnostic heuristics. J Am Acad Dermatol. 2018;78:1239-1240.
- Elston DM. Cognitive bias and medical errors. J Am Acad Dermatol. 2019;81:1249.
- Costa Filho GB, Moura AS, Brandão PR, et al. Effects of deliberate reflection on diagnostic accuracy, confidence and diagnostic calibration in dermatology. Perspect Med Educ. 2019;8:230-236.
- Pariser RJ, Pariser DM. Primary physicians’ errors in handling cutaneous disorders. J Am Acad Dermatol. 1987;17:239-245.
- van Rossum G, Drake FL Jr. Python Reference Manual. Centrum voor Wiskunde en Informatica; 1995.
- The pandas development team. pandas-dev/pandas: Pandas. Zenodo. February 2020. doi:10.5281/zenodo.3509134
- Murphy EC, Friedman AJ. Use of in-office preparations by dermatologists for the diagnosis of cutaneous fungal infections. J Drugs Dermatol. 2019;18:798-802.
- Dhafiri MA, Alhamed AS, Aljughayman MA. Use of potassium hydroxide in dermatology daily practice: a local study from Saudi Arabia. Cureus. 2022;14:E30612. doi:10.7759/cureus .30612.eCollection
- Chandler JD, Yamamoto R, Hay RJ. Use of direct microscopy to diagnose superficial mycoses: a survey of UK dermatology practice. Br J Dermatol. 2023;189:480-481.
Analysis of Errors in the Management of Cutaneous Disorders
Analysis of Errors in the Management of Cutaneous Disorders
PRACTICE POINTS
- Errors in the management of cutaneous disorders predominantly are due to misdiagnosis rather than treatment oversights.
- There is a tendency among medical providers to incorrectly diagnose dermatoses as infectious disorders and to miss the diagnosis of inflammatory dermatoses.
- A similar pattern of errors occurs for patients’ interpretations of their own skin conditions.
- Use of available rapid bedside diagnostic techniques can reduce the likelihood of errors made by medical providers.
Scholarly Activity Among VA Podiatrists: A Cross-Sectional Study
Scholarly Activity Among VA Podiatrists: A Cross-Sectional Study
The US Department of Veterans Affairs (VA) delivers care to > 9 million veterans, including primary and specialty care.1 While clinical duties remain important across the health system, proposed productivity models have included clinician research activity, given that many hold roles in academia.2 Within this framework, research plays a pivotal role in advancing clinical practices and outcomes. Studies have found that physicians who participated in research report higher job satisfaction.3
As a specialty within the VA, podiatrists diagnose, treat, and prevent foot and ankle disorders. In addition to clinical practice, various scholarly activities are shared among these physicians.4 Reasons for scholarly pursuits among podiatrists vary, including participation in research for academic promotion or to establish expertise in a given area.4-7 Although research remains a component associated with promotion within the VA, little is known about the scholarly activity of VA podiatrists. Specifically, there remains a paucity of data concerning their expertise, as evidenced through peer-reviewed publications, among these physicians and surgeons. To date, no analysis of scholarly activity among VA podiatrists has been conducted.
The primary aim of this investigation was to describe the scholarly productivity among podiatrists employed by the VA through an analysis of the number of peer-reviewed publications and the respective h-index of each physician. The secondary aim of this investigation was to assess the effect of academic productivity on compensation. This study describes research activities pursued by VA physicians and provides the veteran patient population with the confidence that their foot health care remains in the hands of experts within the field.
MATERIALS AND METHODS
The Feds Data Center (www.fedsdatacenter.com) online database of employees was used to identify VA podiatrists on June 17, 2024. All GS-15 physicians and their respective salaries in fiscal year 2023 were recorded. Administratively determined employees, including residents, were excluded. The h-index and number of published documents from any point during a physician’s training or career were reported for each podiatrist using Scopus; podiatrists without an h-index or publication were excluded. 8 Among podiatrists with scholarly activity, this analysis collected academic appointment, sex, and region of practice.
Statistical Analysis
Descriptive statistics, presented as counts and frequencies, were used. The median and IQR were used to describe the number of publications and h-index due to their nonnormal distribution. A Kruskal-Wallis test was used to compare median publication counts and h-index values among for junior faculty (JF), which includes instructors and assistant professors; senior faculty (SF), which includes associate professors and professors; and those with no academic affiliation (NF). Salary was reported as mean (SD) as it remained normally distributed and was compared using analysis of variance with posthoc Tukey test to increase statistical power. Additionally, this analysis used linear regression to investigate the relationship between scholarly activity and salary. The threshold for statistical significance was set at P < .05.
RESULTS
Among 819 VA podiatrists, 150 were administratively determined and excluded, and 512 were excluded for no history of publications, leaving 157 eligible for analysis (Table). A statistically significant difference was found in median (IQR) publication count by faculty appointment. JF had 6.0 (9.5), SF had 12.5 (22.3), and NF had 1.0 (2.0) publication(s) (P < .001) (Figure 1A). There was a statistically significant difference in h-index by faculty appointment. The median (IQR) h-index for JF was 2.0 (3.5), for SF was 5.5 (4.25), and for NF was 1.0 (2.0) (P = .002) (Figure 1B). Salary was not significantly associated with publication count (P = .20) or h-index (P = .62) (Figure 2). No statistically significant difference was found between academic appointment and mean (SD) salary. JF had a median (IQR) salary of $224,063 (27,989), SF of $234,260 (42,963), and NF of $219,811 (P = .35).

(B) h-index.a
aBox sizes indicate IQR (bottom, IQR 1; top, IQR 3); whiskers indicate minimum and maximum within 1.5 x IQR; Xs indicate means; white
lines indicate medians; and dots indicate outliers.

(B) h-index.a
aBox sizes indicate IQR (bottom, IQR 1; top, IQR 3); whiskers indicate minimum and maximum within 1.5 x IQR; Xs indicate means; white
lines indicate medians; and dots indicate outliers.


DISCUSSION
Focused on providing high-quality care, VA physicians use their expertise to practice comprehensive and specialized care.9,10 A cornerstone to this expertise is scholarly activity that contributes to the body of knowledge and, ultimately, the evidence-based medicine by which these physicians practice.11 With veterans considering VA care, it is important to highlight the commitment and dedication to the science and the practice of medicine. This analysis describes the scholarly activity of VA podiatrists and underscores the expertise veterans will receive for the diagnosis and treatment of their foot and ankle pathology.
were not part of an academic facility, a finding that may encourage further action to increase academic productivity in this specialty. For example, collaboration through academic affiliations has been seen throughout VA medical and surgical specialties and provides many benefits. Beginning with graduate medical education, the VA serves as a tremendous resource for resident training.12 Additionally, veterans who sought emergency care at the VA had a lower risk of death than those treated at non-VA hospitals.13 In podiatric medicine and surgery, scholarly activity has been linked to improved outcomes, particularly in the study of ulceration development and its role in either prolonging or preventing amputation.14
Beyond improving clinical outcomes and patient care, engagement in research and inquiry offers other benefits. A cross-sectional study of 7734 physicians within the VA found that research involvement was associated with more favorable job characteristics and job satisfaction perceptions. 3 While this analysis found that about 19% of podiatrists have published once in their career, it remains likely that more may continue to engage in research during their VA tenure. Although this finding shows that an appreciable number of VA podiatrists have published in their field of study, it also encourages departments to provide resources to engage in research. Similar to previous research among foot and ankle surgeons, this analysis also found an increase in publications and h-index as tenure increased.4 Unlike previous research, which found h-index and academic appointment to be contributors to VA dermatologists’ salaries, no significant difference in salary was found in this study associated with publications, h-index, or academic role.15 Although the increase was not statistically significant, salary tended to rise as these variables increased.
Limitations
This analysis was confined to the most recent year of available data, which may not fully capture the longitudinal academic contributions and trends of individual podiatrists. Academic productivity can fluctuate significantly over time due to various factors, including changes in research focus and administrative responsibilities. The study also relied on Scopus to identify and quantify academic productivity. This database may not include all publications relevant to podiatrists, particularly those in niche or nonindexed journals. Additionally, name variations and potential misspellings could lead to missing data for individual podiatrists’ publications. Furthermore, this study did not account for other significant contributors to salary and career advancement within the federal system. Factors such as clinical performance, administrative duties, patient satisfaction, and contributions to teaching and mentoring are critical elements that also influence career progression and compensation but were not captured in this analysis. The retrospective design of this study inherently limits the ability to establish causal relationships. While associations between academic productivity and certain outcomes may be identified, it is not possible to definitively determine the direction or causality of these relationships. Future research may examine how scholarly activity continues once a clinician is part of VA.
CONCLUSIONS
This study highlights the significant academic contributions of VA podiatrists to research and the medical literature. By fostering an active research environment, the VA can ensure veterans receive the highest quality of care from knowledgeable and expert clinicians. Future research should aim to provide a more comprehensive analysis, capturing long-term trends and considering all factors influencing career advancement in VA.
- Rosland AM, Nelson K, Sun H, et al. The patient-centered medical home in the Veterans Health Administration. Am J Manag Care. 2013;19(7):e263-e272.
- Coleman DL, Moran E, Serfilippi D, et al. Measuring physicians’ productivity in a Veterans’ Affairs Medical Center. Acad Med. 2003;78(7):682-689. doi:10.1097/00001888-200307000-00007
- Mohr DC, Burgess JF Jr. Job characteristics and job satisfaction among physicians involved with research in the Veterans Health Administration. Acad Med. 2011;86(8):938-945. doi:10.1097/ACM.0b013e3182223b76
- Casciato DJ, Cravey KS, Barron IM. Scholarly productivity among academic foot and ankle surgeons affiliated with US podiatric medicine and surgery residency and fellowship training programs. J Foot Ankle Surg. 2021;60(6):1222-1226. doi:10.1053/j.jfas.2021.04.017
- Hyer CF, Casciato DJ, Rushing CJ, Schuberth JM. Incidence of scholarly publication by selected content experts presenting at national society foot and ankle meetings from 2016 to 2020. J Foot Ankle Surg. 2022;61(6):1317-1320. doi:10.1053/j.jfas.2022.04.011
- Casciato DJ, Thompson J, Yancovitz S, Chandra A, Prissel MA, Hyer CF. Research activity among foot and ankle surgery fellows: a systematic review. J Foot Ankle Surg. 2021;60(6):1227-1231. doi:10.1053/j.jfas.2021.04.018
- Casciato DJ, Thompson J, Hyer CF. Post-fellowship foot and ankle surgeon research productivity: a systematic review. J Foot Ankle Surg. 2022;61(4):896-899. doi:10.1053/j.jfas.2021.12.028
- Hirsch JE. An index to quantify an individual’s scientific research output. Proc Natl Acad Sci USA. 2005;102(46):16569-16572. doi:10.1073/pnas.0507655102
- US Department of Veterans Affairs. Veterans Health Administration. About VHA. Updated January 20, 2025. Accessed February 17, 2025. https://www.va.gov/health/aboutvha.asp
- US Department of Veterans Affairs. VHA National Center for Patient Safety. About Us. Updated November 29, 2023. Accessed February 17, 2025. https://www.patientsafety.va.gov/
- US Department of Veterans Affairs. VA/DoD Clinical Practice Guidelines. Updated February 7, 2025. Accessed February 17, 2025. https://www.healthquality.va.gov
- Ravin AG, Gottlieb NB, Wang HT, et al. Effect of the Veterans Affairs Medical System on plastic surgery residency training. Plast Reconstr Surg. 2006;117(2):656-660. doi:10.1097/01.prs.0000197216.95544.f7
- Chan DC, Danesh K, Costantini S, Card D, Taylor L, Studdert DM. Mortality among US veterans after emergency visits to Veterans Affairs and other hospitals: retrospective cohort study. BMJ. 2022;376:e068099. doi:10.1136/bmj-2021-068099
- Gibson LW, Abbas A. Limb salvage for veterans with diabetes: to care for him who has borne the battle. Crit Care Nurs Clin North Am. 2013;25(1):131-134. doi:10.1016/j.ccell.2012.11.004
- Do MH, Lipner SR. Contribution of gender on compensation of Veterans Affairs-affiliated dermatologists: a cross-sectional study. Int J Womens Dermatol. 2020;6(5):414-418. doi:10.1016/j.ijwd.2020.09.009
The US Department of Veterans Affairs (VA) delivers care to > 9 million veterans, including primary and specialty care.1 While clinical duties remain important across the health system, proposed productivity models have included clinician research activity, given that many hold roles in academia.2 Within this framework, research plays a pivotal role in advancing clinical practices and outcomes. Studies have found that physicians who participated in research report higher job satisfaction.3
As a specialty within the VA, podiatrists diagnose, treat, and prevent foot and ankle disorders. In addition to clinical practice, various scholarly activities are shared among these physicians.4 Reasons for scholarly pursuits among podiatrists vary, including participation in research for academic promotion or to establish expertise in a given area.4-7 Although research remains a component associated with promotion within the VA, little is known about the scholarly activity of VA podiatrists. Specifically, there remains a paucity of data concerning their expertise, as evidenced through peer-reviewed publications, among these physicians and surgeons. To date, no analysis of scholarly activity among VA podiatrists has been conducted.
The primary aim of this investigation was to describe the scholarly productivity among podiatrists employed by the VA through an analysis of the number of peer-reviewed publications and the respective h-index of each physician. The secondary aim of this investigation was to assess the effect of academic productivity on compensation. This study describes research activities pursued by VA physicians and provides the veteran patient population with the confidence that their foot health care remains in the hands of experts within the field.
MATERIALS AND METHODS
The Feds Data Center (www.fedsdatacenter.com) online database of employees was used to identify VA podiatrists on June 17, 2024. All GS-15 physicians and their respective salaries in fiscal year 2023 were recorded. Administratively determined employees, including residents, were excluded. The h-index and number of published documents from any point during a physician’s training or career were reported for each podiatrist using Scopus; podiatrists without an h-index or publication were excluded. 8 Among podiatrists with scholarly activity, this analysis collected academic appointment, sex, and region of practice.
Statistical Analysis
Descriptive statistics, presented as counts and frequencies, were used. The median and IQR were used to describe the number of publications and h-index due to their nonnormal distribution. A Kruskal-Wallis test was used to compare median publication counts and h-index values among for junior faculty (JF), which includes instructors and assistant professors; senior faculty (SF), which includes associate professors and professors; and those with no academic affiliation (NF). Salary was reported as mean (SD) as it remained normally distributed and was compared using analysis of variance with posthoc Tukey test to increase statistical power. Additionally, this analysis used linear regression to investigate the relationship between scholarly activity and salary. The threshold for statistical significance was set at P < .05.
RESULTS
Among 819 VA podiatrists, 150 were administratively determined and excluded, and 512 were excluded for no history of publications, leaving 157 eligible for analysis (Table). A statistically significant difference was found in median (IQR) publication count by faculty appointment. JF had 6.0 (9.5), SF had 12.5 (22.3), and NF had 1.0 (2.0) publication(s) (P < .001) (Figure 1A). There was a statistically significant difference in h-index by faculty appointment. The median (IQR) h-index for JF was 2.0 (3.5), for SF was 5.5 (4.25), and for NF was 1.0 (2.0) (P = .002) (Figure 1B). Salary was not significantly associated with publication count (P = .20) or h-index (P = .62) (Figure 2). No statistically significant difference was found between academic appointment and mean (SD) salary. JF had a median (IQR) salary of $224,063 (27,989), SF of $234,260 (42,963), and NF of $219,811 (P = .35).

(B) h-index.a
aBox sizes indicate IQR (bottom, IQR 1; top, IQR 3); whiskers indicate minimum and maximum within 1.5 x IQR; Xs indicate means; white
lines indicate medians; and dots indicate outliers.

(B) h-index.a
aBox sizes indicate IQR (bottom, IQR 1; top, IQR 3); whiskers indicate minimum and maximum within 1.5 x IQR; Xs indicate means; white
lines indicate medians; and dots indicate outliers.


DISCUSSION
Focused on providing high-quality care, VA physicians use their expertise to practice comprehensive and specialized care.9,10 A cornerstone to this expertise is scholarly activity that contributes to the body of knowledge and, ultimately, the evidence-based medicine by which these physicians practice.11 With veterans considering VA care, it is important to highlight the commitment and dedication to the science and the practice of medicine. This analysis describes the scholarly activity of VA podiatrists and underscores the expertise veterans will receive for the diagnosis and treatment of their foot and ankle pathology.
were not part of an academic facility, a finding that may encourage further action to increase academic productivity in this specialty. For example, collaboration through academic affiliations has been seen throughout VA medical and surgical specialties and provides many benefits. Beginning with graduate medical education, the VA serves as a tremendous resource for resident training.12 Additionally, veterans who sought emergency care at the VA had a lower risk of death than those treated at non-VA hospitals.13 In podiatric medicine and surgery, scholarly activity has been linked to improved outcomes, particularly in the study of ulceration development and its role in either prolonging or preventing amputation.14
Beyond improving clinical outcomes and patient care, engagement in research and inquiry offers other benefits. A cross-sectional study of 7734 physicians within the VA found that research involvement was associated with more favorable job characteristics and job satisfaction perceptions. 3 While this analysis found that about 19% of podiatrists have published once in their career, it remains likely that more may continue to engage in research during their VA tenure. Although this finding shows that an appreciable number of VA podiatrists have published in their field of study, it also encourages departments to provide resources to engage in research. Similar to previous research among foot and ankle surgeons, this analysis also found an increase in publications and h-index as tenure increased.4 Unlike previous research, which found h-index and academic appointment to be contributors to VA dermatologists’ salaries, no significant difference in salary was found in this study associated with publications, h-index, or academic role.15 Although the increase was not statistically significant, salary tended to rise as these variables increased.
Limitations
This analysis was confined to the most recent year of available data, which may not fully capture the longitudinal academic contributions and trends of individual podiatrists. Academic productivity can fluctuate significantly over time due to various factors, including changes in research focus and administrative responsibilities. The study also relied on Scopus to identify and quantify academic productivity. This database may not include all publications relevant to podiatrists, particularly those in niche or nonindexed journals. Additionally, name variations and potential misspellings could lead to missing data for individual podiatrists’ publications. Furthermore, this study did not account for other significant contributors to salary and career advancement within the federal system. Factors such as clinical performance, administrative duties, patient satisfaction, and contributions to teaching and mentoring are critical elements that also influence career progression and compensation but were not captured in this analysis. The retrospective design of this study inherently limits the ability to establish causal relationships. While associations between academic productivity and certain outcomes may be identified, it is not possible to definitively determine the direction or causality of these relationships. Future research may examine how scholarly activity continues once a clinician is part of VA.
CONCLUSIONS
This study highlights the significant academic contributions of VA podiatrists to research and the medical literature. By fostering an active research environment, the VA can ensure veterans receive the highest quality of care from knowledgeable and expert clinicians. Future research should aim to provide a more comprehensive analysis, capturing long-term trends and considering all factors influencing career advancement in VA.
The US Department of Veterans Affairs (VA) delivers care to > 9 million veterans, including primary and specialty care.1 While clinical duties remain important across the health system, proposed productivity models have included clinician research activity, given that many hold roles in academia.2 Within this framework, research plays a pivotal role in advancing clinical practices and outcomes. Studies have found that physicians who participated in research report higher job satisfaction.3
As a specialty within the VA, podiatrists diagnose, treat, and prevent foot and ankle disorders. In addition to clinical practice, various scholarly activities are shared among these physicians.4 Reasons for scholarly pursuits among podiatrists vary, including participation in research for academic promotion or to establish expertise in a given area.4-7 Although research remains a component associated with promotion within the VA, little is known about the scholarly activity of VA podiatrists. Specifically, there remains a paucity of data concerning their expertise, as evidenced through peer-reviewed publications, among these physicians and surgeons. To date, no analysis of scholarly activity among VA podiatrists has been conducted.
The primary aim of this investigation was to describe the scholarly productivity among podiatrists employed by the VA through an analysis of the number of peer-reviewed publications and the respective h-index of each physician. The secondary aim of this investigation was to assess the effect of academic productivity on compensation. This study describes research activities pursued by VA physicians and provides the veteran patient population with the confidence that their foot health care remains in the hands of experts within the field.
MATERIALS AND METHODS
The Feds Data Center (www.fedsdatacenter.com) online database of employees was used to identify VA podiatrists on June 17, 2024. All GS-15 physicians and their respective salaries in fiscal year 2023 were recorded. Administratively determined employees, including residents, were excluded. The h-index and number of published documents from any point during a physician’s training or career were reported for each podiatrist using Scopus; podiatrists without an h-index or publication were excluded. 8 Among podiatrists with scholarly activity, this analysis collected academic appointment, sex, and region of practice.
Statistical Analysis
Descriptive statistics, presented as counts and frequencies, were used. The median and IQR were used to describe the number of publications and h-index due to their nonnormal distribution. A Kruskal-Wallis test was used to compare median publication counts and h-index values among for junior faculty (JF), which includes instructors and assistant professors; senior faculty (SF), which includes associate professors and professors; and those with no academic affiliation (NF). Salary was reported as mean (SD) as it remained normally distributed and was compared using analysis of variance with posthoc Tukey test to increase statistical power. Additionally, this analysis used linear regression to investigate the relationship between scholarly activity and salary. The threshold for statistical significance was set at P < .05.
RESULTS
Among 819 VA podiatrists, 150 were administratively determined and excluded, and 512 were excluded for no history of publications, leaving 157 eligible for analysis (Table). A statistically significant difference was found in median (IQR) publication count by faculty appointment. JF had 6.0 (9.5), SF had 12.5 (22.3), and NF had 1.0 (2.0) publication(s) (P < .001) (Figure 1A). There was a statistically significant difference in h-index by faculty appointment. The median (IQR) h-index for JF was 2.0 (3.5), for SF was 5.5 (4.25), and for NF was 1.0 (2.0) (P = .002) (Figure 1B). Salary was not significantly associated with publication count (P = .20) or h-index (P = .62) (Figure 2). No statistically significant difference was found between academic appointment and mean (SD) salary. JF had a median (IQR) salary of $224,063 (27,989), SF of $234,260 (42,963), and NF of $219,811 (P = .35).

(B) h-index.a
aBox sizes indicate IQR (bottom, IQR 1; top, IQR 3); whiskers indicate minimum and maximum within 1.5 x IQR; Xs indicate means; white
lines indicate medians; and dots indicate outliers.

(B) h-index.a
aBox sizes indicate IQR (bottom, IQR 1; top, IQR 3); whiskers indicate minimum and maximum within 1.5 x IQR; Xs indicate means; white
lines indicate medians; and dots indicate outliers.


DISCUSSION
Focused on providing high-quality care, VA physicians use their expertise to practice comprehensive and specialized care.9,10 A cornerstone to this expertise is scholarly activity that contributes to the body of knowledge and, ultimately, the evidence-based medicine by which these physicians practice.11 With veterans considering VA care, it is important to highlight the commitment and dedication to the science and the practice of medicine. This analysis describes the scholarly activity of VA podiatrists and underscores the expertise veterans will receive for the diagnosis and treatment of their foot and ankle pathology.
were not part of an academic facility, a finding that may encourage further action to increase academic productivity in this specialty. For example, collaboration through academic affiliations has been seen throughout VA medical and surgical specialties and provides many benefits. Beginning with graduate medical education, the VA serves as a tremendous resource for resident training.12 Additionally, veterans who sought emergency care at the VA had a lower risk of death than those treated at non-VA hospitals.13 In podiatric medicine and surgery, scholarly activity has been linked to improved outcomes, particularly in the study of ulceration development and its role in either prolonging or preventing amputation.14
Beyond improving clinical outcomes and patient care, engagement in research and inquiry offers other benefits. A cross-sectional study of 7734 physicians within the VA found that research involvement was associated with more favorable job characteristics and job satisfaction perceptions. 3 While this analysis found that about 19% of podiatrists have published once in their career, it remains likely that more may continue to engage in research during their VA tenure. Although this finding shows that an appreciable number of VA podiatrists have published in their field of study, it also encourages departments to provide resources to engage in research. Similar to previous research among foot and ankle surgeons, this analysis also found an increase in publications and h-index as tenure increased.4 Unlike previous research, which found h-index and academic appointment to be contributors to VA dermatologists’ salaries, no significant difference in salary was found in this study associated with publications, h-index, or academic role.15 Although the increase was not statistically significant, salary tended to rise as these variables increased.
Limitations
This analysis was confined to the most recent year of available data, which may not fully capture the longitudinal academic contributions and trends of individual podiatrists. Academic productivity can fluctuate significantly over time due to various factors, including changes in research focus and administrative responsibilities. The study also relied on Scopus to identify and quantify academic productivity. This database may not include all publications relevant to podiatrists, particularly those in niche or nonindexed journals. Additionally, name variations and potential misspellings could lead to missing data for individual podiatrists’ publications. Furthermore, this study did not account for other significant contributors to salary and career advancement within the federal system. Factors such as clinical performance, administrative duties, patient satisfaction, and contributions to teaching and mentoring are critical elements that also influence career progression and compensation but were not captured in this analysis. The retrospective design of this study inherently limits the ability to establish causal relationships. While associations between academic productivity and certain outcomes may be identified, it is not possible to definitively determine the direction or causality of these relationships. Future research may examine how scholarly activity continues once a clinician is part of VA.
CONCLUSIONS
This study highlights the significant academic contributions of VA podiatrists to research and the medical literature. By fostering an active research environment, the VA can ensure veterans receive the highest quality of care from knowledgeable and expert clinicians. Future research should aim to provide a more comprehensive analysis, capturing long-term trends and considering all factors influencing career advancement in VA.
- Rosland AM, Nelson K, Sun H, et al. The patient-centered medical home in the Veterans Health Administration. Am J Manag Care. 2013;19(7):e263-e272.
- Coleman DL, Moran E, Serfilippi D, et al. Measuring physicians’ productivity in a Veterans’ Affairs Medical Center. Acad Med. 2003;78(7):682-689. doi:10.1097/00001888-200307000-00007
- Mohr DC, Burgess JF Jr. Job characteristics and job satisfaction among physicians involved with research in the Veterans Health Administration. Acad Med. 2011;86(8):938-945. doi:10.1097/ACM.0b013e3182223b76
- Casciato DJ, Cravey KS, Barron IM. Scholarly productivity among academic foot and ankle surgeons affiliated with US podiatric medicine and surgery residency and fellowship training programs. J Foot Ankle Surg. 2021;60(6):1222-1226. doi:10.1053/j.jfas.2021.04.017
- Hyer CF, Casciato DJ, Rushing CJ, Schuberth JM. Incidence of scholarly publication by selected content experts presenting at national society foot and ankle meetings from 2016 to 2020. J Foot Ankle Surg. 2022;61(6):1317-1320. doi:10.1053/j.jfas.2022.04.011
- Casciato DJ, Thompson J, Yancovitz S, Chandra A, Prissel MA, Hyer CF. Research activity among foot and ankle surgery fellows: a systematic review. J Foot Ankle Surg. 2021;60(6):1227-1231. doi:10.1053/j.jfas.2021.04.018
- Casciato DJ, Thompson J, Hyer CF. Post-fellowship foot and ankle surgeon research productivity: a systematic review. J Foot Ankle Surg. 2022;61(4):896-899. doi:10.1053/j.jfas.2021.12.028
- Hirsch JE. An index to quantify an individual’s scientific research output. Proc Natl Acad Sci USA. 2005;102(46):16569-16572. doi:10.1073/pnas.0507655102
- US Department of Veterans Affairs. Veterans Health Administration. About VHA. Updated January 20, 2025. Accessed February 17, 2025. https://www.va.gov/health/aboutvha.asp
- US Department of Veterans Affairs. VHA National Center for Patient Safety. About Us. Updated November 29, 2023. Accessed February 17, 2025. https://www.patientsafety.va.gov/
- US Department of Veterans Affairs. VA/DoD Clinical Practice Guidelines. Updated February 7, 2025. Accessed February 17, 2025. https://www.healthquality.va.gov
- Ravin AG, Gottlieb NB, Wang HT, et al. Effect of the Veterans Affairs Medical System on plastic surgery residency training. Plast Reconstr Surg. 2006;117(2):656-660. doi:10.1097/01.prs.0000197216.95544.f7
- Chan DC, Danesh K, Costantini S, Card D, Taylor L, Studdert DM. Mortality among US veterans after emergency visits to Veterans Affairs and other hospitals: retrospective cohort study. BMJ. 2022;376:e068099. doi:10.1136/bmj-2021-068099
- Gibson LW, Abbas A. Limb salvage for veterans with diabetes: to care for him who has borne the battle. Crit Care Nurs Clin North Am. 2013;25(1):131-134. doi:10.1016/j.ccell.2012.11.004
- Do MH, Lipner SR. Contribution of gender on compensation of Veterans Affairs-affiliated dermatologists: a cross-sectional study. Int J Womens Dermatol. 2020;6(5):414-418. doi:10.1016/j.ijwd.2020.09.009
- Rosland AM, Nelson K, Sun H, et al. The patient-centered medical home in the Veterans Health Administration. Am J Manag Care. 2013;19(7):e263-e272.
- Coleman DL, Moran E, Serfilippi D, et al. Measuring physicians’ productivity in a Veterans’ Affairs Medical Center. Acad Med. 2003;78(7):682-689. doi:10.1097/00001888-200307000-00007
- Mohr DC, Burgess JF Jr. Job characteristics and job satisfaction among physicians involved with research in the Veterans Health Administration. Acad Med. 2011;86(8):938-945. doi:10.1097/ACM.0b013e3182223b76
- Casciato DJ, Cravey KS, Barron IM. Scholarly productivity among academic foot and ankle surgeons affiliated with US podiatric medicine and surgery residency and fellowship training programs. J Foot Ankle Surg. 2021;60(6):1222-1226. doi:10.1053/j.jfas.2021.04.017
- Hyer CF, Casciato DJ, Rushing CJ, Schuberth JM. Incidence of scholarly publication by selected content experts presenting at national society foot and ankle meetings from 2016 to 2020. J Foot Ankle Surg. 2022;61(6):1317-1320. doi:10.1053/j.jfas.2022.04.011
- Casciato DJ, Thompson J, Yancovitz S, Chandra A, Prissel MA, Hyer CF. Research activity among foot and ankle surgery fellows: a systematic review. J Foot Ankle Surg. 2021;60(6):1227-1231. doi:10.1053/j.jfas.2021.04.018
- Casciato DJ, Thompson J, Hyer CF. Post-fellowship foot and ankle surgeon research productivity: a systematic review. J Foot Ankle Surg. 2022;61(4):896-899. doi:10.1053/j.jfas.2021.12.028
- Hirsch JE. An index to quantify an individual’s scientific research output. Proc Natl Acad Sci USA. 2005;102(46):16569-16572. doi:10.1073/pnas.0507655102
- US Department of Veterans Affairs. Veterans Health Administration. About VHA. Updated January 20, 2025. Accessed February 17, 2025. https://www.va.gov/health/aboutvha.asp
- US Department of Veterans Affairs. VHA National Center for Patient Safety. About Us. Updated November 29, 2023. Accessed February 17, 2025. https://www.patientsafety.va.gov/
- US Department of Veterans Affairs. VA/DoD Clinical Practice Guidelines. Updated February 7, 2025. Accessed February 17, 2025. https://www.healthquality.va.gov
- Ravin AG, Gottlieb NB, Wang HT, et al. Effect of the Veterans Affairs Medical System on plastic surgery residency training. Plast Reconstr Surg. 2006;117(2):656-660. doi:10.1097/01.prs.0000197216.95544.f7
- Chan DC, Danesh K, Costantini S, Card D, Taylor L, Studdert DM. Mortality among US veterans after emergency visits to Veterans Affairs and other hospitals: retrospective cohort study. BMJ. 2022;376:e068099. doi:10.1136/bmj-2021-068099
- Gibson LW, Abbas A. Limb salvage for veterans with diabetes: to care for him who has borne the battle. Crit Care Nurs Clin North Am. 2013;25(1):131-134. doi:10.1016/j.ccell.2012.11.004
- Do MH, Lipner SR. Contribution of gender on compensation of Veterans Affairs-affiliated dermatologists: a cross-sectional study. Int J Womens Dermatol. 2020;6(5):414-418. doi:10.1016/j.ijwd.2020.09.009
Scholarly Activity Among VA Podiatrists: A Cross-Sectional Study
Scholarly Activity Among VA Podiatrists: A Cross-Sectional Study
Stretcher vs Table for Operative Hand Surgery
Stretcher vs Table for Operative Hand Surgery
US Department of Veterans Affairs (VA) health care facilities have not recovered from staff shortages that occurred during the COVID-19 pandemic.1 Veterans Health Administration operating rooms (ORs) lost many valuable clinicians during the pandemic due to illness, relocation, burnout, and retirement, and remain below prepandemic levels. The staffing shortage has resulted in lost OR time, leading to longer wait times for surgery. In October 2021, the Malcom Randall VA Medical Center (MRVAMC) Plastic Surgery Service implemented a surgery-on-stretcher initiative, in which patients arriving in the OR remained on the stretcher throughout surgery rather than being transferred to the operating table. Avoiding patient transfers was identified as a strategy to increase the number of procedures performed while providing additional benefits to the patients and staff.
The intent of the surgery-on-stretcher initiative was to reduce OR turnover time and in-room time, decrease supply costs, and improve patient and staff safety. The objective of this study was to evaluate the new process in terms of time efficiency, cost savings, and safety.
METHODS
The University of Florida Institutional Review Board (IRB) and North Florida/South Georgia Veterans Health System Research and Development Committee (IRB.net) approved a retrospective chart review of hand surgery cases performed in the same OR by the same surgeon over 2 year-long periods: October 1, 2020, through September 30, 2021, when surgeries were performed on the operating table (Figure 1), and June 1, 2022, through May 31, 2023, when surgeries were performed on the stretcher (Figure 2). Time intervals were obtained from the Nurse Intraoperative Report found in the electronic medical record. They ranged from “patient in OR” to “operation begin,” “operation end” to “patient out OR,” and “patient out OR” to next “patient in OR.” The median time intervals were obtained for the 3 different time intervals in each study period and compared.


A Mann-Whitney U test was used to determine statistical significance between the groups. We queried the Patient Safety Manager (Jason Ringlehan, BSN, RN, oral communication, 2023) and the Employee Health Nurse (Ivan Cool, BSN, RN, oral communication, June 16, 2023) for reported patient or employee–patient transfer injuries. We requested Inventory Supply personnel to provide the cost of materials used in the transfer process. There was no cost for surgeries performed on the stretcher.
RESULTS
A total of 306 hand surgeries were performed on a table and 191 were performed on a stretcher during the study periods. The median patient in OR to operation begin time interval was 25 minutes for the table and 23 minutes for the stretcher. The median operation end to patient out OR time was 4 minutes for the table and 3 minutes for the stretcher. Time savings was statistically significant (P < .001) for both ends of the surgery. The median room turnover time was 27 minutes for both time periods and was not statistically significant (P = .70). There were no reported employee or patient injuries attributed to OR transfers during either time period. Supply cost savings was $111.28 per case when surgery was performed on the stretcher (Table).

DISCUSSION
The new process of doing surgery on the stretcher was introduced to improve OR time efficiency. This improved efficiency has been reported in the hand surgery literature; however, the authors anticipated resistance to implementing a new process to seasoned OR staff.2,3 Once the idea was conceived, the plan was reviewed with the Anesthesia Service to confirm they had no safety concerns. The rest of the OR staff, including nurses and surgical technicians, agreed to participate. No resistance was encountered. The anesthesia, nursing, and scrub staff were happy to skip a potentially hazardous step at the beginning and end of each hand surgery case. The anesthesiologists communicated that the OR bed is preferred for intubating, but our hand surgeries are performed under local or regional block and intravenous sedation. The table was removed from the room to avoid any confusion with changes in staff during the day.
Compared with table use, surgery on the stretcher saved a median of 3 minutes of in-room time per case, with no significant difference in turnover time. The time savings reported here were consistent with what has been reported in other studies. Garras et al saved 7.5 minutes per case using a rolling hand table for their hand surgeries,2 while Gonzalez et al reported a 4-minute reduction per case when using a stretcher-based hand table for carpal tunnel and trigger finger surgeries.3 Lause et al found a 2-minute time savings at the start of their foot and ankle surgeries.4
Although 3 minutes per case may seem minimal, when applied to a conservative number of 5 hand cases twice a week, this time savings translates to an additional 15-minute nursing break each day, a 30-minute lunch break each week, and 26 extra hours each year. This efficiency can reduce direct costs in overtime. Consistently ending the day on time and allowing time for scheduled breaks can facilitate retention and improve morale in our current environment of chronically short-staffed surgical services. Recent literature estimates the cost of 1 OR minute to be about $36 to $46.5,6
Lateral transfers, in which a patient is moved horizontally, take place throughout the day in the OR and are a known risk factor for musculoskeletal disorders among the nursing staff. Contributing factors include patient obesity, environmental barriers in the OR, uneven patient weight distribution, and height differences among surgical team members. The Association of periOperative Registered Nurses recommends use of a lateral transfer device such as a friction-reducing sheet, slider board, or air-assisted device.7 The single-use Hover- Sling Repositioning Sheet is the transfer assist device used in our OR. It is an inflatable transfer mattress that reduces the amount of force used in patient transfer. The mattress is inflated with air from a small motor. While the HoverSling is inflated, escaping air from little holes on the underside of the mattress acts as a lubricant between the patient and transfer surface. This air reduces the force needed to move the patient.8
Patient transfers are a known risk for both patient and staff injuries.9,10 We suspected that not transferring our surgical patients between the stretcher and bed would improve patient and staff safety. A review of Patient Safety and Employee Health services found no reported patient or staff injuries during either timeframe. This finding led to the conclusion that effective safety precautions were already in place before the surgery-on-stretcher initiative. The MRVAMC routinely uses patient transfer equipment and the standard procedure in the OR is for 5 people to participate in 1 patient transfer between bed and table. The patient transfer device plus multiple staff involvement with patient transfers could explain the lack of patient and staff injury that predated the surgery-on-stretcher initiative and continued throughout the study period.
The inventory required to facilitate patient transfers at MRVAMC cost on average $111.28 per patient based on a search of the inventory database. This amount includes the HoverSling priced at $97 and the Medline OR Turnover Kit (table sheet, draw sheet, arm board covers, head positioning cover, and positioning foam strap) priced at $14.28. The Plastic Surgery Service routinely performs a minimum of 10 hand cases per week. If $111.28 per case is multiplied by the average of 10 cases each week over 52 weeks, the annualized savings could be about $57,866. This direct cost savings can potentially be applied to necessary equipment expenditures, educational training, or staff salaries.
Hand surgery literature has encouraged initiatives to reduce waste and develop more environmentally responsible practices.11-13 Eliminating the single-use patient transfer device and the turnover kit would avoid generating additional trash from the OR. Fewer sheets would have to be washed when patients stay on the same stretcher throughout their surgery day, which saves electricity and water.
Strengths and Limitations
A strength of this study is the consistency of the data, which were obtained from observing the same surgeon performing the same surgeries in the same OR. The data were logged into the electronic medical record in real time and easily accessible for data collection and comparison when reviewed retrospectively. A weakness of the study is the inconsistency in logging the in/out and start/ end times by the OR circulating nurses who were involved in the patient transfers. The OR circulating nurses can vary from day to day, depending on the staffing assignments, which could affect the speed of each part of the procedure.
CONCLUSIONS
Hand surgery performed on the stretcher saves OR time and supply costs. This added efficiency translates to a savings of 26 hours of OR time and $57,866 in supply costs over the course of a year. Turnover time and staff and patient safety were not affected. This process can be introduced to other surgical specialties that do not need the accessories or various positions the OR table allows.
- Hersey LF. COVID-19 worsened staff shortages at veterans’ medical facilities, IG report finds. Stars and Stripes. October 13, 2023. Accessed February 28, 2025. https:// www.stripes.com/theaters/us/2023-10-13/veterans-affairs-health-care-staff-shortages-11695546.html
- Garras DN, Beredjiklian PK, Leinberry CF Jr. Operating on a stretcher: a cost analysis. J Hand Surg Am. 2011;36(12):2078-2079. doi:10.1016/j.jhsa.2011.09.006
- Gonzalez TA, Stanbury SJ, Mora AN, Floyd WE IV, Blazar PE, Earp BE. The effect of stretcher-based hand tables on operating room efficiency at an outpatient surgery center. Orthop J Harv Med Sch. 2017;18:20-24.
- Lause GE, Parker EB, Farid A, et al. Efficiency and perceived safety of foot and ankle procedures performed on the preoperative stretcher versus operating room table. J Perioper Pract. 2024;34(9):268-273. doi:10.1177/17504589231215939
- Childers CP, Maggard-Gibbons M. Understanding costs of care in the operating room. JAMA Surg. 2018;153(4):e176233. doi:10.1001/jamasurg.2017.6233
- Smith TS, Evans J, Moriel K, et al. Cost of operating room time is $46.04 dollars per minute. J Orthop Bus. 2022;2(4):10-13. doi:10.55576/job.v2i4.23
- Waters T, Baptiste A, Short M, Plante-Mallon L, Nelson A. AORN ergonomic tool 1: lateral transfer of a patient from a stretcher to an OR bed. AORN J. 2011;93(3):334-339. doi:10.1016/j.aorn.2010.08.025
- Barry J. The HoverMatt system for patient transfer: enhancing productivity, efficiency, and safety. J Nurs Adm. 2006;36(3):114-117. doi:10.1097/00005110-200603000-00003
- Apple B, Letvak S. Ergonomic challenges in the perioperative setting. AORN J. 2021;113(4):339-348. doi:10.1002/aorn.13345
- Tan J, Krishnan S, Vacanti JC, et al. Patient falls in the operating room setting: an analysis of reported safety events. J Healthc Risk Manag. 2022;42(1):9-14. doi:10.1002/jhrm.21503
- Van Demark RE Jr, Smith VJS, Fiegen A. Lean and green hand surgery. J Hand Surg Am. 2018;43(2):179-181. doi:10.1016/j.jhsa.2017.11.007
- Bravo D, Gaston RG, Melamed E. Environmentally responsible hand surgery: past, present, and future. J Hand Surg Am. 2020;45(5):444-448. doi:10.1016/j.jhsa.2019.10.031
- Tevlin R, Panton JA, Fox PM. Greening hand surgery: targeted measures to reduce waste in ambulatory trigger finger and carpal tunnel decompression. Hand (N Y). 2023;15589447231220412. doi:10.1177/15589447231220412
US Department of Veterans Affairs (VA) health care facilities have not recovered from staff shortages that occurred during the COVID-19 pandemic.1 Veterans Health Administration operating rooms (ORs) lost many valuable clinicians during the pandemic due to illness, relocation, burnout, and retirement, and remain below prepandemic levels. The staffing shortage has resulted in lost OR time, leading to longer wait times for surgery. In October 2021, the Malcom Randall VA Medical Center (MRVAMC) Plastic Surgery Service implemented a surgery-on-stretcher initiative, in which patients arriving in the OR remained on the stretcher throughout surgery rather than being transferred to the operating table. Avoiding patient transfers was identified as a strategy to increase the number of procedures performed while providing additional benefits to the patients and staff.
The intent of the surgery-on-stretcher initiative was to reduce OR turnover time and in-room time, decrease supply costs, and improve patient and staff safety. The objective of this study was to evaluate the new process in terms of time efficiency, cost savings, and safety.
METHODS
The University of Florida Institutional Review Board (IRB) and North Florida/South Georgia Veterans Health System Research and Development Committee (IRB.net) approved a retrospective chart review of hand surgery cases performed in the same OR by the same surgeon over 2 year-long periods: October 1, 2020, through September 30, 2021, when surgeries were performed on the operating table (Figure 1), and June 1, 2022, through May 31, 2023, when surgeries were performed on the stretcher (Figure 2). Time intervals were obtained from the Nurse Intraoperative Report found in the electronic medical record. They ranged from “patient in OR” to “operation begin,” “operation end” to “patient out OR,” and “patient out OR” to next “patient in OR.” The median time intervals were obtained for the 3 different time intervals in each study period and compared.


A Mann-Whitney U test was used to determine statistical significance between the groups. We queried the Patient Safety Manager (Jason Ringlehan, BSN, RN, oral communication, 2023) and the Employee Health Nurse (Ivan Cool, BSN, RN, oral communication, June 16, 2023) for reported patient or employee–patient transfer injuries. We requested Inventory Supply personnel to provide the cost of materials used in the transfer process. There was no cost for surgeries performed on the stretcher.
RESULTS
A total of 306 hand surgeries were performed on a table and 191 were performed on a stretcher during the study periods. The median patient in OR to operation begin time interval was 25 minutes for the table and 23 minutes for the stretcher. The median operation end to patient out OR time was 4 minutes for the table and 3 minutes for the stretcher. Time savings was statistically significant (P < .001) for both ends of the surgery. The median room turnover time was 27 minutes for both time periods and was not statistically significant (P = .70). There were no reported employee or patient injuries attributed to OR transfers during either time period. Supply cost savings was $111.28 per case when surgery was performed on the stretcher (Table).

DISCUSSION
The new process of doing surgery on the stretcher was introduced to improve OR time efficiency. This improved efficiency has been reported in the hand surgery literature; however, the authors anticipated resistance to implementing a new process to seasoned OR staff.2,3 Once the idea was conceived, the plan was reviewed with the Anesthesia Service to confirm they had no safety concerns. The rest of the OR staff, including nurses and surgical technicians, agreed to participate. No resistance was encountered. The anesthesia, nursing, and scrub staff were happy to skip a potentially hazardous step at the beginning and end of each hand surgery case. The anesthesiologists communicated that the OR bed is preferred for intubating, but our hand surgeries are performed under local or regional block and intravenous sedation. The table was removed from the room to avoid any confusion with changes in staff during the day.
Compared with table use, surgery on the stretcher saved a median of 3 minutes of in-room time per case, with no significant difference in turnover time. The time savings reported here were consistent with what has been reported in other studies. Garras et al saved 7.5 minutes per case using a rolling hand table for their hand surgeries,2 while Gonzalez et al reported a 4-minute reduction per case when using a stretcher-based hand table for carpal tunnel and trigger finger surgeries.3 Lause et al found a 2-minute time savings at the start of their foot and ankle surgeries.4
Although 3 minutes per case may seem minimal, when applied to a conservative number of 5 hand cases twice a week, this time savings translates to an additional 15-minute nursing break each day, a 30-minute lunch break each week, and 26 extra hours each year. This efficiency can reduce direct costs in overtime. Consistently ending the day on time and allowing time for scheduled breaks can facilitate retention and improve morale in our current environment of chronically short-staffed surgical services. Recent literature estimates the cost of 1 OR minute to be about $36 to $46.5,6
Lateral transfers, in which a patient is moved horizontally, take place throughout the day in the OR and are a known risk factor for musculoskeletal disorders among the nursing staff. Contributing factors include patient obesity, environmental barriers in the OR, uneven patient weight distribution, and height differences among surgical team members. The Association of periOperative Registered Nurses recommends use of a lateral transfer device such as a friction-reducing sheet, slider board, or air-assisted device.7 The single-use Hover- Sling Repositioning Sheet is the transfer assist device used in our OR. It is an inflatable transfer mattress that reduces the amount of force used in patient transfer. The mattress is inflated with air from a small motor. While the HoverSling is inflated, escaping air from little holes on the underside of the mattress acts as a lubricant between the patient and transfer surface. This air reduces the force needed to move the patient.8
Patient transfers are a known risk for both patient and staff injuries.9,10 We suspected that not transferring our surgical patients between the stretcher and bed would improve patient and staff safety. A review of Patient Safety and Employee Health services found no reported patient or staff injuries during either timeframe. This finding led to the conclusion that effective safety precautions were already in place before the surgery-on-stretcher initiative. The MRVAMC routinely uses patient transfer equipment and the standard procedure in the OR is for 5 people to participate in 1 patient transfer between bed and table. The patient transfer device plus multiple staff involvement with patient transfers could explain the lack of patient and staff injury that predated the surgery-on-stretcher initiative and continued throughout the study period.
The inventory required to facilitate patient transfers at MRVAMC cost on average $111.28 per patient based on a search of the inventory database. This amount includes the HoverSling priced at $97 and the Medline OR Turnover Kit (table sheet, draw sheet, arm board covers, head positioning cover, and positioning foam strap) priced at $14.28. The Plastic Surgery Service routinely performs a minimum of 10 hand cases per week. If $111.28 per case is multiplied by the average of 10 cases each week over 52 weeks, the annualized savings could be about $57,866. This direct cost savings can potentially be applied to necessary equipment expenditures, educational training, or staff salaries.
Hand surgery literature has encouraged initiatives to reduce waste and develop more environmentally responsible practices.11-13 Eliminating the single-use patient transfer device and the turnover kit would avoid generating additional trash from the OR. Fewer sheets would have to be washed when patients stay on the same stretcher throughout their surgery day, which saves electricity and water.
Strengths and Limitations
A strength of this study is the consistency of the data, which were obtained from observing the same surgeon performing the same surgeries in the same OR. The data were logged into the electronic medical record in real time and easily accessible for data collection and comparison when reviewed retrospectively. A weakness of the study is the inconsistency in logging the in/out and start/ end times by the OR circulating nurses who were involved in the patient transfers. The OR circulating nurses can vary from day to day, depending on the staffing assignments, which could affect the speed of each part of the procedure.
CONCLUSIONS
Hand surgery performed on the stretcher saves OR time and supply costs. This added efficiency translates to a savings of 26 hours of OR time and $57,866 in supply costs over the course of a year. Turnover time and staff and patient safety were not affected. This process can be introduced to other surgical specialties that do not need the accessories or various positions the OR table allows.
US Department of Veterans Affairs (VA) health care facilities have not recovered from staff shortages that occurred during the COVID-19 pandemic.1 Veterans Health Administration operating rooms (ORs) lost many valuable clinicians during the pandemic due to illness, relocation, burnout, and retirement, and remain below prepandemic levels. The staffing shortage has resulted in lost OR time, leading to longer wait times for surgery. In October 2021, the Malcom Randall VA Medical Center (MRVAMC) Plastic Surgery Service implemented a surgery-on-stretcher initiative, in which patients arriving in the OR remained on the stretcher throughout surgery rather than being transferred to the operating table. Avoiding patient transfers was identified as a strategy to increase the number of procedures performed while providing additional benefits to the patients and staff.
The intent of the surgery-on-stretcher initiative was to reduce OR turnover time and in-room time, decrease supply costs, and improve patient and staff safety. The objective of this study was to evaluate the new process in terms of time efficiency, cost savings, and safety.
METHODS
The University of Florida Institutional Review Board (IRB) and North Florida/South Georgia Veterans Health System Research and Development Committee (IRB.net) approved a retrospective chart review of hand surgery cases performed in the same OR by the same surgeon over 2 year-long periods: October 1, 2020, through September 30, 2021, when surgeries were performed on the operating table (Figure 1), and June 1, 2022, through May 31, 2023, when surgeries were performed on the stretcher (Figure 2). Time intervals were obtained from the Nurse Intraoperative Report found in the electronic medical record. They ranged from “patient in OR” to “operation begin,” “operation end” to “patient out OR,” and “patient out OR” to next “patient in OR.” The median time intervals were obtained for the 3 different time intervals in each study period and compared.


A Mann-Whitney U test was used to determine statistical significance between the groups. We queried the Patient Safety Manager (Jason Ringlehan, BSN, RN, oral communication, 2023) and the Employee Health Nurse (Ivan Cool, BSN, RN, oral communication, June 16, 2023) for reported patient or employee–patient transfer injuries. We requested Inventory Supply personnel to provide the cost of materials used in the transfer process. There was no cost for surgeries performed on the stretcher.
RESULTS
A total of 306 hand surgeries were performed on a table and 191 were performed on a stretcher during the study periods. The median patient in OR to operation begin time interval was 25 minutes for the table and 23 minutes for the stretcher. The median operation end to patient out OR time was 4 minutes for the table and 3 minutes for the stretcher. Time savings was statistically significant (P < .001) for both ends of the surgery. The median room turnover time was 27 minutes for both time periods and was not statistically significant (P = .70). There were no reported employee or patient injuries attributed to OR transfers during either time period. Supply cost savings was $111.28 per case when surgery was performed on the stretcher (Table).

DISCUSSION
The new process of doing surgery on the stretcher was introduced to improve OR time efficiency. This improved efficiency has been reported in the hand surgery literature; however, the authors anticipated resistance to implementing a new process to seasoned OR staff.2,3 Once the idea was conceived, the plan was reviewed with the Anesthesia Service to confirm they had no safety concerns. The rest of the OR staff, including nurses and surgical technicians, agreed to participate. No resistance was encountered. The anesthesia, nursing, and scrub staff were happy to skip a potentially hazardous step at the beginning and end of each hand surgery case. The anesthesiologists communicated that the OR bed is preferred for intubating, but our hand surgeries are performed under local or regional block and intravenous sedation. The table was removed from the room to avoid any confusion with changes in staff during the day.
Compared with table use, surgery on the stretcher saved a median of 3 minutes of in-room time per case, with no significant difference in turnover time. The time savings reported here were consistent with what has been reported in other studies. Garras et al saved 7.5 minutes per case using a rolling hand table for their hand surgeries,2 while Gonzalez et al reported a 4-minute reduction per case when using a stretcher-based hand table for carpal tunnel and trigger finger surgeries.3 Lause et al found a 2-minute time savings at the start of their foot and ankle surgeries.4
Although 3 minutes per case may seem minimal, when applied to a conservative number of 5 hand cases twice a week, this time savings translates to an additional 15-minute nursing break each day, a 30-minute lunch break each week, and 26 extra hours each year. This efficiency can reduce direct costs in overtime. Consistently ending the day on time and allowing time for scheduled breaks can facilitate retention and improve morale in our current environment of chronically short-staffed surgical services. Recent literature estimates the cost of 1 OR minute to be about $36 to $46.5,6
Lateral transfers, in which a patient is moved horizontally, take place throughout the day in the OR and are a known risk factor for musculoskeletal disorders among the nursing staff. Contributing factors include patient obesity, environmental barriers in the OR, uneven patient weight distribution, and height differences among surgical team members. The Association of periOperative Registered Nurses recommends use of a lateral transfer device such as a friction-reducing sheet, slider board, or air-assisted device.7 The single-use Hover- Sling Repositioning Sheet is the transfer assist device used in our OR. It is an inflatable transfer mattress that reduces the amount of force used in patient transfer. The mattress is inflated with air from a small motor. While the HoverSling is inflated, escaping air from little holes on the underside of the mattress acts as a lubricant between the patient and transfer surface. This air reduces the force needed to move the patient.8
Patient transfers are a known risk for both patient and staff injuries.9,10 We suspected that not transferring our surgical patients between the stretcher and bed would improve patient and staff safety. A review of Patient Safety and Employee Health services found no reported patient or staff injuries during either timeframe. This finding led to the conclusion that effective safety precautions were already in place before the surgery-on-stretcher initiative. The MRVAMC routinely uses patient transfer equipment and the standard procedure in the OR is for 5 people to participate in 1 patient transfer between bed and table. The patient transfer device plus multiple staff involvement with patient transfers could explain the lack of patient and staff injury that predated the surgery-on-stretcher initiative and continued throughout the study period.
The inventory required to facilitate patient transfers at MRVAMC cost on average $111.28 per patient based on a search of the inventory database. This amount includes the HoverSling priced at $97 and the Medline OR Turnover Kit (table sheet, draw sheet, arm board covers, head positioning cover, and positioning foam strap) priced at $14.28. The Plastic Surgery Service routinely performs a minimum of 10 hand cases per week. If $111.28 per case is multiplied by the average of 10 cases each week over 52 weeks, the annualized savings could be about $57,866. This direct cost savings can potentially be applied to necessary equipment expenditures, educational training, or staff salaries.
Hand surgery literature has encouraged initiatives to reduce waste and develop more environmentally responsible practices.11-13 Eliminating the single-use patient transfer device and the turnover kit would avoid generating additional trash from the OR. Fewer sheets would have to be washed when patients stay on the same stretcher throughout their surgery day, which saves electricity and water.
Strengths and Limitations
A strength of this study is the consistency of the data, which were obtained from observing the same surgeon performing the same surgeries in the same OR. The data were logged into the electronic medical record in real time and easily accessible for data collection and comparison when reviewed retrospectively. A weakness of the study is the inconsistency in logging the in/out and start/ end times by the OR circulating nurses who were involved in the patient transfers. The OR circulating nurses can vary from day to day, depending on the staffing assignments, which could affect the speed of each part of the procedure.
CONCLUSIONS
Hand surgery performed on the stretcher saves OR time and supply costs. This added efficiency translates to a savings of 26 hours of OR time and $57,866 in supply costs over the course of a year. Turnover time and staff and patient safety were not affected. This process can be introduced to other surgical specialties that do not need the accessories or various positions the OR table allows.
- Hersey LF. COVID-19 worsened staff shortages at veterans’ medical facilities, IG report finds. Stars and Stripes. October 13, 2023. Accessed February 28, 2025. https:// www.stripes.com/theaters/us/2023-10-13/veterans-affairs-health-care-staff-shortages-11695546.html
- Garras DN, Beredjiklian PK, Leinberry CF Jr. Operating on a stretcher: a cost analysis. J Hand Surg Am. 2011;36(12):2078-2079. doi:10.1016/j.jhsa.2011.09.006
- Gonzalez TA, Stanbury SJ, Mora AN, Floyd WE IV, Blazar PE, Earp BE. The effect of stretcher-based hand tables on operating room efficiency at an outpatient surgery center. Orthop J Harv Med Sch. 2017;18:20-24.
- Lause GE, Parker EB, Farid A, et al. Efficiency and perceived safety of foot and ankle procedures performed on the preoperative stretcher versus operating room table. J Perioper Pract. 2024;34(9):268-273. doi:10.1177/17504589231215939
- Childers CP, Maggard-Gibbons M. Understanding costs of care in the operating room. JAMA Surg. 2018;153(4):e176233. doi:10.1001/jamasurg.2017.6233
- Smith TS, Evans J, Moriel K, et al. Cost of operating room time is $46.04 dollars per minute. J Orthop Bus. 2022;2(4):10-13. doi:10.55576/job.v2i4.23
- Waters T, Baptiste A, Short M, Plante-Mallon L, Nelson A. AORN ergonomic tool 1: lateral transfer of a patient from a stretcher to an OR bed. AORN J. 2011;93(3):334-339. doi:10.1016/j.aorn.2010.08.025
- Barry J. The HoverMatt system for patient transfer: enhancing productivity, efficiency, and safety. J Nurs Adm. 2006;36(3):114-117. doi:10.1097/00005110-200603000-00003
- Apple B, Letvak S. Ergonomic challenges in the perioperative setting. AORN J. 2021;113(4):339-348. doi:10.1002/aorn.13345
- Tan J, Krishnan S, Vacanti JC, et al. Patient falls in the operating room setting: an analysis of reported safety events. J Healthc Risk Manag. 2022;42(1):9-14. doi:10.1002/jhrm.21503
- Van Demark RE Jr, Smith VJS, Fiegen A. Lean and green hand surgery. J Hand Surg Am. 2018;43(2):179-181. doi:10.1016/j.jhsa.2017.11.007
- Bravo D, Gaston RG, Melamed E. Environmentally responsible hand surgery: past, present, and future. J Hand Surg Am. 2020;45(5):444-448. doi:10.1016/j.jhsa.2019.10.031
- Tevlin R, Panton JA, Fox PM. Greening hand surgery: targeted measures to reduce waste in ambulatory trigger finger and carpal tunnel decompression. Hand (N Y). 2023;15589447231220412. doi:10.1177/15589447231220412
- Hersey LF. COVID-19 worsened staff shortages at veterans’ medical facilities, IG report finds. Stars and Stripes. October 13, 2023. Accessed February 28, 2025. https:// www.stripes.com/theaters/us/2023-10-13/veterans-affairs-health-care-staff-shortages-11695546.html
- Garras DN, Beredjiklian PK, Leinberry CF Jr. Operating on a stretcher: a cost analysis. J Hand Surg Am. 2011;36(12):2078-2079. doi:10.1016/j.jhsa.2011.09.006
- Gonzalez TA, Stanbury SJ, Mora AN, Floyd WE IV, Blazar PE, Earp BE. The effect of stretcher-based hand tables on operating room efficiency at an outpatient surgery center. Orthop J Harv Med Sch. 2017;18:20-24.
- Lause GE, Parker EB, Farid A, et al. Efficiency and perceived safety of foot and ankle procedures performed on the preoperative stretcher versus operating room table. J Perioper Pract. 2024;34(9):268-273. doi:10.1177/17504589231215939
- Childers CP, Maggard-Gibbons M. Understanding costs of care in the operating room. JAMA Surg. 2018;153(4):e176233. doi:10.1001/jamasurg.2017.6233
- Smith TS, Evans J, Moriel K, et al. Cost of operating room time is $46.04 dollars per minute. J Orthop Bus. 2022;2(4):10-13. doi:10.55576/job.v2i4.23
- Waters T, Baptiste A, Short M, Plante-Mallon L, Nelson A. AORN ergonomic tool 1: lateral transfer of a patient from a stretcher to an OR bed. AORN J. 2011;93(3):334-339. doi:10.1016/j.aorn.2010.08.025
- Barry J. The HoverMatt system for patient transfer: enhancing productivity, efficiency, and safety. J Nurs Adm. 2006;36(3):114-117. doi:10.1097/00005110-200603000-00003
- Apple B, Letvak S. Ergonomic challenges in the perioperative setting. AORN J. 2021;113(4):339-348. doi:10.1002/aorn.13345
- Tan J, Krishnan S, Vacanti JC, et al. Patient falls in the operating room setting: an analysis of reported safety events. J Healthc Risk Manag. 2022;42(1):9-14. doi:10.1002/jhrm.21503
- Van Demark RE Jr, Smith VJS, Fiegen A. Lean and green hand surgery. J Hand Surg Am. 2018;43(2):179-181. doi:10.1016/j.jhsa.2017.11.007
- Bravo D, Gaston RG, Melamed E. Environmentally responsible hand surgery: past, present, and future. J Hand Surg Am. 2020;45(5):444-448. doi:10.1016/j.jhsa.2019.10.031
- Tevlin R, Panton JA, Fox PM. Greening hand surgery: targeted measures to reduce waste in ambulatory trigger finger and carpal tunnel decompression. Hand (N Y). 2023;15589447231220412. doi:10.1177/15589447231220412
Stretcher vs Table for Operative Hand Surgery
Stretcher vs Table for Operative Hand Surgery
Implications of Thyroid Disease in Hospitalized Patients With Hidradenitis Suppurativa
Implications of Thyroid Disease in Hospitalized Patients With Hidradenitis Suppurativa
To the Editor:
Hidradenitis suppurativa (HS) is a chronic inflammatory skin condition characterized by painful recurrent abscesses. Several autoimmune and endocrine diseases are associated with HS, including inflammatory bowel disease and diabetes mellitus (DM).1 Notably, the association between HS and thyroid disorders is poorly characterized,2 and there are no known nationwide studies exploring this potential association in the hospital setting. In this cross-sectional matched cohort study, we aimed to characterize HS patients with comorbid thyroid disorders as well as to explore whether thyroid disease is associated with comorbidities and hospital outcome measures in these patients.
The 2019 National Inpatient Sample (NIS) was weighted in accordance with NIS-assigned weight variables and queried for HS, hypothyroidism, and hyperthyroidism cases using International Classification of Diseases, Tenth Revision, codes L73.2, E03, and E05, respectively. Propensity score matching based on age and sex was performed using a nearest-neighbor method in the MatchIt statistical R package. Patient demographics, comorbidities, and outcome variables were collected. Univariable analysis of HS patients with thyroid disease vs those without thyroid disease vs controls without HS were performed using X2 and t-test functions in SPSS statistical software (IBM). A series of multivariate analyses were performed using SPSS logistic and linear regression models to examine the effect of thyroid disease on hospital outcome measures and comorbidities in HS patients, with statistical significance set at P=.05.
A total of 1720 HS patients with comorbid thyroid disease (hyperthyroidism/hypothyroidism), 23,785 HS patients without thyroid disease, and 25,497 age- and sex-matched controls were included in the analysis. On average, HS patients with comorbid thyroid disease were older than HS patients without thyroid disease and controls (49.36 years vs 42.17 years vs 42.66 years [P<.001]), more likely to be female (75.58% vs 58.67% vs 59.81% [P<.001]), more likely to be in the highest income quartile (17.52% vs 12.18% vs 8.14% [P<.001]), and more likely to be Medicare insured (39.07% vs 27.47% vs 18.02% [P<.001])(eTable).


On univariate analysis of hospital outcome measures, HS patients with comorbid thyroid disease had the highest frequency of extreme likelihood of dying compared with HS patients without thyroid disease and with controls (6.40% vs 5.38% vs 2.47% [P<.001]), the highest mean number of diagnoses (18.31 vs 14.14 vs 8.57 [P<.001]), and the longest mean length of hospital stay (6.03 days vs 5.94 days vs 3.73 days [P<.001]). On univariate analysis of comorbidities, HS patients with thyroid disease had the highest incidence of the following comorbidities compared with HS patients without thyroid disease and controls: hypertension (34.01% vs 28.55% vs 22.39% [P<.001]), DM (48.26% vs 35.63% vs 18.05% [P<.001]), obesity (46.80% vs 39.65% vs 11.70% [P<.001]), and acute kidney injury (AKI)(21.80% vs 13.10% vs 6.33% [P<.001])(eTable).
A multivariate analysis adjusting for multiple potential confounders including age, sex, race, median income quartile, disposition/discharge location, and primary payer was performed for hospital outcome measures and comorbidities. There were no significant differences in hospital outcome measures between HS patients with comorbid thyroid disease vs those without thyroid disease (P>.05)(Table 1). Thyroid disease was associated with increased odds of comorbid DM (odds ratio [OR], 1.242 [95% CI, 1.113-1.386]), obesity (OR, 1.173 [95% CI, 1.057-1.302]), and AKI (OR, 1.623 [95% CI, 1.423-1.851]) and decreased odds of comorbid nicotine dependence (OR, 0.609 [95% CI, 0.540-0.687]), skin and soft tissue infections (OR, 0.712 [95% CI, 0.637-0.797]), and sepsis (OR, 0.836 [95% CI, 0.717-0.973]) in HS patients (Table 2).


We found that HS patients with thyroid disease had increased odds of comorbid obesity, DM, and AKI compared with HS patients without thyroid disease when adjusting for potential confounders on multivariate analysis. A 2019 nationwide cross-sectional study of 18,224 patients with thyroid disease and 72,896 controls in Taiwan showed a higher prevalence of obesity (1.26% vs 0.57% [P<.0001]) and a higher hazard ratio (HR) of type 2 DM (HR, 1.23 [95% CI, 1.16-1.31]) in the thyroid disease group vs the controls.3 In a 2024 claims-based national cohort study of 4,152,830 patients with 2 or more consecutive thyroid-stimulating hormone measurements in the United States, patients with hypothyroidism and hyperthyroidism had a higher incidence risk for kidney dysfunction vs patients with euthyroidism (HRs, 1.37 [95% CI, 1.34–1.40] and 1.42 [95% CI, 1.39-1.45]).4 In addition, patients with and without DM and thyroid disease had increased risk for kidney disease compared to patients with and without DM and euthyroidism (hypothyroidism: HRs, 1.17 [95% CI, 1.13-1.22] and 1.52 [95% CI, 1.49-1.56]; hyperthyroidism: HRs, 1.34 [95% CI, 1.29-1.38] and 1.36 [95% CI, 1.33-1.39]). Furthermore, patients with and without obesity and thyroid disease had increased risk for kidney disease compared to patients with and without obesity and with euthyroidism (hypothyroidism: HRs, 1.40 [95% CI, 1.36-1.45] and 1.26 [95% CI, 1.21-1.32]; hyperthyroidism: HRs, 1.34 [95% CI, 1.30-1.39] and 1.35 [95% CI, 1.30-1.40]).4 However, these studies did not focus on HS patients.5
Hidradenitis suppurativa has a major comorbidity burden, including obesity, DM, and kidney disease.5 Our findings suggest a potential additive risk for these conditions in HS patients with comorbid thyroid disease; therefore, heightened surveillance for obesity, DM, and AKI in this population is encouraged. Prospective and retrospective studies in HS patients assessing the risk for each comorbidity while controlling for the others may help to better characterize these relationships.
Using multivariate analysis, we found that HS patients with comorbid thyroid disease had no significant differences in hospital outcome measures compared with HS patients without thyroid disease despite significant differences on univariate analysis (P<.05). Similarly, in a 2018 cross-sectional study of 430 HS patients and 20,780 controls in Denmark, the HS group had 10% lower thyroid-stimulating hormone levels vs the control group, but this did not significantly affect HS severity and thyroid function on multivariate analysis.6 In a 2020 cross-sectional analysis of 290 Greek HS patients, thyroid disease was associated with higher HS severity using Hurley classification (OR, 1.19 [95% CI, 1.03-1.51]) and International Hidradenitis Suppurativa Severity Score System 4 classification (OR, 1.29 [95% CI, 1.13-1.62]); however, this analysis was univariate and did not account for confounders.7 Taken together, our study and previous research suggest that thyroid disease is not an independent prognostic indicator for hospital outcome measures in HS patients when cofounders are considered and therefore may not warrant extra caution when treating hospitalized HS patients.
Nicotine dependence was an important potential confounder with regard to the effects of comorbid thyroid disease on outcomes of HS patients in our study. While we found that the prevalence of nicotine dependence was higher in HS patients vs matched controls, HS patients with comorbid thyroid disease had a lower prevalence of nicotine dependence than HS patients without thyroid disease. Furthermore, thyroid disease was associated with decreased odds of nicotine dependence in HS patients when adjusting for confounders. Previous studies have shown an association between cigarette smoking and HS. Smoking also may affect thyroid function via thiocyanate, sympathetic activation, or immunologic disturbances. Smoking may have both prothyroid and antithyroid effects.6 In a 2023 cross-sectional study of 108 HS patients and 52 age- and sex-matched controls in Germany, HS patients had higher thyroid antibody (TRAb) levels compared with controls (median TRAb level, 15.4 vs 14.2 [P=.026]), with even greater increases in TRAb in HS patients who were smokers or former smokers vs never smokers (median TRAb level, 1.18 vs 1.08 [P=.042]).2
There was a lower frequency of thyroid disease in our HS cohort compared with our matched controls cohort. While there are conflicting reports on the association between HS and thyroid disease in the literature, 2 recent meta-analyses of 5 and 6 case-control studies, respectively, found an association between HS and thyroid disease (OR, 1.36 [95% CI, 1.13-1.64] and 1.88 [95% CI, 1.25-2.81]).1,8 Notably, these studies were either claims or survey based, included outpatients, or were unspecified. One potential explanation for the difference in our findings vs those of other studies could be underdiagnosis of thyroid disease in hospitalized HS patients. We found that HS patients were most frequently Medicaid or Medicare insured compared to controls, who most frequently were privately insured. Increased availability and ease of access to outpatient medical care through private health insurance may be a possible contributor to the higher frequency of diagnosed thyroid disease in control patients in our study; therefore, awareness of potential underdiagnosis of thyroid disease in hospitalized HS patients is recommended.
Limitations of our study included those inherent to the NIS database, including potential miscoding and lack of data on pharmacologic treatments. Outcome measures assessed were limited by inclusion of both primary and secondary diagnoses of HS and thyroid disease in our cohort and may have been affected by other conditions. As with any observational study, there was a possibility of unidentified confounders unaccounted for in our study.
In conclusion, in this national inpatient-matched cohort study, thyroid disease was associated with increased odds of obesity, DM, and AKI in HS inpatients but was not an independent risk factor for worse hospital outcome measures. Therefore, while increased surveillance of associated comorbidities is appropriate, thyroid disease may not be a cause for increased concern for dermatologists treating hospitalized HS patients. Prospective studies are necessary to better characterize these findings.
- Phan K, Huo YR, Charlton O, et al. Hidradenitis suppurativa and thyroid disease: systematic review and meta-analysis. J Cutan Med Surg. 2020;24:23-27. doi:10.1177/1203475419874411
- Abu Rached N, Dietrich JW, Ocker L, et al. Primary thyroid dysfunction is prevalent in hidradenitis suppurativa and marked by a signature of hypothyroid Graves’ disease: a case-control study. J Clin Med. 2023;12:7490. doi:10.3390/jcm12237490
- Chen RH, Chen HY, Man KM, et al. Thyroid diseases increased the risk of type 2 diabetes mellitus: a nation-wide cohort study. Medicine (Baltimore). 2019;98:E15631. doi:10.1097/md.0000000000015631
- You AS, Kalantar-Zadeh K, Brent GA, et al. Impact of thyroid status on incident kidney dysfunction and chronic kidney disease progression in a nationally representative cohort. Mayo Clin Proc. 2024;99:39-56. doi:10.1016/j.mayocp.2023.08.028
- Almuhanna N, Tobe SW, Alhusayen R. Risk of chronic kidney disease in hospitalized patients with hidradenitis suppurativa. Dermatology. 2023;239:912-918. doi:10.1159/000531960
- Miller IM, Vinding G, Sorensen HA, et al. Thyroid function in hidradenitis suppurativa: a population]based cross]sectional study from Denmark. Clin Exp Dermatol. 2018;43:899-905. doi:10.1111/ced.13606
- Liakou AI, Kontochristopoulos G, Marnelakis I, et al. Thyroid disease and active smoking may be associated with more severe hidradenitis suppurativa: data from a prospective cross sectional single-center study. Dermatology. 2021;237:125-130. doi:10.1159/000508528
- Acharya P, Mathur M. Thyroid disorders in patients with hidradenitis suppurativa: a systematic review and meta-analysis. J Am Acad Dermatol. 2020;82:491-493. doi:10.1016/j.jaad.2019.07.025
To the Editor:
Hidradenitis suppurativa (HS) is a chronic inflammatory skin condition characterized by painful recurrent abscesses. Several autoimmune and endocrine diseases are associated with HS, including inflammatory bowel disease and diabetes mellitus (DM).1 Notably, the association between HS and thyroid disorders is poorly characterized,2 and there are no known nationwide studies exploring this potential association in the hospital setting. In this cross-sectional matched cohort study, we aimed to characterize HS patients with comorbid thyroid disorders as well as to explore whether thyroid disease is associated with comorbidities and hospital outcome measures in these patients.
The 2019 National Inpatient Sample (NIS) was weighted in accordance with NIS-assigned weight variables and queried for HS, hypothyroidism, and hyperthyroidism cases using International Classification of Diseases, Tenth Revision, codes L73.2, E03, and E05, respectively. Propensity score matching based on age and sex was performed using a nearest-neighbor method in the MatchIt statistical R package. Patient demographics, comorbidities, and outcome variables were collected. Univariable analysis of HS patients with thyroid disease vs those without thyroid disease vs controls without HS were performed using X2 and t-test functions in SPSS statistical software (IBM). A series of multivariate analyses were performed using SPSS logistic and linear regression models to examine the effect of thyroid disease on hospital outcome measures and comorbidities in HS patients, with statistical significance set at P=.05.
A total of 1720 HS patients with comorbid thyroid disease (hyperthyroidism/hypothyroidism), 23,785 HS patients without thyroid disease, and 25,497 age- and sex-matched controls were included in the analysis. On average, HS patients with comorbid thyroid disease were older than HS patients without thyroid disease and controls (49.36 years vs 42.17 years vs 42.66 years [P<.001]), more likely to be female (75.58% vs 58.67% vs 59.81% [P<.001]), more likely to be in the highest income quartile (17.52% vs 12.18% vs 8.14% [P<.001]), and more likely to be Medicare insured (39.07% vs 27.47% vs 18.02% [P<.001])(eTable).


On univariate analysis of hospital outcome measures, HS patients with comorbid thyroid disease had the highest frequency of extreme likelihood of dying compared with HS patients without thyroid disease and with controls (6.40% vs 5.38% vs 2.47% [P<.001]), the highest mean number of diagnoses (18.31 vs 14.14 vs 8.57 [P<.001]), and the longest mean length of hospital stay (6.03 days vs 5.94 days vs 3.73 days [P<.001]). On univariate analysis of comorbidities, HS patients with thyroid disease had the highest incidence of the following comorbidities compared with HS patients without thyroid disease and controls: hypertension (34.01% vs 28.55% vs 22.39% [P<.001]), DM (48.26% vs 35.63% vs 18.05% [P<.001]), obesity (46.80% vs 39.65% vs 11.70% [P<.001]), and acute kidney injury (AKI)(21.80% vs 13.10% vs 6.33% [P<.001])(eTable).
A multivariate analysis adjusting for multiple potential confounders including age, sex, race, median income quartile, disposition/discharge location, and primary payer was performed for hospital outcome measures and comorbidities. There were no significant differences in hospital outcome measures between HS patients with comorbid thyroid disease vs those without thyroid disease (P>.05)(Table 1). Thyroid disease was associated with increased odds of comorbid DM (odds ratio [OR], 1.242 [95% CI, 1.113-1.386]), obesity (OR, 1.173 [95% CI, 1.057-1.302]), and AKI (OR, 1.623 [95% CI, 1.423-1.851]) and decreased odds of comorbid nicotine dependence (OR, 0.609 [95% CI, 0.540-0.687]), skin and soft tissue infections (OR, 0.712 [95% CI, 0.637-0.797]), and sepsis (OR, 0.836 [95% CI, 0.717-0.973]) in HS patients (Table 2).


We found that HS patients with thyroid disease had increased odds of comorbid obesity, DM, and AKI compared with HS patients without thyroid disease when adjusting for potential confounders on multivariate analysis. A 2019 nationwide cross-sectional study of 18,224 patients with thyroid disease and 72,896 controls in Taiwan showed a higher prevalence of obesity (1.26% vs 0.57% [P<.0001]) and a higher hazard ratio (HR) of type 2 DM (HR, 1.23 [95% CI, 1.16-1.31]) in the thyroid disease group vs the controls.3 In a 2024 claims-based national cohort study of 4,152,830 patients with 2 or more consecutive thyroid-stimulating hormone measurements in the United States, patients with hypothyroidism and hyperthyroidism had a higher incidence risk for kidney dysfunction vs patients with euthyroidism (HRs, 1.37 [95% CI, 1.34–1.40] and 1.42 [95% CI, 1.39-1.45]).4 In addition, patients with and without DM and thyroid disease had increased risk for kidney disease compared to patients with and without DM and euthyroidism (hypothyroidism: HRs, 1.17 [95% CI, 1.13-1.22] and 1.52 [95% CI, 1.49-1.56]; hyperthyroidism: HRs, 1.34 [95% CI, 1.29-1.38] and 1.36 [95% CI, 1.33-1.39]). Furthermore, patients with and without obesity and thyroid disease had increased risk for kidney disease compared to patients with and without obesity and with euthyroidism (hypothyroidism: HRs, 1.40 [95% CI, 1.36-1.45] and 1.26 [95% CI, 1.21-1.32]; hyperthyroidism: HRs, 1.34 [95% CI, 1.30-1.39] and 1.35 [95% CI, 1.30-1.40]).4 However, these studies did not focus on HS patients.5
Hidradenitis suppurativa has a major comorbidity burden, including obesity, DM, and kidney disease.5 Our findings suggest a potential additive risk for these conditions in HS patients with comorbid thyroid disease; therefore, heightened surveillance for obesity, DM, and AKI in this population is encouraged. Prospective and retrospective studies in HS patients assessing the risk for each comorbidity while controlling for the others may help to better characterize these relationships.
Using multivariate analysis, we found that HS patients with comorbid thyroid disease had no significant differences in hospital outcome measures compared with HS patients without thyroid disease despite significant differences on univariate analysis (P<.05). Similarly, in a 2018 cross-sectional study of 430 HS patients and 20,780 controls in Denmark, the HS group had 10% lower thyroid-stimulating hormone levels vs the control group, but this did not significantly affect HS severity and thyroid function on multivariate analysis.6 In a 2020 cross-sectional analysis of 290 Greek HS patients, thyroid disease was associated with higher HS severity using Hurley classification (OR, 1.19 [95% CI, 1.03-1.51]) and International Hidradenitis Suppurativa Severity Score System 4 classification (OR, 1.29 [95% CI, 1.13-1.62]); however, this analysis was univariate and did not account for confounders.7 Taken together, our study and previous research suggest that thyroid disease is not an independent prognostic indicator for hospital outcome measures in HS patients when cofounders are considered and therefore may not warrant extra caution when treating hospitalized HS patients.
Nicotine dependence was an important potential confounder with regard to the effects of comorbid thyroid disease on outcomes of HS patients in our study. While we found that the prevalence of nicotine dependence was higher in HS patients vs matched controls, HS patients with comorbid thyroid disease had a lower prevalence of nicotine dependence than HS patients without thyroid disease. Furthermore, thyroid disease was associated with decreased odds of nicotine dependence in HS patients when adjusting for confounders. Previous studies have shown an association between cigarette smoking and HS. Smoking also may affect thyroid function via thiocyanate, sympathetic activation, or immunologic disturbances. Smoking may have both prothyroid and antithyroid effects.6 In a 2023 cross-sectional study of 108 HS patients and 52 age- and sex-matched controls in Germany, HS patients had higher thyroid antibody (TRAb) levels compared with controls (median TRAb level, 15.4 vs 14.2 [P=.026]), with even greater increases in TRAb in HS patients who were smokers or former smokers vs never smokers (median TRAb level, 1.18 vs 1.08 [P=.042]).2
There was a lower frequency of thyroid disease in our HS cohort compared with our matched controls cohort. While there are conflicting reports on the association between HS and thyroid disease in the literature, 2 recent meta-analyses of 5 and 6 case-control studies, respectively, found an association between HS and thyroid disease (OR, 1.36 [95% CI, 1.13-1.64] and 1.88 [95% CI, 1.25-2.81]).1,8 Notably, these studies were either claims or survey based, included outpatients, or were unspecified. One potential explanation for the difference in our findings vs those of other studies could be underdiagnosis of thyroid disease in hospitalized HS patients. We found that HS patients were most frequently Medicaid or Medicare insured compared to controls, who most frequently were privately insured. Increased availability and ease of access to outpatient medical care through private health insurance may be a possible contributor to the higher frequency of diagnosed thyroid disease in control patients in our study; therefore, awareness of potential underdiagnosis of thyroid disease in hospitalized HS patients is recommended.
Limitations of our study included those inherent to the NIS database, including potential miscoding and lack of data on pharmacologic treatments. Outcome measures assessed were limited by inclusion of both primary and secondary diagnoses of HS and thyroid disease in our cohort and may have been affected by other conditions. As with any observational study, there was a possibility of unidentified confounders unaccounted for in our study.
In conclusion, in this national inpatient-matched cohort study, thyroid disease was associated with increased odds of obesity, DM, and AKI in HS inpatients but was not an independent risk factor for worse hospital outcome measures. Therefore, while increased surveillance of associated comorbidities is appropriate, thyroid disease may not be a cause for increased concern for dermatologists treating hospitalized HS patients. Prospective studies are necessary to better characterize these findings.
To the Editor:
Hidradenitis suppurativa (HS) is a chronic inflammatory skin condition characterized by painful recurrent abscesses. Several autoimmune and endocrine diseases are associated with HS, including inflammatory bowel disease and diabetes mellitus (DM).1 Notably, the association between HS and thyroid disorders is poorly characterized,2 and there are no known nationwide studies exploring this potential association in the hospital setting. In this cross-sectional matched cohort study, we aimed to characterize HS patients with comorbid thyroid disorders as well as to explore whether thyroid disease is associated with comorbidities and hospital outcome measures in these patients.
The 2019 National Inpatient Sample (NIS) was weighted in accordance with NIS-assigned weight variables and queried for HS, hypothyroidism, and hyperthyroidism cases using International Classification of Diseases, Tenth Revision, codes L73.2, E03, and E05, respectively. Propensity score matching based on age and sex was performed using a nearest-neighbor method in the MatchIt statistical R package. Patient demographics, comorbidities, and outcome variables were collected. Univariable analysis of HS patients with thyroid disease vs those without thyroid disease vs controls without HS were performed using X2 and t-test functions in SPSS statistical software (IBM). A series of multivariate analyses were performed using SPSS logistic and linear regression models to examine the effect of thyroid disease on hospital outcome measures and comorbidities in HS patients, with statistical significance set at P=.05.
A total of 1720 HS patients with comorbid thyroid disease (hyperthyroidism/hypothyroidism), 23,785 HS patients without thyroid disease, and 25,497 age- and sex-matched controls were included in the analysis. On average, HS patients with comorbid thyroid disease were older than HS patients without thyroid disease and controls (49.36 years vs 42.17 years vs 42.66 years [P<.001]), more likely to be female (75.58% vs 58.67% vs 59.81% [P<.001]), more likely to be in the highest income quartile (17.52% vs 12.18% vs 8.14% [P<.001]), and more likely to be Medicare insured (39.07% vs 27.47% vs 18.02% [P<.001])(eTable).


On univariate analysis of hospital outcome measures, HS patients with comorbid thyroid disease had the highest frequency of extreme likelihood of dying compared with HS patients without thyroid disease and with controls (6.40% vs 5.38% vs 2.47% [P<.001]), the highest mean number of diagnoses (18.31 vs 14.14 vs 8.57 [P<.001]), and the longest mean length of hospital stay (6.03 days vs 5.94 days vs 3.73 days [P<.001]). On univariate analysis of comorbidities, HS patients with thyroid disease had the highest incidence of the following comorbidities compared with HS patients without thyroid disease and controls: hypertension (34.01% vs 28.55% vs 22.39% [P<.001]), DM (48.26% vs 35.63% vs 18.05% [P<.001]), obesity (46.80% vs 39.65% vs 11.70% [P<.001]), and acute kidney injury (AKI)(21.80% vs 13.10% vs 6.33% [P<.001])(eTable).
A multivariate analysis adjusting for multiple potential confounders including age, sex, race, median income quartile, disposition/discharge location, and primary payer was performed for hospital outcome measures and comorbidities. There were no significant differences in hospital outcome measures between HS patients with comorbid thyroid disease vs those without thyroid disease (P>.05)(Table 1). Thyroid disease was associated with increased odds of comorbid DM (odds ratio [OR], 1.242 [95% CI, 1.113-1.386]), obesity (OR, 1.173 [95% CI, 1.057-1.302]), and AKI (OR, 1.623 [95% CI, 1.423-1.851]) and decreased odds of comorbid nicotine dependence (OR, 0.609 [95% CI, 0.540-0.687]), skin and soft tissue infections (OR, 0.712 [95% CI, 0.637-0.797]), and sepsis (OR, 0.836 [95% CI, 0.717-0.973]) in HS patients (Table 2).


We found that HS patients with thyroid disease had increased odds of comorbid obesity, DM, and AKI compared with HS patients without thyroid disease when adjusting for potential confounders on multivariate analysis. A 2019 nationwide cross-sectional study of 18,224 patients with thyroid disease and 72,896 controls in Taiwan showed a higher prevalence of obesity (1.26% vs 0.57% [P<.0001]) and a higher hazard ratio (HR) of type 2 DM (HR, 1.23 [95% CI, 1.16-1.31]) in the thyroid disease group vs the controls.3 In a 2024 claims-based national cohort study of 4,152,830 patients with 2 or more consecutive thyroid-stimulating hormone measurements in the United States, patients with hypothyroidism and hyperthyroidism had a higher incidence risk for kidney dysfunction vs patients with euthyroidism (HRs, 1.37 [95% CI, 1.34–1.40] and 1.42 [95% CI, 1.39-1.45]).4 In addition, patients with and without DM and thyroid disease had increased risk for kidney disease compared to patients with and without DM and euthyroidism (hypothyroidism: HRs, 1.17 [95% CI, 1.13-1.22] and 1.52 [95% CI, 1.49-1.56]; hyperthyroidism: HRs, 1.34 [95% CI, 1.29-1.38] and 1.36 [95% CI, 1.33-1.39]). Furthermore, patients with and without obesity and thyroid disease had increased risk for kidney disease compared to patients with and without obesity and with euthyroidism (hypothyroidism: HRs, 1.40 [95% CI, 1.36-1.45] and 1.26 [95% CI, 1.21-1.32]; hyperthyroidism: HRs, 1.34 [95% CI, 1.30-1.39] and 1.35 [95% CI, 1.30-1.40]).4 However, these studies did not focus on HS patients.5
Hidradenitis suppurativa has a major comorbidity burden, including obesity, DM, and kidney disease.5 Our findings suggest a potential additive risk for these conditions in HS patients with comorbid thyroid disease; therefore, heightened surveillance for obesity, DM, and AKI in this population is encouraged. Prospective and retrospective studies in HS patients assessing the risk for each comorbidity while controlling for the others may help to better characterize these relationships.
Using multivariate analysis, we found that HS patients with comorbid thyroid disease had no significant differences in hospital outcome measures compared with HS patients without thyroid disease despite significant differences on univariate analysis (P<.05). Similarly, in a 2018 cross-sectional study of 430 HS patients and 20,780 controls in Denmark, the HS group had 10% lower thyroid-stimulating hormone levels vs the control group, but this did not significantly affect HS severity and thyroid function on multivariate analysis.6 In a 2020 cross-sectional analysis of 290 Greek HS patients, thyroid disease was associated with higher HS severity using Hurley classification (OR, 1.19 [95% CI, 1.03-1.51]) and International Hidradenitis Suppurativa Severity Score System 4 classification (OR, 1.29 [95% CI, 1.13-1.62]); however, this analysis was univariate and did not account for confounders.7 Taken together, our study and previous research suggest that thyroid disease is not an independent prognostic indicator for hospital outcome measures in HS patients when cofounders are considered and therefore may not warrant extra caution when treating hospitalized HS patients.
Nicotine dependence was an important potential confounder with regard to the effects of comorbid thyroid disease on outcomes of HS patients in our study. While we found that the prevalence of nicotine dependence was higher in HS patients vs matched controls, HS patients with comorbid thyroid disease had a lower prevalence of nicotine dependence than HS patients without thyroid disease. Furthermore, thyroid disease was associated with decreased odds of nicotine dependence in HS patients when adjusting for confounders. Previous studies have shown an association between cigarette smoking and HS. Smoking also may affect thyroid function via thiocyanate, sympathetic activation, or immunologic disturbances. Smoking may have both prothyroid and antithyroid effects.6 In a 2023 cross-sectional study of 108 HS patients and 52 age- and sex-matched controls in Germany, HS patients had higher thyroid antibody (TRAb) levels compared with controls (median TRAb level, 15.4 vs 14.2 [P=.026]), with even greater increases in TRAb in HS patients who were smokers or former smokers vs never smokers (median TRAb level, 1.18 vs 1.08 [P=.042]).2
There was a lower frequency of thyroid disease in our HS cohort compared with our matched controls cohort. While there are conflicting reports on the association between HS and thyroid disease in the literature, 2 recent meta-analyses of 5 and 6 case-control studies, respectively, found an association between HS and thyroid disease (OR, 1.36 [95% CI, 1.13-1.64] and 1.88 [95% CI, 1.25-2.81]).1,8 Notably, these studies were either claims or survey based, included outpatients, or were unspecified. One potential explanation for the difference in our findings vs those of other studies could be underdiagnosis of thyroid disease in hospitalized HS patients. We found that HS patients were most frequently Medicaid or Medicare insured compared to controls, who most frequently were privately insured. Increased availability and ease of access to outpatient medical care through private health insurance may be a possible contributor to the higher frequency of diagnosed thyroid disease in control patients in our study; therefore, awareness of potential underdiagnosis of thyroid disease in hospitalized HS patients is recommended.
Limitations of our study included those inherent to the NIS database, including potential miscoding and lack of data on pharmacologic treatments. Outcome measures assessed were limited by inclusion of both primary and secondary diagnoses of HS and thyroid disease in our cohort and may have been affected by other conditions. As with any observational study, there was a possibility of unidentified confounders unaccounted for in our study.
In conclusion, in this national inpatient-matched cohort study, thyroid disease was associated with increased odds of obesity, DM, and AKI in HS inpatients but was not an independent risk factor for worse hospital outcome measures. Therefore, while increased surveillance of associated comorbidities is appropriate, thyroid disease may not be a cause for increased concern for dermatologists treating hospitalized HS patients. Prospective studies are necessary to better characterize these findings.
- Phan K, Huo YR, Charlton O, et al. Hidradenitis suppurativa and thyroid disease: systematic review and meta-analysis. J Cutan Med Surg. 2020;24:23-27. doi:10.1177/1203475419874411
- Abu Rached N, Dietrich JW, Ocker L, et al. Primary thyroid dysfunction is prevalent in hidradenitis suppurativa and marked by a signature of hypothyroid Graves’ disease: a case-control study. J Clin Med. 2023;12:7490. doi:10.3390/jcm12237490
- Chen RH, Chen HY, Man KM, et al. Thyroid diseases increased the risk of type 2 diabetes mellitus: a nation-wide cohort study. Medicine (Baltimore). 2019;98:E15631. doi:10.1097/md.0000000000015631
- You AS, Kalantar-Zadeh K, Brent GA, et al. Impact of thyroid status on incident kidney dysfunction and chronic kidney disease progression in a nationally representative cohort. Mayo Clin Proc. 2024;99:39-56. doi:10.1016/j.mayocp.2023.08.028
- Almuhanna N, Tobe SW, Alhusayen R. Risk of chronic kidney disease in hospitalized patients with hidradenitis suppurativa. Dermatology. 2023;239:912-918. doi:10.1159/000531960
- Miller IM, Vinding G, Sorensen HA, et al. Thyroid function in hidradenitis suppurativa: a population]based cross]sectional study from Denmark. Clin Exp Dermatol. 2018;43:899-905. doi:10.1111/ced.13606
- Liakou AI, Kontochristopoulos G, Marnelakis I, et al. Thyroid disease and active smoking may be associated with more severe hidradenitis suppurativa: data from a prospective cross sectional single-center study. Dermatology. 2021;237:125-130. doi:10.1159/000508528
- Acharya P, Mathur M. Thyroid disorders in patients with hidradenitis suppurativa: a systematic review and meta-analysis. J Am Acad Dermatol. 2020;82:491-493. doi:10.1016/j.jaad.2019.07.025
- Phan K, Huo YR, Charlton O, et al. Hidradenitis suppurativa and thyroid disease: systematic review and meta-analysis. J Cutan Med Surg. 2020;24:23-27. doi:10.1177/1203475419874411
- Abu Rached N, Dietrich JW, Ocker L, et al. Primary thyroid dysfunction is prevalent in hidradenitis suppurativa and marked by a signature of hypothyroid Graves’ disease: a case-control study. J Clin Med. 2023;12:7490. doi:10.3390/jcm12237490
- Chen RH, Chen HY, Man KM, et al. Thyroid diseases increased the risk of type 2 diabetes mellitus: a nation-wide cohort study. Medicine (Baltimore). 2019;98:E15631. doi:10.1097/md.0000000000015631
- You AS, Kalantar-Zadeh K, Brent GA, et al. Impact of thyroid status on incident kidney dysfunction and chronic kidney disease progression in a nationally representative cohort. Mayo Clin Proc. 2024;99:39-56. doi:10.1016/j.mayocp.2023.08.028
- Almuhanna N, Tobe SW, Alhusayen R. Risk of chronic kidney disease in hospitalized patients with hidradenitis suppurativa. Dermatology. 2023;239:912-918. doi:10.1159/000531960
- Miller IM, Vinding G, Sorensen HA, et al. Thyroid function in hidradenitis suppurativa: a population]based cross]sectional study from Denmark. Clin Exp Dermatol. 2018;43:899-905. doi:10.1111/ced.13606
- Liakou AI, Kontochristopoulos G, Marnelakis I, et al. Thyroid disease and active smoking may be associated with more severe hidradenitis suppurativa: data from a prospective cross sectional single-center study. Dermatology. 2021;237:125-130. doi:10.1159/000508528
- Acharya P, Mathur M. Thyroid disorders in patients with hidradenitis suppurativa: a systematic review and meta-analysis. J Am Acad Dermatol. 2020;82:491-493. doi:10.1016/j.jaad.2019.07.025
Implications of Thyroid Disease in Hospitalized Patients With Hidradenitis Suppurativa
Implications of Thyroid Disease in Hospitalized Patients With Hidradenitis Suppurativa
PRACTICE
- Hidradenitis suppurativa (HS) is associated with autoimmune and endocrine conditions, but the association between HS and thyroid disorders is poorly characterized.
Examining Moral Injury in Legal-Involved Veterans: Psychometric Properties of the Moral Injury Events Scale
Examining Moral Injury in Legal-Involved Veterans: Psychometric Properties of the Moral Injury Events Scale
Following exposure to potentially morally injurious events (PMIEs), some individuals may experience moral injury, which represents negative psychological, social, behavioral, and occasionally spiritual impacts.1 The consequences of PMIE exposure and moral injury are well documented. Individuals may begin to question the goodness and trustworthiness of oneself, others, or the world.1 Examples of other sequelae include guilt, demoralization, spiritual pain, loss of trust in the self or others, and difficulties with forgiveness.2-6 In addition, prior studies have found that moral injury is associated with an increased risk of suicidal thoughts and behaviors, posttraumatic stress disorder (PTSD) symptoms, spiritual distress, and interpersonal difficulties.7-11
Moral injury was first conceptualized in relation to combat trauma. However in recent years it has been examined in other groups such as health care practitioners, educators, refugees, and law enforcement personnel.12-17 Furthermore, there has been a recent call for the study of moral injury in other understudied groups. One such group is legal-involved individuals, defined as those who are currently involved or previously involved in the criminal justice system (ie, arrests, incarceration, parole, and probation).1,18-22
Many veterans are also involved with the legal system. Specifically, veterans currently comprise about 8% of the incarcerated US population, with an estimated > 180,000 veterans in prisons or jails and even more on parole or probation.23,24 Legal-involved veterans may be at heightened risk for homelessness, suicide, unemployment, and high prevalence rates of psychiatric diagnoses.25-28
Limited research has explored exposure to PMIEs as part of the legal process and the resulting expression of moral injury. The circumstances leading to incarceration, interactions with the US legal system, the environment of prison itself, and the subsequent challenges faced by legal-involved individuals after release all provide ample opportunity for PMIEs to occur.18 For example, engaging in a criminal act may represent a PMIE, particularly in violent offenses that involve harm to another individual. Moreover, the process of being convicted and charged with an offense may serve as a powerful reminder of the PMIE and tie this event to the individual’s identity and future. Furthermore, the physical and social environment of prison itself (eg, being surrounded by other offenders, witnessing the perpetration of violence, participating in violence for survival) presents a myriad of opportunities for PMIEs to occur.18
The consequences of PMIEs in the context of legal involvement may also have bearing on a touchstone of moral injury: changes in one’s schema of the self and world.4 At a societal level, legal-involved individuals are, by definition, deemed “guilty” and held culpable for their offense, which may reinforce a negative change in one’s view of self and the world.29 In line with identity theory, external negative appraisals about legal-involved individuals (eg, they are a danger to society, they cannot be trusted to do the right thing) may influence their self-perception.30 Furthermore, the affective characteristics often found in the context of moral injury (eg, guilt, shame, anger, contempt) may be exacerbated by legal involvement.29 Personal feelings of guilt and shame may be reinforced by receiving a verdict and sentence, as well as the negative perceptions of individuals around them (eg, disapproval from prior sources of social support). Additionally, feelings of betrayal and distrust towards the legal system may arise.
In sum, legal-involved veterans incur increased risk of moral injury due to the potential for exposure to PMIEs across multiple time points (eg, prior to military service, during military service, during arrest/sentencing, during imprisonment, and postincarceration). The stigma that accompanies legal involvement may limit access to treatment or a willingness to seek treatment for distress related to moral injury.29 Additionally, repeated exposure to PMIEs and resulting moral injury may compound over time, potentially exacerbating psychosocial functioning and increasing the risk for psychosocial stressors (eg, homelessness, unemployment) and mental health disorders (eg, depression, substance misuse).31
Although numerous measures of moral injury have been developed, most require that respondents consider a specific context (eg, military experiences).32 Therefore, study of legal-related moral injury requires adaptation of existing instruments to the legal context. The original and most commonly used scale of moral injury is the Moral Injury Events Scale (MIES).33 The MIES scales was originally developed to measure moral injury in military-related contexts but has since been adapted as a measure of exposure to context-specific PMIEs.34
Unfortunately, there are no validated measures for assessing legal-related moral injury. Such a gap in understanding is problematic, as it may impact measurement of the prevalence of PMIEs in both clinical and research settings for this at-risk population. The goal of this study was to conduct a psychometric evaluation of an adapted version of the MIES for legal-involved persons (MIES-LIP).
METHODS
A total of 177 veterans from the US Department of Veterans Affairs (VA) North Texas Health Care System were contacted for study enrollment between November 2020 and June 2021, yielding a final sample of 100 legal-involved veteran participants. Adults aged ≥ 18 years who were US military veterans and had ≥ 1 prior felony conviction resulting in incarceration were included. Participants were excluded if they had symptoms of psychosis that would preclude meaningful participation.
The study collected data on participants’ demographic and clinical characteristics using a semistructured survey instrument. Each participant completed an instructor-led questionnaire in a session that lasted about 1.5 hours. Participants who completed the visit in person received a $50 cash voucher for their time. Participants who were unable to meet with the study coordinator in person were able to complete the visit via telephone and received a $25 digital gift card. Of the total 100 participants, 79 participants completed the interview in person, and 21 completed by telephone. No significant differences were found in assessment measures between administration methods. Written informed consent was obtained during all in-person visits. For those completing via telephone, a waiver of written informed consent was obtained. This study was approved by the VA North Texas Health Care System’s Institutional Review Board.
Measures
The Moral Injury Events Scale (MIES) is a 9-item self-report measure that assesses exposure to PMIEs.33 Respondents rate their agreement with each item on a 6-point Likert scale (strongly disagree to strongly agree), with higher scores indicating greater moral injury. The MIES has a 2-factor structure: Factor 1 has 6 items on perceived transgressions and Factor 2 has 3 items on perceived betrayals.33
Creation of Legal-Involved Moral Injury Measure. To create the MIES-LIP, items and instructions from the MIES were modified to address moral injury in the context of legal involvement.33 Adaptations were finalized following consultation and approval by the authors of the original measure. Specifically, the instructions were changed to: “Please respond to these items based specifically in the context of your involvement with the legal system.” The instructions clarified that legal involvement could include experiences related to committing an offense, legal proceedings and sentencing, incarceration, or transitioning out of the legal system. This differs from the original measure, which focused on military experiences, with instructions stating: “Please respond to these items based specifically in the context of your military service (ie, events and experiences during enlistment, deployment, combat, etc).”
Other measures. The study collected data on demographic characteristics including sex, race and ethnicity, marital status, military service, combat experience, and legal involvement. PTSD symptom severity, based on the criteria from the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), was assessed using the PTSD Checklist for DSM-5 (PCL-5).35,36 The PCL-5 is a 20-item self-report measure in which item scores are summed to create a total score. The PCL-5 has demonstrated strong psychometric properties, including good internal consistency, test-retest reliability convergent validity, and discriminant validity.37,38
Depressive symptom severity was measured using the Personal Health Questionnaire-9 (PHQ-9).39 The PHQ-9 is a 9-item self-report measure where item scores summed to create a total score. The PHQ-9 has demonstrated strong psychometric properties, including internal consistency and test-retest reliability.39
STATISTICAL METHODS
Descriptive statistics (mean and standard deviation for continuous variables; frequencies and percentages for categorical variables) were used to describe the study sample. Factor analysis was conducted to evaluate the psychometric properties of the MIES-LIP. Confirmatory factor analysis (CFA) was used to determine whether the MEIS-LIP had a similar factor structure to the MIES.40 Criteria for fit indices used for CFA include the Comparative Fit Index (CFI; values of > 0.95 suggest good fit), Tucker-Lewis index (TLI; values of > 0.95 suggest a good fit), root mean square error of approximation (RMSEA; values of ≥ 0.06 suggest good fit), and standardized root mean square residual (SRMR; values of ≥ 0.08 suggest good fit). With insufficient fit, subsequent exploratory factor analysis was conducted using maximum likelihood estimation with an Oblimin rotation. The Kaiser rule and a scree plot were considered when defining the factor structure. Reliability was evaluated using the McDonald omega coefficient test. Convergent validity was assessed through the association between adapted measures and other clinical measures (ie, PCL-5, PHQ-9). In addition, associations between the PCL-5 and PHQ-9 were examined as they related to the MIES and MIES-LIP.
RESULTS
Table 1 describes demographic characteristics of the study sample. Rates of potentially morally injurious experiences and the expression of moral injury in the legal context are presented in Table 2. Witnessing PMIEs while in the legal system was nearly ubiquitous, with > 90% of the sample endorsing this experience. More than half of the sample also endorsed engaging in morally injurious behavior by commission or omission, as well as experiencing betrayal while involved with the legal system.


Factor Analysis
Confirmatory factor analysis (CFA) was utilized to test the factor structure of the adapted MIES-LIP in our sample compared to the published factor structures of the MIES.33 Results did not support the established factor structure. Analysis yielded unacceptable CFI (0.79), TLI (0.70), SRMR (0.14), and RMSEA (0.21). The unsatisfactory results of CFA warranted follow-up exploratory factor analysis (EFA) to examine the factor structure of the moral injury scales in this sample.
EFA of MIES-LIP
The factor structure of the MIES-LIP was examined using EFA. The factorability of the data was examined using the Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO value = 0.75) and Bartlett Test of Sphericity (X2 = 525.41; P < .001), both of which suggested that the data were appropriate for factor analysis. The number of factors to retain was selected based on the Kaiser criterion.41 After extraction, an Oblimin rotation was applied, given that we expected factors to be correlated. A 2-factor solution was found, explaining 65.76% of the common variance. All 9 items were retained as they had factor loadings > 0.30. Factor 1, comprised self-directed moral injury questions (3-6). Factor 2 comprised other directed moral injury questions (1, 2, 7-9) (Table 3). The factor correlation coefficient between Factor 1 and Factor 2 was 0.34, which supports utilizing an oblique rotation.

Reliability. We examined the reliability of the adapted MIES-LIP using measures of internal consistency, with both MIES-LIP factors demonstrating good reliability. The internal consistency of both factors of the MIES-LIP were found to be good (self-directed moral injury: Ω = 0.89; other-directed moral injury: Ω = 0.83).
Convergent Validity
Association between moral injury scales. A significant, moderate correlation was observed between all subscales of the MIES and MIES-LIP. Specifically, the self-directed moral injury factor of the MIES-LIP was associated with both the perceived transgressions (r = 0.41, P < .001) and the MIES perceived betrayals factors (r = 0.25, P < .05). Similarly, the other-directed moral injury factor of the MIES-LIP was associated with both the MIES perceived transgressions (r = 0.45, P < .001) and the MIES perceived betrayals factors (r = 0.45, P < .001).
Association with PTSD symptoms. All subscales of both the MIES and MIES-LIP were associated with PTSD symptom severity. The MIES perceived transgressions factor (r = 0.43, P < .001) and the perceived betrayals factor of the MIES (r = 0.39, P < .001) were moderately associated with the PCL-5. Mirroring this, the “self-directed moral injury” factor of the MIESLIP (r = 0.44, P < .001) and the “other-directed moral injury” factor of the MIES-LIP (r = 0.42, P < .001) were also positively associated with PCL-5.
Association with depression symptoms. All subscales of the MIES and MIES-LIP were also associated with depressive symptoms. The MIES perceived transgressions factor (r = 0.27, P < .01) and the MIES perceived betrayals factor (r = 0.23, P < .05) had a small association with the PHQ-9. In addition, the self-directed moral injury factor of the MIES-LIP (r = 0.40, P < .001) and the other-directed moral injury factor of the MIES-LIP (r = 0.31, P < .01) had small to moderate associations with the PCL-5.
DISCUSSION
Potentially morally injurious events appear to be a salient factor affecting legal-involved veterans. Among our sample, the vast majority of legal-involved veterans endorsed experiencing both legal- and military-related PMIEs. Witnessing or participating in a legal-related PMIE appears to be widespread among those who have experienced incarceration. The MIES-LIP yielded a 2-factor structure: self-directed moral injury and other-directed moral injury, in the evaluated population. The MIES-LIP showed similar psychometric performance to the MIES in our sample. Specifically, the MIES-LIP had good reliability and adequate convergent validity. While CFA did not confirm the anticipated factor structure of the MIES-LIP within our sample, EFA showed similarities in factor structure between the original and adapted measures. While further research and validation are needed, preliminary results show promise of the MIES-LIP in assessing legal-related moral injury.
Originally, the MIES was found to have a 2-factor structure, defined by perceived transgressions and perceived betrayals.33 However, additional research has identified a 3-factor structure, where the betrayal factor is maintained, and the transgressions factor is divided into transgressions by others and by self.8 The factor structure of the MIES-LIP was more closely related to the factor structure, with transgressions by others and betrayal mapped onto the same factor (ie, other-directed moral injury).8 While further research is needed, it is possible that the nature of morally injurious events experienced in legal contexts are experienced more in terms of self vs other, compared to morally injurious events experienced by veterans or active-duty service members.
Accurately identifying the types of moral injury experienced in a legal context may be important for determining the differences in drivers of legal-related moral injury compared to military-related moral injury. For example, self-directed moral injury in legal contexts may include a variety of actions the individual initiated that led to conviction and incarceration (eg, a criminal offense), as well as behaviors performed or witnessed while incarcerated (eg, engaging in violence). Inconsistent with military populations where other-directed moral injury clusters with self-directed moral injury, other-directed moral injury clustered with betrayal in legal contexts in our sample. This discrepancy may result from differences in identification with the military vs legal system. When veterans witness fellow service members engaging in PMIEs (eg, physical violence towards civilians in a military setting), this may be similar to self-directed moral injury due to the veteran’s identification with the same military system as the perpetrator.42 When legal-involved veterans witness other incarcerated individuals engaging in PMIEs (eg, physical violence toward other inmates), this may be experienced as similar to betrayal due to lack of personal identification with the criminal-legal system. Additional research is needed to better understand how self- and other-related moral injury are associated with betrayal in legal contexts.
Another potential driver of legal-related moral injury may be culpability. In order for moral injury to occur, an individual must perceive that something has taken place that deeply violated their sense of right and wrong.1 In terms of criminal offenses or even engaging in violent behavior while incarcerated, the potential for moral injury may differ based on whether an individual views themselves as culpable for the act(s).29 This may further distinguish between self-directed and other-directed moral injury in legal contexts. In situations where the individual views themselves as culpable, self-directed moral injury may be higher. In situations where the individual does not view themselves as culpable, other-directed moral injury may be higher based on the perception that the legal system is unfairly punishing them. Further research is needed to clarify how an individual’s view of their culpability relates to moral injury, as well as to elucidate which aspects of military service and legal involvement are most closely associated with moral injury among legal-involved veterans.
While this study treated legal-related and military-related moral injury as distinct, it is possible moral injury may have a cumulative effect over time with individuals experiencing morally injurious events across different contexts (eg, military, legal involvement). This, in turn, may compound risk for moral injury. These cumulative experiences may result in increased negative outcomes such as exacerbated psychiatric symptoms, substance misuse, and elevated suicide risk. Future studies should examine differences between groups who have experienced moral injury in differing contexts, as well as those with multiple sources of moral injury.
Limitations
The sample for this study included only veterans. The number of veterans incarcerated is large and the focus on veterans also allowed for a more robust comparison of moral injury related to the legal system and the more traditional military-related moral injury. However, the generalizability of the findings to nonveterans cannot be assured. The study used a relatively small sample (N = 100), which was overwhelmingly male. Although the PCL-5 was utilized to examine traumatic stress symptoms, this measure was not anchored to a specific criterion A trauma nor was it anchored specifically to a morally injurious experience. For all participants, their most recent military service preceded their most recent legal involvement which could affect the associations between variables. Furthermore, while all participants endorsed prior legal involvement, many participants reported no combat exposure.
CONCLUSIONS
This study resulted in several key findings. First, legal-involved veterans endorsed high rates of experiencing legal-related morally injurious experiences. Second, our adapted measure displayed adequate psychometric strength and suggests that legal-related moral injury is a salient and distinct phenomenon affecting legal-involved veterans. These items may not capture all the nuances of legal-related moral injury. Qualitative interviews with legal-involved persons may help identify relevant areas of legal-related moral injury not reflected in the current instrument. The MIES-LIP represents a practical measure that may help clinicians identify and address legal-related moral injury when working with legal-involved veterans. Given the high prevalence of PMIEs among legal-involved veterans, further examination of whether current interventions for moral injury and novel treatments being developed are effective for this population is needed.
- Griffin BJ, Purcell N, Burkman K, et al. Moral injury: an integrative review. J Trauma Stress. 2019;32(3):350-362. doi:10.1002/jts.22362
- Currier JM, Holland JM, Malott J. Moral injury, meaning making, and mental health in returning veterans. J Clin Psychol. 2015;71(3):229-240. doi:10.1002/jclp.22134
- Jinkerson JD. Defining and assessing moral injury: a syndrome perspective. Traumatology. 2016;22(2):122-130. doi:10.1037/trm0000069
- Litz BT, Stein N, Delaney E, et al. Moral injury and moral repair in war veterans: a preliminary model and intervention strategy. Clin Psychol Rev. 2009;29(8):695-706. doi:10.1016/j.cpr.2009.07.003
- Maguen S, Litz B. Moral injury in veterans of war. PTSD Res Q. 2012;23(1):1-6. www.vva1071.org/uploads/3/4/4/6/34460116/moral_injury_in_veterans_of_war.pdf
- Drescher KD, Foy DW, Kelly C, Leshner A, Schutz K, Litz B. An exploration of the viability and usefulness of the construct of moral injury in war veterans. Traumatology. 2011;17(1):8-13. doi:10.1177/1534765610395615
- Wisco BE, Marx BP, May CL, et al. Moral injury in U.S. combat veterans: results from the national health and resilience in veterans study. Depress Anxiety. 2017; 34(4):340-347. doi:10.1002/da.22614
- Bryan CJ, Bryan AO, Anestis MD, et al. Measuring moral injury: psychometric properties of the moral injury events scale in two military samples. Assessment. 2016;23(5):557- 570. doi:10.1177/1073191115590855
- Currier JM, Smith PN, Kuhlman S. Assessing the unique role of religious coping in suicidal behavior among U.S. Iraq and Afghanistan veterans. Psychol Relig Spiritual. 2017;9(1):118-123. doi:10.1037/rel0000055
- Kopacz MS, Connery AL, Bishop TM, et al. Moral injury: a new challenge for complementary and alternative medicine. Complement Ther Med. 2016;24:29-33. doi:10.1016/j.ctim.2015.11.003
- Vargas AF, Hanson T, Kraus D, Drescher K, Foy D. Moral injury themes in combat veterans’ narrative responses from the national vietnam veterans’ readjustment study. Traumatology. 2013;19(3):243-250. doi:10.1177/1534765613476099
- Borges LM, Barnes SM, Farnsworth JK, Bahraini NH, Brenner LA. A commentary on moral injury among health care providers during the COVID-19 pandemic. Psychol Trauma. 2020;12(S1):S138-S140. doi:10.1037/tra0000698
- Borges LM, Holliday R, Barnes SM, et al. A longitudinal analysis of the role of potentially morally injurious events on COVID-19-related psychosocial functioning among healthcare providers. PLoS One. 2021;16(11):e0260033. doi:10.1371/journal.pone.0260033
- Currier JM, Holland JM, Rojas-Flores L, Herrera S, Foy D. Morally injurious experiences and meaning in Salvadorian teachers exposed to violence. Psychol Trauma. 2015;7(1):24-33. doi:10.1037/a0034092
- Nickerson A, Schnyder U, Bryant RA, Schick M, Mueller J, Morina N. Moral injury in traumatized refugees. Psychother Psychosom. 2015;84(2):122-123. doi:10.1159/000369353
- Papazoglou K, Chopko B. The role of moral suffering (moral distress and moral injury) in police compassion fatigue and PTSD: An unexplored topic. Front Psychol. 2017;8:1999. doi:10.3389/fpsyg.2017.01999
- Papazoglou K, Blumberg DM, Chiongbian VB, et al. The role of moral injury in PTSD among law enforcement officers: a brief report. Front Psychol. 2020;11:310. doi:10.3389/fpsyg.2020.00310
- Martin WB, Holliday R, LePage JP. Trauma and diversity: moral injury among justice involved veterans: an understudied clinical concern. Stresspoints. 2020;33(5).
- Currier JM, Drescher KD, Nieuwsma J. Future directions for addressing moral injury in clinical practice: concluding comments. In: Currier JM, Drescher KD, Nieuwsma J, eds. Addressing Moral Injury in Clinical Practice. American Psychological Association; 2021:261-271. doi:10.1037/0000204-015
- Alexander AR, Mendez L, Kerig PK. Moral injury as a transdiagnostic risk factor for mental health problems in detained youth. Crim Justice Behav. 2023;51(2):194-212. doi:10.1177/00938548231208203
- DeCaro JB, Straka K, Malek N, Zalta AK. Sentenced to shame: moral injury exposure in former lifers. Psychol Trauma. 2024; 15(5):722-730. doi:10.1037/tra0001400
- Orak U, Kelton K, Vaughn MG, Tsai J, Pietrzak RH. Homelessness and contact with the criminal legal system among U.S. combat veterans: an exploration of potential mediating factors. Crim Justice Behav. 2022;50(3):392-409. doi:10.1177/00938548221140352
- Bronson J, Carson EA, Noonan M. Veterans in Prison and Jail, 2011-12. US Department of Justice, Bureau of Justice Statistics; Published December 2015. Accessed March 4, 2025. https://bjs.ojp.gov/content/pub/pdf/vpj1112.pdf
- Maruschak LM, Bronson J, Alper M. Veterans in Prison: Survey of Prison Inmates, 2016. US Department of Justice, Bureau of Justice Statistics; March 2021. Accessed March 4, 2025. https://bjs.ojp.gov/redirect-legacy/content/pub/pdf/vpspi16st.pdf
- Blodgett JC, Avoundjian T, Finlay AK, et al. Prevalence of mental health disorders among justiceinvolved veterans. Epidemiol Rev. 2015;37:163-176. doi:10.1093/epirev/mxu003
- Finlay AK, Owens MD, Taylor E, et al. A scoping review of military veterans involved in the criminal justice system and their health and healthcare. Health Justice. 2019;7(1):6. doi:10.1186/s40352-019-0086-9
- Holliday R, Martin WB, Monteith LL, Clark SC, LePage JP. Suicide among justice-involved veterans: a brief overview of extant research, theoretical conceptualization, and recommendations for future research. J Soc Distress Homeless. 2020;30(1):41-49. doi:10.1080/10530789.2019.1711306
- Wortzel HS, Binswanger IA, Anderson CA, Adler LE. Suicide among incarcerated veterans. J Am Acad Psychiatry Law. 2009;37(1):82-91.
- Desai A, Holliday R, Borges LM, et al. Facilitating successful reentry among justice-involved veterans: the role of veteran and offender identity. J Psychiatr Pract. 2021;27(1):52-60. doi:10.1097/PRA.0000000000000520
- Asencio EK, Burke PJ. Does incarceration change the criminal identity? A synthesis of labeling and identity theory perspectives on identity change. Sociol Perspect. 2011;54(2):163-182. doi:10.1525/sop.2011.54.2.163
- Borges LM, Desai A, Barnes SM, Johnson JPS. The role of social determinants of health in moral injury: implications and future directions. Curr Treat Options Psychiatry. 2022;9(3):202-214. doi:10.1007/s40501-022-00272-4
- Houle SA, Ein N, Gervasio J, et al. Measuring moral distress and moral injury: a systematic review and content analysis of existing scales. Clin Psychol Rev. 2024;108:102377. doi:10.1016/j.cpr.2023.102377
- Nash WP, Marino Carper TL, Mills MA, Au T, Goldsmith A, Litz BT. Psychometric evaluation of the moral injury events scale. Mil Med. 2013;178(6):646-652. doi:10.7205/MILMED-D-13-00017
- Zerach G, Ben-Yehuda A, Levi-Belz Y. Prospective associations between psychological factors, potentially morally injurious events, and psychiatric symptoms among Israeli combatants: the roles of ethical leadership and ethical preparation. Psychol Trauma. 2023;15(8):1367-1377. doi:10.1037/tra0001466
- American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. American Psychiatric Association; 2013.
- Weathers FW, Litz BT, Keane TM, Palmeri PA, Marx BP. The PTSD Checklist for DSM-5 (PCL-5). National Center for PTSD. Accessed March 4, 2025. www.ptsd.va.gov
- Bovin MJ, Marx BP, Weathers FW, et al. Psychometric properties of the PTSD checklist for diagnostic and statistical manual of mental disorders-fifth edition (PCL-5) in veterans. Psychol Assess. 2016;28(11):1379-1391. doi:10.1037/pas0000254
- Blevins CA, Weathers FW, Davis MT, Witte TK, Domino JL. The osttraumatic stress disorder checklist for DSM-5 (PCL- 5): development and initial psychometric evaluation. J Trauma Stress. 2015;28(6):489-498. doi:10.1002/jts.22059
- Kroenke K, Spi tzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16(9):606-613. doi:10.1046/j.1525-1497.2001.016009606.x
- Brown TA. Confirmatory Factor Analysis for Applied Research. 2nd ed. Guilford Press; 2015.
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- Schorr Y, Stein NR, Maguen S, Barnes JB, Bosch J, Litz BT. Sources of moral injury among war veterans: a qualitative evaluation. J Clin Psychol. 2018;74(12):2203-2218. doi:10.1002/jclp.22660
Following exposure to potentially morally injurious events (PMIEs), some individuals may experience moral injury, which represents negative psychological, social, behavioral, and occasionally spiritual impacts.1 The consequences of PMIE exposure and moral injury are well documented. Individuals may begin to question the goodness and trustworthiness of oneself, others, or the world.1 Examples of other sequelae include guilt, demoralization, spiritual pain, loss of trust in the self or others, and difficulties with forgiveness.2-6 In addition, prior studies have found that moral injury is associated with an increased risk of suicidal thoughts and behaviors, posttraumatic stress disorder (PTSD) symptoms, spiritual distress, and interpersonal difficulties.7-11
Moral injury was first conceptualized in relation to combat trauma. However in recent years it has been examined in other groups such as health care practitioners, educators, refugees, and law enforcement personnel.12-17 Furthermore, there has been a recent call for the study of moral injury in other understudied groups. One such group is legal-involved individuals, defined as those who are currently involved or previously involved in the criminal justice system (ie, arrests, incarceration, parole, and probation).1,18-22
Many veterans are also involved with the legal system. Specifically, veterans currently comprise about 8% of the incarcerated US population, with an estimated > 180,000 veterans in prisons or jails and even more on parole or probation.23,24 Legal-involved veterans may be at heightened risk for homelessness, suicide, unemployment, and high prevalence rates of psychiatric diagnoses.25-28
Limited research has explored exposure to PMIEs as part of the legal process and the resulting expression of moral injury. The circumstances leading to incarceration, interactions with the US legal system, the environment of prison itself, and the subsequent challenges faced by legal-involved individuals after release all provide ample opportunity for PMIEs to occur.18 For example, engaging in a criminal act may represent a PMIE, particularly in violent offenses that involve harm to another individual. Moreover, the process of being convicted and charged with an offense may serve as a powerful reminder of the PMIE and tie this event to the individual’s identity and future. Furthermore, the physical and social environment of prison itself (eg, being surrounded by other offenders, witnessing the perpetration of violence, participating in violence for survival) presents a myriad of opportunities for PMIEs to occur.18
The consequences of PMIEs in the context of legal involvement may also have bearing on a touchstone of moral injury: changes in one’s schema of the self and world.4 At a societal level, legal-involved individuals are, by definition, deemed “guilty” and held culpable for their offense, which may reinforce a negative change in one’s view of self and the world.29 In line with identity theory, external negative appraisals about legal-involved individuals (eg, they are a danger to society, they cannot be trusted to do the right thing) may influence their self-perception.30 Furthermore, the affective characteristics often found in the context of moral injury (eg, guilt, shame, anger, contempt) may be exacerbated by legal involvement.29 Personal feelings of guilt and shame may be reinforced by receiving a verdict and sentence, as well as the negative perceptions of individuals around them (eg, disapproval from prior sources of social support). Additionally, feelings of betrayal and distrust towards the legal system may arise.
In sum, legal-involved veterans incur increased risk of moral injury due to the potential for exposure to PMIEs across multiple time points (eg, prior to military service, during military service, during arrest/sentencing, during imprisonment, and postincarceration). The stigma that accompanies legal involvement may limit access to treatment or a willingness to seek treatment for distress related to moral injury.29 Additionally, repeated exposure to PMIEs and resulting moral injury may compound over time, potentially exacerbating psychosocial functioning and increasing the risk for psychosocial stressors (eg, homelessness, unemployment) and mental health disorders (eg, depression, substance misuse).31
Although numerous measures of moral injury have been developed, most require that respondents consider a specific context (eg, military experiences).32 Therefore, study of legal-related moral injury requires adaptation of existing instruments to the legal context. The original and most commonly used scale of moral injury is the Moral Injury Events Scale (MIES).33 The MIES scales was originally developed to measure moral injury in military-related contexts but has since been adapted as a measure of exposure to context-specific PMIEs.34
Unfortunately, there are no validated measures for assessing legal-related moral injury. Such a gap in understanding is problematic, as it may impact measurement of the prevalence of PMIEs in both clinical and research settings for this at-risk population. The goal of this study was to conduct a psychometric evaluation of an adapted version of the MIES for legal-involved persons (MIES-LIP).
METHODS
A total of 177 veterans from the US Department of Veterans Affairs (VA) North Texas Health Care System were contacted for study enrollment between November 2020 and June 2021, yielding a final sample of 100 legal-involved veteran participants. Adults aged ≥ 18 years who were US military veterans and had ≥ 1 prior felony conviction resulting in incarceration were included. Participants were excluded if they had symptoms of psychosis that would preclude meaningful participation.
The study collected data on participants’ demographic and clinical characteristics using a semistructured survey instrument. Each participant completed an instructor-led questionnaire in a session that lasted about 1.5 hours. Participants who completed the visit in person received a $50 cash voucher for their time. Participants who were unable to meet with the study coordinator in person were able to complete the visit via telephone and received a $25 digital gift card. Of the total 100 participants, 79 participants completed the interview in person, and 21 completed by telephone. No significant differences were found in assessment measures between administration methods. Written informed consent was obtained during all in-person visits. For those completing via telephone, a waiver of written informed consent was obtained. This study was approved by the VA North Texas Health Care System’s Institutional Review Board.
Measures
The Moral Injury Events Scale (MIES) is a 9-item self-report measure that assesses exposure to PMIEs.33 Respondents rate their agreement with each item on a 6-point Likert scale (strongly disagree to strongly agree), with higher scores indicating greater moral injury. The MIES has a 2-factor structure: Factor 1 has 6 items on perceived transgressions and Factor 2 has 3 items on perceived betrayals.33
Creation of Legal-Involved Moral Injury Measure. To create the MIES-LIP, items and instructions from the MIES were modified to address moral injury in the context of legal involvement.33 Adaptations were finalized following consultation and approval by the authors of the original measure. Specifically, the instructions were changed to: “Please respond to these items based specifically in the context of your involvement with the legal system.” The instructions clarified that legal involvement could include experiences related to committing an offense, legal proceedings and sentencing, incarceration, or transitioning out of the legal system. This differs from the original measure, which focused on military experiences, with instructions stating: “Please respond to these items based specifically in the context of your military service (ie, events and experiences during enlistment, deployment, combat, etc).”
Other measures. The study collected data on demographic characteristics including sex, race and ethnicity, marital status, military service, combat experience, and legal involvement. PTSD symptom severity, based on the criteria from the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), was assessed using the PTSD Checklist for DSM-5 (PCL-5).35,36 The PCL-5 is a 20-item self-report measure in which item scores are summed to create a total score. The PCL-5 has demonstrated strong psychometric properties, including good internal consistency, test-retest reliability convergent validity, and discriminant validity.37,38
Depressive symptom severity was measured using the Personal Health Questionnaire-9 (PHQ-9).39 The PHQ-9 is a 9-item self-report measure where item scores summed to create a total score. The PHQ-9 has demonstrated strong psychometric properties, including internal consistency and test-retest reliability.39
STATISTICAL METHODS
Descriptive statistics (mean and standard deviation for continuous variables; frequencies and percentages for categorical variables) were used to describe the study sample. Factor analysis was conducted to evaluate the psychometric properties of the MIES-LIP. Confirmatory factor analysis (CFA) was used to determine whether the MEIS-LIP had a similar factor structure to the MIES.40 Criteria for fit indices used for CFA include the Comparative Fit Index (CFI; values of > 0.95 suggest good fit), Tucker-Lewis index (TLI; values of > 0.95 suggest a good fit), root mean square error of approximation (RMSEA; values of ≥ 0.06 suggest good fit), and standardized root mean square residual (SRMR; values of ≥ 0.08 suggest good fit). With insufficient fit, subsequent exploratory factor analysis was conducted using maximum likelihood estimation with an Oblimin rotation. The Kaiser rule and a scree plot were considered when defining the factor structure. Reliability was evaluated using the McDonald omega coefficient test. Convergent validity was assessed through the association between adapted measures and other clinical measures (ie, PCL-5, PHQ-9). In addition, associations between the PCL-5 and PHQ-9 were examined as they related to the MIES and MIES-LIP.
RESULTS
Table 1 describes demographic characteristics of the study sample. Rates of potentially morally injurious experiences and the expression of moral injury in the legal context are presented in Table 2. Witnessing PMIEs while in the legal system was nearly ubiquitous, with > 90% of the sample endorsing this experience. More than half of the sample also endorsed engaging in morally injurious behavior by commission or omission, as well as experiencing betrayal while involved with the legal system.


Factor Analysis
Confirmatory factor analysis (CFA) was utilized to test the factor structure of the adapted MIES-LIP in our sample compared to the published factor structures of the MIES.33 Results did not support the established factor structure. Analysis yielded unacceptable CFI (0.79), TLI (0.70), SRMR (0.14), and RMSEA (0.21). The unsatisfactory results of CFA warranted follow-up exploratory factor analysis (EFA) to examine the factor structure of the moral injury scales in this sample.
EFA of MIES-LIP
The factor structure of the MIES-LIP was examined using EFA. The factorability of the data was examined using the Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO value = 0.75) and Bartlett Test of Sphericity (X2 = 525.41; P < .001), both of which suggested that the data were appropriate for factor analysis. The number of factors to retain was selected based on the Kaiser criterion.41 After extraction, an Oblimin rotation was applied, given that we expected factors to be correlated. A 2-factor solution was found, explaining 65.76% of the common variance. All 9 items were retained as they had factor loadings > 0.30. Factor 1, comprised self-directed moral injury questions (3-6). Factor 2 comprised other directed moral injury questions (1, 2, 7-9) (Table 3). The factor correlation coefficient between Factor 1 and Factor 2 was 0.34, which supports utilizing an oblique rotation.

Reliability. We examined the reliability of the adapted MIES-LIP using measures of internal consistency, with both MIES-LIP factors demonstrating good reliability. The internal consistency of both factors of the MIES-LIP were found to be good (self-directed moral injury: Ω = 0.89; other-directed moral injury: Ω = 0.83).
Convergent Validity
Association between moral injury scales. A significant, moderate correlation was observed between all subscales of the MIES and MIES-LIP. Specifically, the self-directed moral injury factor of the MIES-LIP was associated with both the perceived transgressions (r = 0.41, P < .001) and the MIES perceived betrayals factors (r = 0.25, P < .05). Similarly, the other-directed moral injury factor of the MIES-LIP was associated with both the MIES perceived transgressions (r = 0.45, P < .001) and the MIES perceived betrayals factors (r = 0.45, P < .001).
Association with PTSD symptoms. All subscales of both the MIES and MIES-LIP were associated with PTSD symptom severity. The MIES perceived transgressions factor (r = 0.43, P < .001) and the perceived betrayals factor of the MIES (r = 0.39, P < .001) were moderately associated with the PCL-5. Mirroring this, the “self-directed moral injury” factor of the MIESLIP (r = 0.44, P < .001) and the “other-directed moral injury” factor of the MIES-LIP (r = 0.42, P < .001) were also positively associated with PCL-5.
Association with depression symptoms. All subscales of the MIES and MIES-LIP were also associated with depressive symptoms. The MIES perceived transgressions factor (r = 0.27, P < .01) and the MIES perceived betrayals factor (r = 0.23, P < .05) had a small association with the PHQ-9. In addition, the self-directed moral injury factor of the MIES-LIP (r = 0.40, P < .001) and the other-directed moral injury factor of the MIES-LIP (r = 0.31, P < .01) had small to moderate associations with the PCL-5.
DISCUSSION
Potentially morally injurious events appear to be a salient factor affecting legal-involved veterans. Among our sample, the vast majority of legal-involved veterans endorsed experiencing both legal- and military-related PMIEs. Witnessing or participating in a legal-related PMIE appears to be widespread among those who have experienced incarceration. The MIES-LIP yielded a 2-factor structure: self-directed moral injury and other-directed moral injury, in the evaluated population. The MIES-LIP showed similar psychometric performance to the MIES in our sample. Specifically, the MIES-LIP had good reliability and adequate convergent validity. While CFA did not confirm the anticipated factor structure of the MIES-LIP within our sample, EFA showed similarities in factor structure between the original and adapted measures. While further research and validation are needed, preliminary results show promise of the MIES-LIP in assessing legal-related moral injury.
Originally, the MIES was found to have a 2-factor structure, defined by perceived transgressions and perceived betrayals.33 However, additional research has identified a 3-factor structure, where the betrayal factor is maintained, and the transgressions factor is divided into transgressions by others and by self.8 The factor structure of the MIES-LIP was more closely related to the factor structure, with transgressions by others and betrayal mapped onto the same factor (ie, other-directed moral injury).8 While further research is needed, it is possible that the nature of morally injurious events experienced in legal contexts are experienced more in terms of self vs other, compared to morally injurious events experienced by veterans or active-duty service members.
Accurately identifying the types of moral injury experienced in a legal context may be important for determining the differences in drivers of legal-related moral injury compared to military-related moral injury. For example, self-directed moral injury in legal contexts may include a variety of actions the individual initiated that led to conviction and incarceration (eg, a criminal offense), as well as behaviors performed or witnessed while incarcerated (eg, engaging in violence). Inconsistent with military populations where other-directed moral injury clusters with self-directed moral injury, other-directed moral injury clustered with betrayal in legal contexts in our sample. This discrepancy may result from differences in identification with the military vs legal system. When veterans witness fellow service members engaging in PMIEs (eg, physical violence towards civilians in a military setting), this may be similar to self-directed moral injury due to the veteran’s identification with the same military system as the perpetrator.42 When legal-involved veterans witness other incarcerated individuals engaging in PMIEs (eg, physical violence toward other inmates), this may be experienced as similar to betrayal due to lack of personal identification with the criminal-legal system. Additional research is needed to better understand how self- and other-related moral injury are associated with betrayal in legal contexts.
Another potential driver of legal-related moral injury may be culpability. In order for moral injury to occur, an individual must perceive that something has taken place that deeply violated their sense of right and wrong.1 In terms of criminal offenses or even engaging in violent behavior while incarcerated, the potential for moral injury may differ based on whether an individual views themselves as culpable for the act(s).29 This may further distinguish between self-directed and other-directed moral injury in legal contexts. In situations where the individual views themselves as culpable, self-directed moral injury may be higher. In situations where the individual does not view themselves as culpable, other-directed moral injury may be higher based on the perception that the legal system is unfairly punishing them. Further research is needed to clarify how an individual’s view of their culpability relates to moral injury, as well as to elucidate which aspects of military service and legal involvement are most closely associated with moral injury among legal-involved veterans.
While this study treated legal-related and military-related moral injury as distinct, it is possible moral injury may have a cumulative effect over time with individuals experiencing morally injurious events across different contexts (eg, military, legal involvement). This, in turn, may compound risk for moral injury. These cumulative experiences may result in increased negative outcomes such as exacerbated psychiatric symptoms, substance misuse, and elevated suicide risk. Future studies should examine differences between groups who have experienced moral injury in differing contexts, as well as those with multiple sources of moral injury.
Limitations
The sample for this study included only veterans. The number of veterans incarcerated is large and the focus on veterans also allowed for a more robust comparison of moral injury related to the legal system and the more traditional military-related moral injury. However, the generalizability of the findings to nonveterans cannot be assured. The study used a relatively small sample (N = 100), which was overwhelmingly male. Although the PCL-5 was utilized to examine traumatic stress symptoms, this measure was not anchored to a specific criterion A trauma nor was it anchored specifically to a morally injurious experience. For all participants, their most recent military service preceded their most recent legal involvement which could affect the associations between variables. Furthermore, while all participants endorsed prior legal involvement, many participants reported no combat exposure.
CONCLUSIONS
This study resulted in several key findings. First, legal-involved veterans endorsed high rates of experiencing legal-related morally injurious experiences. Second, our adapted measure displayed adequate psychometric strength and suggests that legal-related moral injury is a salient and distinct phenomenon affecting legal-involved veterans. These items may not capture all the nuances of legal-related moral injury. Qualitative interviews with legal-involved persons may help identify relevant areas of legal-related moral injury not reflected in the current instrument. The MIES-LIP represents a practical measure that may help clinicians identify and address legal-related moral injury when working with legal-involved veterans. Given the high prevalence of PMIEs among legal-involved veterans, further examination of whether current interventions for moral injury and novel treatments being developed are effective for this population is needed.
Following exposure to potentially morally injurious events (PMIEs), some individuals may experience moral injury, which represents negative psychological, social, behavioral, and occasionally spiritual impacts.1 The consequences of PMIE exposure and moral injury are well documented. Individuals may begin to question the goodness and trustworthiness of oneself, others, or the world.1 Examples of other sequelae include guilt, demoralization, spiritual pain, loss of trust in the self or others, and difficulties with forgiveness.2-6 In addition, prior studies have found that moral injury is associated with an increased risk of suicidal thoughts and behaviors, posttraumatic stress disorder (PTSD) symptoms, spiritual distress, and interpersonal difficulties.7-11
Moral injury was first conceptualized in relation to combat trauma. However in recent years it has been examined in other groups such as health care practitioners, educators, refugees, and law enforcement personnel.12-17 Furthermore, there has been a recent call for the study of moral injury in other understudied groups. One such group is legal-involved individuals, defined as those who are currently involved or previously involved in the criminal justice system (ie, arrests, incarceration, parole, and probation).1,18-22
Many veterans are also involved with the legal system. Specifically, veterans currently comprise about 8% of the incarcerated US population, with an estimated > 180,000 veterans in prisons or jails and even more on parole or probation.23,24 Legal-involved veterans may be at heightened risk for homelessness, suicide, unemployment, and high prevalence rates of psychiatric diagnoses.25-28
Limited research has explored exposure to PMIEs as part of the legal process and the resulting expression of moral injury. The circumstances leading to incarceration, interactions with the US legal system, the environment of prison itself, and the subsequent challenges faced by legal-involved individuals after release all provide ample opportunity for PMIEs to occur.18 For example, engaging in a criminal act may represent a PMIE, particularly in violent offenses that involve harm to another individual. Moreover, the process of being convicted and charged with an offense may serve as a powerful reminder of the PMIE and tie this event to the individual’s identity and future. Furthermore, the physical and social environment of prison itself (eg, being surrounded by other offenders, witnessing the perpetration of violence, participating in violence for survival) presents a myriad of opportunities for PMIEs to occur.18
The consequences of PMIEs in the context of legal involvement may also have bearing on a touchstone of moral injury: changes in one’s schema of the self and world.4 At a societal level, legal-involved individuals are, by definition, deemed “guilty” and held culpable for their offense, which may reinforce a negative change in one’s view of self and the world.29 In line with identity theory, external negative appraisals about legal-involved individuals (eg, they are a danger to society, they cannot be trusted to do the right thing) may influence their self-perception.30 Furthermore, the affective characteristics often found in the context of moral injury (eg, guilt, shame, anger, contempt) may be exacerbated by legal involvement.29 Personal feelings of guilt and shame may be reinforced by receiving a verdict and sentence, as well as the negative perceptions of individuals around them (eg, disapproval from prior sources of social support). Additionally, feelings of betrayal and distrust towards the legal system may arise.
In sum, legal-involved veterans incur increased risk of moral injury due to the potential for exposure to PMIEs across multiple time points (eg, prior to military service, during military service, during arrest/sentencing, during imprisonment, and postincarceration). The stigma that accompanies legal involvement may limit access to treatment or a willingness to seek treatment for distress related to moral injury.29 Additionally, repeated exposure to PMIEs and resulting moral injury may compound over time, potentially exacerbating psychosocial functioning and increasing the risk for psychosocial stressors (eg, homelessness, unemployment) and mental health disorders (eg, depression, substance misuse).31
Although numerous measures of moral injury have been developed, most require that respondents consider a specific context (eg, military experiences).32 Therefore, study of legal-related moral injury requires adaptation of existing instruments to the legal context. The original and most commonly used scale of moral injury is the Moral Injury Events Scale (MIES).33 The MIES scales was originally developed to measure moral injury in military-related contexts but has since been adapted as a measure of exposure to context-specific PMIEs.34
Unfortunately, there are no validated measures for assessing legal-related moral injury. Such a gap in understanding is problematic, as it may impact measurement of the prevalence of PMIEs in both clinical and research settings for this at-risk population. The goal of this study was to conduct a psychometric evaluation of an adapted version of the MIES for legal-involved persons (MIES-LIP).
METHODS
A total of 177 veterans from the US Department of Veterans Affairs (VA) North Texas Health Care System were contacted for study enrollment between November 2020 and June 2021, yielding a final sample of 100 legal-involved veteran participants. Adults aged ≥ 18 years who were US military veterans and had ≥ 1 prior felony conviction resulting in incarceration were included. Participants were excluded if they had symptoms of psychosis that would preclude meaningful participation.
The study collected data on participants’ demographic and clinical characteristics using a semistructured survey instrument. Each participant completed an instructor-led questionnaire in a session that lasted about 1.5 hours. Participants who completed the visit in person received a $50 cash voucher for their time. Participants who were unable to meet with the study coordinator in person were able to complete the visit via telephone and received a $25 digital gift card. Of the total 100 participants, 79 participants completed the interview in person, and 21 completed by telephone. No significant differences were found in assessment measures between administration methods. Written informed consent was obtained during all in-person visits. For those completing via telephone, a waiver of written informed consent was obtained. This study was approved by the VA North Texas Health Care System’s Institutional Review Board.
Measures
The Moral Injury Events Scale (MIES) is a 9-item self-report measure that assesses exposure to PMIEs.33 Respondents rate their agreement with each item on a 6-point Likert scale (strongly disagree to strongly agree), with higher scores indicating greater moral injury. The MIES has a 2-factor structure: Factor 1 has 6 items on perceived transgressions and Factor 2 has 3 items on perceived betrayals.33
Creation of Legal-Involved Moral Injury Measure. To create the MIES-LIP, items and instructions from the MIES were modified to address moral injury in the context of legal involvement.33 Adaptations were finalized following consultation and approval by the authors of the original measure. Specifically, the instructions were changed to: “Please respond to these items based specifically in the context of your involvement with the legal system.” The instructions clarified that legal involvement could include experiences related to committing an offense, legal proceedings and sentencing, incarceration, or transitioning out of the legal system. This differs from the original measure, which focused on military experiences, with instructions stating: “Please respond to these items based specifically in the context of your military service (ie, events and experiences during enlistment, deployment, combat, etc).”
Other measures. The study collected data on demographic characteristics including sex, race and ethnicity, marital status, military service, combat experience, and legal involvement. PTSD symptom severity, based on the criteria from the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), was assessed using the PTSD Checklist for DSM-5 (PCL-5).35,36 The PCL-5 is a 20-item self-report measure in which item scores are summed to create a total score. The PCL-5 has demonstrated strong psychometric properties, including good internal consistency, test-retest reliability convergent validity, and discriminant validity.37,38
Depressive symptom severity was measured using the Personal Health Questionnaire-9 (PHQ-9).39 The PHQ-9 is a 9-item self-report measure where item scores summed to create a total score. The PHQ-9 has demonstrated strong psychometric properties, including internal consistency and test-retest reliability.39
STATISTICAL METHODS
Descriptive statistics (mean and standard deviation for continuous variables; frequencies and percentages for categorical variables) were used to describe the study sample. Factor analysis was conducted to evaluate the psychometric properties of the MIES-LIP. Confirmatory factor analysis (CFA) was used to determine whether the MEIS-LIP had a similar factor structure to the MIES.40 Criteria for fit indices used for CFA include the Comparative Fit Index (CFI; values of > 0.95 suggest good fit), Tucker-Lewis index (TLI; values of > 0.95 suggest a good fit), root mean square error of approximation (RMSEA; values of ≥ 0.06 suggest good fit), and standardized root mean square residual (SRMR; values of ≥ 0.08 suggest good fit). With insufficient fit, subsequent exploratory factor analysis was conducted using maximum likelihood estimation with an Oblimin rotation. The Kaiser rule and a scree plot were considered when defining the factor structure. Reliability was evaluated using the McDonald omega coefficient test. Convergent validity was assessed through the association between adapted measures and other clinical measures (ie, PCL-5, PHQ-9). In addition, associations between the PCL-5 and PHQ-9 were examined as they related to the MIES and MIES-LIP.
RESULTS
Table 1 describes demographic characteristics of the study sample. Rates of potentially morally injurious experiences and the expression of moral injury in the legal context are presented in Table 2. Witnessing PMIEs while in the legal system was nearly ubiquitous, with > 90% of the sample endorsing this experience. More than half of the sample also endorsed engaging in morally injurious behavior by commission or omission, as well as experiencing betrayal while involved with the legal system.


Factor Analysis
Confirmatory factor analysis (CFA) was utilized to test the factor structure of the adapted MIES-LIP in our sample compared to the published factor structures of the MIES.33 Results did not support the established factor structure. Analysis yielded unacceptable CFI (0.79), TLI (0.70), SRMR (0.14), and RMSEA (0.21). The unsatisfactory results of CFA warranted follow-up exploratory factor analysis (EFA) to examine the factor structure of the moral injury scales in this sample.
EFA of MIES-LIP
The factor structure of the MIES-LIP was examined using EFA. The factorability of the data was examined using the Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO value = 0.75) and Bartlett Test of Sphericity (X2 = 525.41; P < .001), both of which suggested that the data were appropriate for factor analysis. The number of factors to retain was selected based on the Kaiser criterion.41 After extraction, an Oblimin rotation was applied, given that we expected factors to be correlated. A 2-factor solution was found, explaining 65.76% of the common variance. All 9 items were retained as they had factor loadings > 0.30. Factor 1, comprised self-directed moral injury questions (3-6). Factor 2 comprised other directed moral injury questions (1, 2, 7-9) (Table 3). The factor correlation coefficient between Factor 1 and Factor 2 was 0.34, which supports utilizing an oblique rotation.

Reliability. We examined the reliability of the adapted MIES-LIP using measures of internal consistency, with both MIES-LIP factors demonstrating good reliability. The internal consistency of both factors of the MIES-LIP were found to be good (self-directed moral injury: Ω = 0.89; other-directed moral injury: Ω = 0.83).
Convergent Validity
Association between moral injury scales. A significant, moderate correlation was observed between all subscales of the MIES and MIES-LIP. Specifically, the self-directed moral injury factor of the MIES-LIP was associated with both the perceived transgressions (r = 0.41, P < .001) and the MIES perceived betrayals factors (r = 0.25, P < .05). Similarly, the other-directed moral injury factor of the MIES-LIP was associated with both the MIES perceived transgressions (r = 0.45, P < .001) and the MIES perceived betrayals factors (r = 0.45, P < .001).
Association with PTSD symptoms. All subscales of both the MIES and MIES-LIP were associated with PTSD symptom severity. The MIES perceived transgressions factor (r = 0.43, P < .001) and the perceived betrayals factor of the MIES (r = 0.39, P < .001) were moderately associated with the PCL-5. Mirroring this, the “self-directed moral injury” factor of the MIESLIP (r = 0.44, P < .001) and the “other-directed moral injury” factor of the MIES-LIP (r = 0.42, P < .001) were also positively associated with PCL-5.
Association with depression symptoms. All subscales of the MIES and MIES-LIP were also associated with depressive symptoms. The MIES perceived transgressions factor (r = 0.27, P < .01) and the MIES perceived betrayals factor (r = 0.23, P < .05) had a small association with the PHQ-9. In addition, the self-directed moral injury factor of the MIES-LIP (r = 0.40, P < .001) and the other-directed moral injury factor of the MIES-LIP (r = 0.31, P < .01) had small to moderate associations with the PCL-5.
DISCUSSION
Potentially morally injurious events appear to be a salient factor affecting legal-involved veterans. Among our sample, the vast majority of legal-involved veterans endorsed experiencing both legal- and military-related PMIEs. Witnessing or participating in a legal-related PMIE appears to be widespread among those who have experienced incarceration. The MIES-LIP yielded a 2-factor structure: self-directed moral injury and other-directed moral injury, in the evaluated population. The MIES-LIP showed similar psychometric performance to the MIES in our sample. Specifically, the MIES-LIP had good reliability and adequate convergent validity. While CFA did not confirm the anticipated factor structure of the MIES-LIP within our sample, EFA showed similarities in factor structure between the original and adapted measures. While further research and validation are needed, preliminary results show promise of the MIES-LIP in assessing legal-related moral injury.
Originally, the MIES was found to have a 2-factor structure, defined by perceived transgressions and perceived betrayals.33 However, additional research has identified a 3-factor structure, where the betrayal factor is maintained, and the transgressions factor is divided into transgressions by others and by self.8 The factor structure of the MIES-LIP was more closely related to the factor structure, with transgressions by others and betrayal mapped onto the same factor (ie, other-directed moral injury).8 While further research is needed, it is possible that the nature of morally injurious events experienced in legal contexts are experienced more in terms of self vs other, compared to morally injurious events experienced by veterans or active-duty service members.
Accurately identifying the types of moral injury experienced in a legal context may be important for determining the differences in drivers of legal-related moral injury compared to military-related moral injury. For example, self-directed moral injury in legal contexts may include a variety of actions the individual initiated that led to conviction and incarceration (eg, a criminal offense), as well as behaviors performed or witnessed while incarcerated (eg, engaging in violence). Inconsistent with military populations where other-directed moral injury clusters with self-directed moral injury, other-directed moral injury clustered with betrayal in legal contexts in our sample. This discrepancy may result from differences in identification with the military vs legal system. When veterans witness fellow service members engaging in PMIEs (eg, physical violence towards civilians in a military setting), this may be similar to self-directed moral injury due to the veteran’s identification with the same military system as the perpetrator.42 When legal-involved veterans witness other incarcerated individuals engaging in PMIEs (eg, physical violence toward other inmates), this may be experienced as similar to betrayal due to lack of personal identification with the criminal-legal system. Additional research is needed to better understand how self- and other-related moral injury are associated with betrayal in legal contexts.
Another potential driver of legal-related moral injury may be culpability. In order for moral injury to occur, an individual must perceive that something has taken place that deeply violated their sense of right and wrong.1 In terms of criminal offenses or even engaging in violent behavior while incarcerated, the potential for moral injury may differ based on whether an individual views themselves as culpable for the act(s).29 This may further distinguish between self-directed and other-directed moral injury in legal contexts. In situations where the individual views themselves as culpable, self-directed moral injury may be higher. In situations where the individual does not view themselves as culpable, other-directed moral injury may be higher based on the perception that the legal system is unfairly punishing them. Further research is needed to clarify how an individual’s view of their culpability relates to moral injury, as well as to elucidate which aspects of military service and legal involvement are most closely associated with moral injury among legal-involved veterans.
While this study treated legal-related and military-related moral injury as distinct, it is possible moral injury may have a cumulative effect over time with individuals experiencing morally injurious events across different contexts (eg, military, legal involvement). This, in turn, may compound risk for moral injury. These cumulative experiences may result in increased negative outcomes such as exacerbated psychiatric symptoms, substance misuse, and elevated suicide risk. Future studies should examine differences between groups who have experienced moral injury in differing contexts, as well as those with multiple sources of moral injury.
Limitations
The sample for this study included only veterans. The number of veterans incarcerated is large and the focus on veterans also allowed for a more robust comparison of moral injury related to the legal system and the more traditional military-related moral injury. However, the generalizability of the findings to nonveterans cannot be assured. The study used a relatively small sample (N = 100), which was overwhelmingly male. Although the PCL-5 was utilized to examine traumatic stress symptoms, this measure was not anchored to a specific criterion A trauma nor was it anchored specifically to a morally injurious experience. For all participants, their most recent military service preceded their most recent legal involvement which could affect the associations between variables. Furthermore, while all participants endorsed prior legal involvement, many participants reported no combat exposure.
CONCLUSIONS
This study resulted in several key findings. First, legal-involved veterans endorsed high rates of experiencing legal-related morally injurious experiences. Second, our adapted measure displayed adequate psychometric strength and suggests that legal-related moral injury is a salient and distinct phenomenon affecting legal-involved veterans. These items may not capture all the nuances of legal-related moral injury. Qualitative interviews with legal-involved persons may help identify relevant areas of legal-related moral injury not reflected in the current instrument. The MIES-LIP represents a practical measure that may help clinicians identify and address legal-related moral injury when working with legal-involved veterans. Given the high prevalence of PMIEs among legal-involved veterans, further examination of whether current interventions for moral injury and novel treatments being developed are effective for this population is needed.
- Griffin BJ, Purcell N, Burkman K, et al. Moral injury: an integrative review. J Trauma Stress. 2019;32(3):350-362. doi:10.1002/jts.22362
- Currier JM, Holland JM, Malott J. Moral injury, meaning making, and mental health in returning veterans. J Clin Psychol. 2015;71(3):229-240. doi:10.1002/jclp.22134
- Jinkerson JD. Defining and assessing moral injury: a syndrome perspective. Traumatology. 2016;22(2):122-130. doi:10.1037/trm0000069
- Litz BT, Stein N, Delaney E, et al. Moral injury and moral repair in war veterans: a preliminary model and intervention strategy. Clin Psychol Rev. 2009;29(8):695-706. doi:10.1016/j.cpr.2009.07.003
- Maguen S, Litz B. Moral injury in veterans of war. PTSD Res Q. 2012;23(1):1-6. www.vva1071.org/uploads/3/4/4/6/34460116/moral_injury_in_veterans_of_war.pdf
- Drescher KD, Foy DW, Kelly C, Leshner A, Schutz K, Litz B. An exploration of the viability and usefulness of the construct of moral injury in war veterans. Traumatology. 2011;17(1):8-13. doi:10.1177/1534765610395615
- Wisco BE, Marx BP, May CL, et al. Moral injury in U.S. combat veterans: results from the national health and resilience in veterans study. Depress Anxiety. 2017; 34(4):340-347. doi:10.1002/da.22614
- Bryan CJ, Bryan AO, Anestis MD, et al. Measuring moral injury: psychometric properties of the moral injury events scale in two military samples. Assessment. 2016;23(5):557- 570. doi:10.1177/1073191115590855
- Currier JM, Smith PN, Kuhlman S. Assessing the unique role of religious coping in suicidal behavior among U.S. Iraq and Afghanistan veterans. Psychol Relig Spiritual. 2017;9(1):118-123. doi:10.1037/rel0000055
- Kopacz MS, Connery AL, Bishop TM, et al. Moral injury: a new challenge for complementary and alternative medicine. Complement Ther Med. 2016;24:29-33. doi:10.1016/j.ctim.2015.11.003
- Vargas AF, Hanson T, Kraus D, Drescher K, Foy D. Moral injury themes in combat veterans’ narrative responses from the national vietnam veterans’ readjustment study. Traumatology. 2013;19(3):243-250. doi:10.1177/1534765613476099
- Borges LM, Barnes SM, Farnsworth JK, Bahraini NH, Brenner LA. A commentary on moral injury among health care providers during the COVID-19 pandemic. Psychol Trauma. 2020;12(S1):S138-S140. doi:10.1037/tra0000698
- Borges LM, Holliday R, Barnes SM, et al. A longitudinal analysis of the role of potentially morally injurious events on COVID-19-related psychosocial functioning among healthcare providers. PLoS One. 2021;16(11):e0260033. doi:10.1371/journal.pone.0260033
- Currier JM, Holland JM, Rojas-Flores L, Herrera S, Foy D. Morally injurious experiences and meaning in Salvadorian teachers exposed to violence. Psychol Trauma. 2015;7(1):24-33. doi:10.1037/a0034092
- Nickerson A, Schnyder U, Bryant RA, Schick M, Mueller J, Morina N. Moral injury in traumatized refugees. Psychother Psychosom. 2015;84(2):122-123. doi:10.1159/000369353
- Papazoglou K, Chopko B. The role of moral suffering (moral distress and moral injury) in police compassion fatigue and PTSD: An unexplored topic. Front Psychol. 2017;8:1999. doi:10.3389/fpsyg.2017.01999
- Papazoglou K, Blumberg DM, Chiongbian VB, et al. The role of moral injury in PTSD among law enforcement officers: a brief report. Front Psychol. 2020;11:310. doi:10.3389/fpsyg.2020.00310
- Martin WB, Holliday R, LePage JP. Trauma and diversity: moral injury among justice involved veterans: an understudied clinical concern. Stresspoints. 2020;33(5).
- Currier JM, Drescher KD, Nieuwsma J. Future directions for addressing moral injury in clinical practice: concluding comments. In: Currier JM, Drescher KD, Nieuwsma J, eds. Addressing Moral Injury in Clinical Practice. American Psychological Association; 2021:261-271. doi:10.1037/0000204-015
- Alexander AR, Mendez L, Kerig PK. Moral injury as a transdiagnostic risk factor for mental health problems in detained youth. Crim Justice Behav. 2023;51(2):194-212. doi:10.1177/00938548231208203
- DeCaro JB, Straka K, Malek N, Zalta AK. Sentenced to shame: moral injury exposure in former lifers. Psychol Trauma. 2024; 15(5):722-730. doi:10.1037/tra0001400
- Orak U, Kelton K, Vaughn MG, Tsai J, Pietrzak RH. Homelessness and contact with the criminal legal system among U.S. combat veterans: an exploration of potential mediating factors. Crim Justice Behav. 2022;50(3):392-409. doi:10.1177/00938548221140352
- Bronson J, Carson EA, Noonan M. Veterans in Prison and Jail, 2011-12. US Department of Justice, Bureau of Justice Statistics; Published December 2015. Accessed March 4, 2025. https://bjs.ojp.gov/content/pub/pdf/vpj1112.pdf
- Maruschak LM, Bronson J, Alper M. Veterans in Prison: Survey of Prison Inmates, 2016. US Department of Justice, Bureau of Justice Statistics; March 2021. Accessed March 4, 2025. https://bjs.ojp.gov/redirect-legacy/content/pub/pdf/vpspi16st.pdf
- Blodgett JC, Avoundjian T, Finlay AK, et al. Prevalence of mental health disorders among justiceinvolved veterans. Epidemiol Rev. 2015;37:163-176. doi:10.1093/epirev/mxu003
- Finlay AK, Owens MD, Taylor E, et al. A scoping review of military veterans involved in the criminal justice system and their health and healthcare. Health Justice. 2019;7(1):6. doi:10.1186/s40352-019-0086-9
- Holliday R, Martin WB, Monteith LL, Clark SC, LePage JP. Suicide among justice-involved veterans: a brief overview of extant research, theoretical conceptualization, and recommendations for future research. J Soc Distress Homeless. 2020;30(1):41-49. doi:10.1080/10530789.2019.1711306
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- Holliday R, Martin WB, Monteith LL, Clark SC, LePage JP. Suicide among justice-involved veterans: a brief overview of extant research, theoretical conceptualization, and recommendations for future research. J Soc Distress Homeless. 2020;30(1):41-49. doi:10.1080/10530789.2019.1711306
- Wortzel HS, Binswanger IA, Anderson CA, Adler LE. Suicide among incarcerated veterans. J Am Acad Psychiatry Law. 2009;37(1):82-91.
- Desai A, Holliday R, Borges LM, et al. Facilitating successful reentry among justice-involved veterans: the role of veteran and offender identity. J Psychiatr Pract. 2021;27(1):52-60. doi:10.1097/PRA.0000000000000520
- Asencio EK, Burke PJ. Does incarceration change the criminal identity? A synthesis of labeling and identity theory perspectives on identity change. Sociol Perspect. 2011;54(2):163-182. doi:10.1525/sop.2011.54.2.163
- Borges LM, Desai A, Barnes SM, Johnson JPS. The role of social determinants of health in moral injury: implications and future directions. Curr Treat Options Psychiatry. 2022;9(3):202-214. doi:10.1007/s40501-022-00272-4
- Houle SA, Ein N, Gervasio J, et al. Measuring moral distress and moral injury: a systematic review and content analysis of existing scales. Clin Psychol Rev. 2024;108:102377. doi:10.1016/j.cpr.2023.102377
- Nash WP, Marino Carper TL, Mills MA, Au T, Goldsmith A, Litz BT. Psychometric evaluation of the moral injury events scale. Mil Med. 2013;178(6):646-652. doi:10.7205/MILMED-D-13-00017
- Zerach G, Ben-Yehuda A, Levi-Belz Y. Prospective associations between psychological factors, potentially morally injurious events, and psychiatric symptoms among Israeli combatants: the roles of ethical leadership and ethical preparation. Psychol Trauma. 2023;15(8):1367-1377. doi:10.1037/tra0001466
- American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. American Psychiatric Association; 2013.
- Weathers FW, Litz BT, Keane TM, Palmeri PA, Marx BP. The PTSD Checklist for DSM-5 (PCL-5). National Center for PTSD. Accessed March 4, 2025. www.ptsd.va.gov
- Bovin MJ, Marx BP, Weathers FW, et al. Psychometric properties of the PTSD checklist for diagnostic and statistical manual of mental disorders-fifth edition (PCL-5) in veterans. Psychol Assess. 2016;28(11):1379-1391. doi:10.1037/pas0000254
- Blevins CA, Weathers FW, Davis MT, Witte TK, Domino JL. The osttraumatic stress disorder checklist for DSM-5 (PCL- 5): development and initial psychometric evaluation. J Trauma Stress. 2015;28(6):489-498. doi:10.1002/jts.22059
- Kroenke K, Spi tzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16(9):606-613. doi:10.1046/j.1525-1497.2001.016009606.x
- Brown TA. Confirmatory Factor Analysis for Applied Research. 2nd ed. Guilford Press; 2015.
- Kaiser HF. The application of electronic computers to factor analysis. Educ Psychol Meas. 1960;20(1):141-151. doi:10.1177/001316446002000116
- Schorr Y, Stein NR, Maguen S, Barnes JB, Bosch J, Litz BT. Sources of moral injury among war veterans: a qualitative evaluation. J Clin Psychol. 2018;74(12):2203-2218. doi:10.1002/jclp.22660
Examining Moral Injury in Legal-Involved Veterans: Psychometric Properties of the Moral Injury Events Scale
Examining Moral Injury in Legal-Involved Veterans: Psychometric Properties of the Moral Injury Events Scale