Geriatrics

Primary care practitioners (PCPs) in the US Department of Veterans Affairs (VA) provide care for patients with higher rates of many diseases—diabetes, heart disease, cancer, chronic obstructive pulmonary disease (COPD), and stroke—compared to the nonveteran population. ¹ Due to the medical complexities of these diseases, they are often misdiagnosed or not diagnosed at all.

COPD is hiding in plain sight, impacting quality of life and burdening US health care systems.² Research has yielded new treatments and evidence-based guidelines; however, COPD remains underdiagnosed. Only 13 million of the estimated 79 million US adults with COPD aged 20 to 79 years have been formally diagnosed.³ By the time patients are diagnosed, the disease is often advanced, and therapies are less effective. In 2 large studies of patients with COPD symptoms, later diagnosis was associated with worse outcomes.^4,5

Veterans have a higher prevalence of COPD (8%-19%) than nonveterans (6%), likely due to higher rates of smoking and service-related exposures, especially among veterans of post-9/11 conflicts.^6,7 Veterans do not always report symptoms and PCPs may not ask about symptoms, leading to underdiagnosis.⁸ The combination of high likelihood and underdetection of COPD presents a challenge and a target for VA quality improvement (QI).

The US Preventive Services Task Force (USPSTF) recommends against screening asymptomatic patients for COPD. However, both the USPSTF and the Global Initiative for Chronic Obstructive Lung Disease Report advocate for active case finding in primary care clinics to determine whether high-risk patients, such as smokers, experience COPD symptoms and warrant spirometry. ^9,10 To make early COPD diagnoses, clinicians may use questionnaires alone or in combination with handheld peak expiratory flow rate measurements.^11,12 Formal spirometry, considered the gold standard for COPD diagnosis, is ordered for patients who report COPD symptoms (ie, shortness of breath with exertion) or who have both COPD symptoms and reduced peak flow rates.

A systematic review and meta-analysis found that while the combination of questionnaires and peak flows was the more effective strategy overall, questionnaires alone were also valuable for identifying patients with possible COPD.¹³ Implementation of either screening method in primary care practices would be challenging. In a simulation study that applied chronic disease and preventive care guidelines to hypothetical patient panels, the time required for PCPs to provide guideline-recommended chronic and preventive care in addition to acute care far exceeded 8 hours per day, even in team-based settings.¹⁴ Overburdened PCPs are therefore unlikely to accept additional tasks like COPD case finding.

Why don’t patients report their pulmonary symptoms? Patients may not recognize the symptoms as evidence of COPD. Others may be afraid of a COPD diagnosis or the stigma that is associated with it.¹⁵ Perhaps they believe COPD treatment is ineffective because of lung damage from smoking. Some patients may not want to know if they have COPD, while others reduce activity levels to avoid symptoms.¹⁶

QUALITY IMPROVEMENT PROJECT

Given the high prevalence of COPD among veterans and the potential for underdiagnosis, VA Northeast Ohio Healthcare System (VANEOHS) internal medicine residents and faculty assessed the state of COPD diagnosis in its primary care clinic with a QI project in 2022. Patients in the clinic between August 1, 2015, and November 30, 2022, with an International Classification of Diseases-10 (ICD-10) COPD diagnosis code (J44) in the electronic health record were included. Of 157 included patients, 105 patients who had prior spirometry testing were excluded. Of the 52 patients with diagnosed COPD and no spirometry testing, 30 patients had computed tomography (CT) findings consistent with COPD (ie, airway thickening, emphysema, air trapping) that was performed for CT lung cancer screening (LCS).¹⁷ Twenty-three of these 30 patients were contacted by phone. All 23 were ever smokers and 13 reported COPD symptoms. The PCPs of the symptomatic patients were then contacted. Spirometry was ordered for all 13 patients and completed by 7. Three spirometry tests confirmed the COPD diagnosis. One PCP initiated inhaler therapy for a patient with newly diagnosed COPD.

All 11 PCPs of symptomatic patients were interviewed (many had > 1 symptomatic patient). They reported being unaware of patients’ COPD symptoms because the patients did not mention them, noting that screening for COPD was not a priority.

Role of Lung Cancer Screening

VA PCPs use electronic health record clinical reminders to track tests, consults, chronic disease education, cancer screenings, and routine health maintenance. A clinical reminder already exists (based on USPSTF recommendations) for LCS for patients aged 50 to 80 years who have a smoking history of 20 pack years. Patients who meet these criteria would also be considered high risk for COPD.

The VANEOHS QI project suggests that previously undiagnosed patients with findings of COPD on LCS may also have symptoms of COPD. Therefore, we wondered whether the LCS clinical reminder could serve a second purpose by prompting PCPs to ask veterans who meet LCS criteria about their COPD symptoms.

In 2022, about 13 million patients were eligible for LCS.¹⁸ Patients who qualify for LCS are at high risk for other cardiopulmonary disorders, such as COPD and coronary artery disease. Lung cancer is detected in only 1% of patients screened with CT at baseline. However, more often LCS yields evidence of additional cardiopulmonary disorders, such as emphysema or coronary artery calcifications. The International Early Lung Cancer Program (I-ELCAP) and the National Lung Cancer Screening Trial (NLST), which included > 79,000 patients, found evidence of emphysema on CT imaging in 24% and 31% of cases, respectively.^19,20 In both cohorts, > 80% of patients with emphysema on CT imaging had no prior history of COPD.

In a 2022 article summarizing the potential impact of CT LCS on COPD diagnosis, Mulshine et al suggest that detection of emphysema on CT LCS provides “earlier recognition for PCPs to identify patients who would benefit from detailed symptom screening to prompt spirometry for COPD detection” and additional motivation for tobacco cessation.²¹ The VANEOHS QI project was developed and implemented prior to I-ELCAP or NLST reporting results but reinforces the value of CT LCS for COPD diagnosis.

Early diagnosis of COPD remains challenging because PCPs do not ask, patients do not tell, and symptoms can easily be dismissed. However, earlier diagnosis of COPD in symptomatic patients improves outcomes.^3,4 To bridge this gap, VA PCPs and primary care patient aligned care teams (PACTs) need to commit to probing high-risk patients for COPD symptoms and ordering spirometry for those who are symptomatic. To accomplish this task, primary care teams need help.

The VANEOHS QI project confirmed that some patients with evidence of COPD on CT have symptoms of COPD that they did not share with their PCPs and suggests that LCS can be used as a dual action case finding method to screen both for lung cancer and COPD. We propose that patients who are eligible for LCS should also be probed for COPD symptoms at their clinic visits; for symptomatic patients, spirometry should be ordered, and COPD evidence-based management should be initiated when spirometry results are consistent with COPD. Annual probing for COPD symptoms could be considered in asymptomatic patients with ongoing tobacco use or emphysema on CT, since they may develop symptoms in the future. This new case-finding method bypasses the need for time-prohibitive questionnaires or peak flow measurements.

Future Opportunities

VA PCPs juggle many priorities and despite the simplicity of this new case finding COPD method, it may be unintentionally overlooked. PCPs often run out of time or may forget to ask patients about COPD symptoms when ordering LCS.

Future innovations to increase COPD diagnosis could include the creation of a yearly VA clinical reminder linked to the tobacco use reminder that has check boxes asking about symptoms of COPD in current and prior smokers. If patients have COPD symptoms, the reminder can prompt the ordering of spirometry. Similar reminders could be implemented to identify veterans with exposures to burn pits or other military environmental exposures who may have COPD symptoms. Another possible way to increase COPD diagnosis would be a partnership between primary care and the VA LCS program where patients receiving screening are asked about COPD symptoms during their LCS interviews and PACTs are alerted to order spirometry for symptomatic patients.

Elusive no longer! We can pull the veil back on COPD diagnosis and identify patients with possible COPD earlier in their course using their eligibility for LCS as a yearly reminder to probe them for symptoms. While not all patients who undergo LCS—even those with evidence of COPD on CT—will have COPD symptoms, symptoms may develop over time. LCS provides the possibility of 2 diagnoses from 1 test. This is an opportunity we cannot afford to miss.

Primary care practitioners (PCPs) in the US Department of Veterans Affairs (VA) provide care for patients with higher rates of many diseases—diabetes, heart disease, cancer, chronic obstructive pulmonary disease (COPD), and stroke—compared to the nonveteran population. ¹ Due to the medical complexities of these diseases, they are often misdiagnosed or not diagnosed at all.

COPD is hiding in plain sight, impacting quality of life and burdening US health care systems.² Research has yielded new treatments and evidence-based guidelines; however, COPD remains underdiagnosed. Only 13 million of the estimated 79 million US adults with COPD aged 20 to 79 years have been formally diagnosed.³ By the time patients are diagnosed, the disease is often advanced, and therapies are less effective. In 2 large studies of patients with COPD symptoms, later diagnosis was associated with worse outcomes.^4,5

Veterans have a higher prevalence of COPD (8%-19%) than nonveterans (6%), likely due to higher rates of smoking and service-related exposures, especially among veterans of post-9/11 conflicts.^6,7 Veterans do not always report symptoms and PCPs may not ask about symptoms, leading to underdiagnosis.⁸ The combination of high likelihood and underdetection of COPD presents a challenge and a target for VA quality improvement (QI).

The US Preventive Services Task Force (USPSTF) recommends against screening asymptomatic patients for COPD. However, both the USPSTF and the Global Initiative for Chronic Obstructive Lung Disease Report advocate for active case finding in primary care clinics to determine whether high-risk patients, such as smokers, experience COPD symptoms and warrant spirometry. ^9,10 To make early COPD diagnoses, clinicians may use questionnaires alone or in combination with handheld peak expiratory flow rate measurements.^11,12 Formal spirometry, considered the gold standard for COPD diagnosis, is ordered for patients who report COPD symptoms (ie, shortness of breath with exertion) or who have both COPD symptoms and reduced peak flow rates.

A systematic review and meta-analysis found that while the combination of questionnaires and peak flows was the more effective strategy overall, questionnaires alone were also valuable for identifying patients with possible COPD.¹³ Implementation of either screening method in primary care practices would be challenging. In a simulation study that applied chronic disease and preventive care guidelines to hypothetical patient panels, the time required for PCPs to provide guideline-recommended chronic and preventive care in addition to acute care far exceeded 8 hours per day, even in team-based settings.¹⁴ Overburdened PCPs are therefore unlikely to accept additional tasks like COPD case finding.

Why don’t patients report their pulmonary symptoms? Patients may not recognize the symptoms as evidence of COPD. Others may be afraid of a COPD diagnosis or the stigma that is associated with it.¹⁵ Perhaps they believe COPD treatment is ineffective because of lung damage from smoking. Some patients may not want to know if they have COPD, while others reduce activity levels to avoid symptoms.¹⁶

QUALITY IMPROVEMENT PROJECT

Given the high prevalence of COPD among veterans and the potential for underdiagnosis, VA Northeast Ohio Healthcare System (VANEOHS) internal medicine residents and faculty assessed the state of COPD diagnosis in its primary care clinic with a QI project in 2022. Patients in the clinic between August 1, 2015, and November 30, 2022, with an International Classification of Diseases-10 (ICD-10) COPD diagnosis code (J44) in the electronic health record were included. Of 157 included patients, 105 patients who had prior spirometry testing were excluded. Of the 52 patients with diagnosed COPD and no spirometry testing, 30 patients had computed tomography (CT) findings consistent with COPD (ie, airway thickening, emphysema, air trapping) that was performed for CT lung cancer screening (LCS).¹⁷ Twenty-three of these 30 patients were contacted by phone. All 23 were ever smokers and 13 reported COPD symptoms. The PCPs of the symptomatic patients were then contacted. Spirometry was ordered for all 13 patients and completed by 7. Three spirometry tests confirmed the COPD diagnosis. One PCP initiated inhaler therapy for a patient with newly diagnosed COPD.

All 11 PCPs of symptomatic patients were interviewed (many had > 1 symptomatic patient). They reported being unaware of patients’ COPD symptoms because the patients did not mention them, noting that screening for COPD was not a priority.

Role of Lung Cancer Screening

VA PCPs use electronic health record clinical reminders to track tests, consults, chronic disease education, cancer screenings, and routine health maintenance. A clinical reminder already exists (based on USPSTF recommendations) for LCS for patients aged 50 to 80 years who have a smoking history of 20 pack years. Patients who meet these criteria would also be considered high risk for COPD.

The VANEOHS QI project suggests that previously undiagnosed patients with findings of COPD on LCS may also have symptoms of COPD. Therefore, we wondered whether the LCS clinical reminder could serve a second purpose by prompting PCPs to ask veterans who meet LCS criteria about their COPD symptoms.

In 2022, about 13 million patients were eligible for LCS.¹⁸ Patients who qualify for LCS are at high risk for other cardiopulmonary disorders, such as COPD and coronary artery disease. Lung cancer is detected in only 1% of patients screened with CT at baseline. However, more often LCS yields evidence of additional cardiopulmonary disorders, such as emphysema or coronary artery calcifications. The International Early Lung Cancer Program (I-ELCAP) and the National Lung Cancer Screening Trial (NLST), which included > 79,000 patients, found evidence of emphysema on CT imaging in 24% and 31% of cases, respectively.^19,20 In both cohorts, > 80% of patients with emphysema on CT imaging had no prior history of COPD.

In a 2022 article summarizing the potential impact of CT LCS on COPD diagnosis, Mulshine et al suggest that detection of emphysema on CT LCS provides “earlier recognition for PCPs to identify patients who would benefit from detailed symptom screening to prompt spirometry for COPD detection” and additional motivation for tobacco cessation.²¹ The VANEOHS QI project was developed and implemented prior to I-ELCAP or NLST reporting results but reinforces the value of CT LCS for COPD diagnosis.

Early diagnosis of COPD remains challenging because PCPs do not ask, patients do not tell, and symptoms can easily be dismissed. However, earlier diagnosis of COPD in symptomatic patients improves outcomes.^3,4 To bridge this gap, VA PCPs and primary care patient aligned care teams (PACTs) need to commit to probing high-risk patients for COPD symptoms and ordering spirometry for those who are symptomatic. To accomplish this task, primary care teams need help.

The VANEOHS QI project confirmed that some patients with evidence of COPD on CT have symptoms of COPD that they did not share with their PCPs and suggests that LCS can be used as a dual action case finding method to screen both for lung cancer and COPD. We propose that patients who are eligible for LCS should also be probed for COPD symptoms at their clinic visits; for symptomatic patients, spirometry should be ordered, and COPD evidence-based management should be initiated when spirometry results are consistent with COPD. Annual probing for COPD symptoms could be considered in asymptomatic patients with ongoing tobacco use or emphysema on CT, since they may develop symptoms in the future. This new case-finding method bypasses the need for time-prohibitive questionnaires or peak flow measurements.

Future Opportunities

VA PCPs juggle many priorities and despite the simplicity of this new case finding COPD method, it may be unintentionally overlooked. PCPs often run out of time or may forget to ask patients about COPD symptoms when ordering LCS.

Future innovations to increase COPD diagnosis could include the creation of a yearly VA clinical reminder linked to the tobacco use reminder that has check boxes asking about symptoms of COPD in current and prior smokers. If patients have COPD symptoms, the reminder can prompt the ordering of spirometry. Similar reminders could be implemented to identify veterans with exposures to burn pits or other military environmental exposures who may have COPD symptoms. Another possible way to increase COPD diagnosis would be a partnership between primary care and the VA LCS program where patients receiving screening are asked about COPD symptoms during their LCS interviews and PACTs are alerted to order spirometry for symptomatic patients.

Elusive no longer! We can pull the veil back on COPD diagnosis and identify patients with possible COPD earlier in their course using their eligibility for LCS as a yearly reminder to probe them for symptoms. While not all patients who undergo LCS—even those with evidence of COPD on CT—will have COPD symptoms, symptoms may develop over time. LCS provides the possibility of 2 diagnoses from 1 test. This is an opportunity we cannot afford to miss.

Primary care practitioners (PCPs) in the US Department of Veterans Affairs (VA) provide care for patients with higher rates of many diseases—diabetes, heart disease, cancer, chronic obstructive pulmonary disease (COPD), and stroke—compared to the nonveteran population. ¹ Due to the medical complexities of these diseases, they are often misdiagnosed or not diagnosed at all.

COPD is hiding in plain sight, impacting quality of life and burdening US health care systems.² Research has yielded new treatments and evidence-based guidelines; however, COPD remains underdiagnosed. Only 13 million of the estimated 79 million US adults with COPD aged 20 to 79 years have been formally diagnosed.³ By the time patients are diagnosed, the disease is often advanced, and therapies are less effective. In 2 large studies of patients with COPD symptoms, later diagnosis was associated with worse outcomes.^4,5

Veterans have a higher prevalence of COPD (8%-19%) than nonveterans (6%), likely due to higher rates of smoking and service-related exposures, especially among veterans of post-9/11 conflicts.^6,7 Veterans do not always report symptoms and PCPs may not ask about symptoms, leading to underdiagnosis.⁸ The combination of high likelihood and underdetection of COPD presents a challenge and a target for VA quality improvement (QI).

The US Preventive Services Task Force (USPSTF) recommends against screening asymptomatic patients for COPD. However, both the USPSTF and the Global Initiative for Chronic Obstructive Lung Disease Report advocate for active case finding in primary care clinics to determine whether high-risk patients, such as smokers, experience COPD symptoms and warrant spirometry. ^9,10 To make early COPD diagnoses, clinicians may use questionnaires alone or in combination with handheld peak expiratory flow rate measurements.^11,12 Formal spirometry, considered the gold standard for COPD diagnosis, is ordered for patients who report COPD symptoms (ie, shortness of breath with exertion) or who have both COPD symptoms and reduced peak flow rates.

A systematic review and meta-analysis found that while the combination of questionnaires and peak flows was the more effective strategy overall, questionnaires alone were also valuable for identifying patients with possible COPD.¹³ Implementation of either screening method in primary care practices would be challenging. In a simulation study that applied chronic disease and preventive care guidelines to hypothetical patient panels, the time required for PCPs to provide guideline-recommended chronic and preventive care in addition to acute care far exceeded 8 hours per day, even in team-based settings.¹⁴ Overburdened PCPs are therefore unlikely to accept additional tasks like COPD case finding.

Why don’t patients report their pulmonary symptoms? Patients may not recognize the symptoms as evidence of COPD. Others may be afraid of a COPD diagnosis or the stigma that is associated with it.¹⁵ Perhaps they believe COPD treatment is ineffective because of lung damage from smoking. Some patients may not want to know if they have COPD, while others reduce activity levels to avoid symptoms.¹⁶

QUALITY IMPROVEMENT PROJECT

Given the high prevalence of COPD among veterans and the potential for underdiagnosis, VA Northeast Ohio Healthcare System (VANEOHS) internal medicine residents and faculty assessed the state of COPD diagnosis in its primary care clinic with a QI project in 2022. Patients in the clinic between August 1, 2015, and November 30, 2022, with an International Classification of Diseases-10 (ICD-10) COPD diagnosis code (J44) in the electronic health record were included. Of 157 included patients, 105 patients who had prior spirometry testing were excluded. Of the 52 patients with diagnosed COPD and no spirometry testing, 30 patients had computed tomography (CT) findings consistent with COPD (ie, airway thickening, emphysema, air trapping) that was performed for CT lung cancer screening (LCS).¹⁷ Twenty-three of these 30 patients were contacted by phone. All 23 were ever smokers and 13 reported COPD symptoms. The PCPs of the symptomatic patients were then contacted. Spirometry was ordered for all 13 patients and completed by 7. Three spirometry tests confirmed the COPD diagnosis. One PCP initiated inhaler therapy for a patient with newly diagnosed COPD.

All 11 PCPs of symptomatic patients were interviewed (many had > 1 symptomatic patient). They reported being unaware of patients’ COPD symptoms because the patients did not mention them, noting that screening for COPD was not a priority.

Role of Lung Cancer Screening

VA PCPs use electronic health record clinical reminders to track tests, consults, chronic disease education, cancer screenings, and routine health maintenance. A clinical reminder already exists (based on USPSTF recommendations) for LCS for patients aged 50 to 80 years who have a smoking history of 20 pack years. Patients who meet these criteria would also be considered high risk for COPD.

The VANEOHS QI project suggests that previously undiagnosed patients with findings of COPD on LCS may also have symptoms of COPD. Therefore, we wondered whether the LCS clinical reminder could serve a second purpose by prompting PCPs to ask veterans who meet LCS criteria about their COPD symptoms.

In 2022, about 13 million patients were eligible for LCS.¹⁸ Patients who qualify for LCS are at high risk for other cardiopulmonary disorders, such as COPD and coronary artery disease. Lung cancer is detected in only 1% of patients screened with CT at baseline. However, more often LCS yields evidence of additional cardiopulmonary disorders, such as emphysema or coronary artery calcifications. The International Early Lung Cancer Program (I-ELCAP) and the National Lung Cancer Screening Trial (NLST), which included > 79,000 patients, found evidence of emphysema on CT imaging in 24% and 31% of cases, respectively.^19,20 In both cohorts, > 80% of patients with emphysema on CT imaging had no prior history of COPD.

In a 2022 article summarizing the potential impact of CT LCS on COPD diagnosis, Mulshine et al suggest that detection of emphysema on CT LCS provides “earlier recognition for PCPs to identify patients who would benefit from detailed symptom screening to prompt spirometry for COPD detection” and additional motivation for tobacco cessation.²¹ The VANEOHS QI project was developed and implemented prior to I-ELCAP or NLST reporting results but reinforces the value of CT LCS for COPD diagnosis.

Early diagnosis of COPD remains challenging because PCPs do not ask, patients do not tell, and symptoms can easily be dismissed. However, earlier diagnosis of COPD in symptomatic patients improves outcomes.^3,4 To bridge this gap, VA PCPs and primary care patient aligned care teams (PACTs) need to commit to probing high-risk patients for COPD symptoms and ordering spirometry for those who are symptomatic. To accomplish this task, primary care teams need help.

The VANEOHS QI project confirmed that some patients with evidence of COPD on CT have symptoms of COPD that they did not share with their PCPs and suggests that LCS can be used as a dual action case finding method to screen both for lung cancer and COPD. We propose that patients who are eligible for LCS should also be probed for COPD symptoms at their clinic visits; for symptomatic patients, spirometry should be ordered, and COPD evidence-based management should be initiated when spirometry results are consistent with COPD. Annual probing for COPD symptoms could be considered in asymptomatic patients with ongoing tobacco use or emphysema on CT, since they may develop symptoms in the future. This new case-finding method bypasses the need for time-prohibitive questionnaires or peak flow measurements.

Future Opportunities

VA PCPs juggle many priorities and despite the simplicity of this new case finding COPD method, it may be unintentionally overlooked. PCPs often run out of time or may forget to ask patients about COPD symptoms when ordering LCS.

Future innovations to increase COPD diagnosis could include the creation of a yearly VA clinical reminder linked to the tobacco use reminder that has check boxes asking about symptoms of COPD in current and prior smokers. If patients have COPD symptoms, the reminder can prompt the ordering of spirometry. Similar reminders could be implemented to identify veterans with exposures to burn pits or other military environmental exposures who may have COPD symptoms. Another possible way to increase COPD diagnosis would be a partnership between primary care and the VA LCS program where patients receiving screening are asked about COPD symptoms during their LCS interviews and PACTs are alerted to order spirometry for symptomatic patients.

Elusive no longer! We can pull the veil back on COPD diagnosis and identify patients with possible COPD earlier in their course using their eligibility for LCS as a yearly reminder to probe them for symptoms. While not all patients who undergo LCS—even those with evidence of COPD on CT—will have COPD symptoms, symptoms may develop over time. LCS provides the possibility of 2 diagnoses from 1 test. This is an opportunity we cannot afford to miss.

About half of US adults aged ≥ 65 years report arthritis, and of those, 44% have an arthritis-attributable activity limitation.^1,2 Arthritis is a significant health issue for veterans, with veterans reporting higher rates of disability compared with the civilian population.³

Osteoarthritis (OA) is the most common type of arthritis.⁴ Among individuals aged ≥ 40 years, the incidence of OA is nearly twice as high among veterans compared with civilians and is a leading cause of separation from military service and disability.^5,6 OA pain and disability have been shown to be associated with increases in health care and medication use, including opioids, nonsteroidal anti-inflammatory medications, and muscle relaxants.^7,8 Because OA is chronic and has no cure, safe and effective management strategies—such as exercise— are critical to minimize pain and maintain physical function.⁹

Exercise can reduce pain and disability associated with OA and is a first-line recommendation in guidelines for the treatment of knee and hip OA.⁹ Given the limited exercise and high levels of physical inactivity among veterans with OA, there is a need to identify opportunities that support veterans with OA engaging in regular exercise.

Gerofit, an outpatient clinical exercise program available at 30 Veterans Health Administration (VHA) sites, may provide an opportunity for older veterans with arthritis to engage in exercise.¹⁰ Gerofit is specifically designed for veterans aged ≥ 65 years. It is not disease-specific and supports older veterans with multiple chronic conditions, including OA. Veterans aged ≥ 65 years with a referral from a VA clinician are eligible for Gerofit. Those who are unable to perform activities of daily living; unable to independently function without assistance; have a history of unstable angina, proliferative diabetic retinopathy, oxygen dependence, volatile behavioral issues, or are unable to work successfully in a group environment/setting; experience active substance abuse, homelessness, or uncontrolled incontinence; and have open wounds that cannot be appropriately dressed are excluded from Gerofit. Exercise sessions are held 3 times per week and last from 60 to 90 minutes. Sessions are supervised by Gerofit staff and include personalized exercise prescriptions based on functional assessments. Exercise prescriptions include aerobic, resistance, and balance/flexibility components and are modified by the Gerofit program staff as needed. Gerofit adopts a functional fitness approach and includes individual progression as appropriate according to evidence-based guidelines, using the Borg ratings of perceived exertion. ¹¹ Assessments are performed at baseline, 3 months, 6 months, and annually thereafter. Clinical staff conduct all assessments, including physical function testing, and record them in a database. Assessments are reviewed with the veteran to chart progress and identify future goals or needs. Veterans perform personalized self-paced exercises in the Gerofit group setting. Exercise prescriptions are continuously modified to meet individualized needs and goals. Veterans may participate continuously with no end date.

Participation in supervised exercise is associated with improved physical function and individuals with arthritis can improve function even though their baseline functional status is lower than individuals without arthritis. ¹² In this analysis, we examine the impact of exercise on the status and location of arthritis (upper body, lower body, or both). Lower body arthritis is more common than upper body arthritis and lower extremity function is associated with increased ability to perform activities of daily living, resulting in independence among older adults.^13,14 We also include upper body strength measures to capture important functional movements such as reaching and pulling.¹⁵ Among those who participate in Gerofit, the greatest gains in physical function occur during the initial 3 months, which tend to be sustained over 12 months.¹⁶ For this reason, this study focused on the initial 3 months of the program.

Older adults with arthritis may have pain and functional limitations that exceed those of the general older adult population. Exercise programs for older adults that do not specifically target arthritis but are able to improve physical function among those with arthritis could potentially increase access to exercise for older adults living with arthritis. Therefore, the purpose of this study was to determine whether change in physical function with participation in Gerofit for 3 months varies by arthritis status, including no arthritis, any arthritis, lower body arthritis, or both upper and lower body arthritis compared with no arthritis.

Methods

This is a secondary analysis of previously collected data from 10 VHA Gerofit sites (Ann Arbor, Baltimore, Greater Los Angeles, Canandaigua, Cincinnati, Miami, Honolulu, Denver, Durham, and Pittsburgh) from 2002 to 2019. Implementation data regarding the consistency of the program delivery at Gerofit expansion sites have been previously published.¹⁶ Although the delivery of Gerofit transitioned to telehealth due to COVID-19, data for this analysis were collected from in-person exercise sessions prior to the pandemic.¹⁷ Data were collected for clinical purposes. This project was part of the Gerofit quality improvement initiative and was reviewed and approved by the Durham Institutional Review Board as quality improvement.

Participants in Gerofit who completed baseline and 3-month assessments were included to analyze the effects of exercise on physical function. At each of the time points, physical functional assessments included: (1) usual gait speed (> 10 meters [m/s], or 10- meter walk test [10MWT]); (2) lower body strength (chair stands [number completed in 30 seconds]); (3) upper body strength (number of arm curls [5-lb for females/8-lb for males] completed in 30 seconds); and (4) 6-minute walk distance [6MWD] in meters to measure aerobic endurance). These measures have been validated in older adults.^18-21 Arm curls were added to the physical function assessments after the 10MWT, chair stands, and 6MWD; therefore, fewer participants had data for this measure. Participants self-reported at baseline on 45 common medical conditions, including arthritis or rheumatism (both upper body and lower body were offered as choices). Self-reporting has been shown to be an acceptable method of identifying arthritis in adults.²²

Descriptive statistics at baseline were calculated for all participants. One-way analysis of variance and X² tests were used to determine differences in baseline characteristics across arthritis status. The primary outcomes were changes in physical function measures from baseline to 3 months by arthritis status. Arthritis status was defined as: any arthritis, which includes individuals who reported upper body arthritis, lower body arthritis, or both; and arthritis status individuals reporting either upper body arthritis, lower body arthritis, or both. Categories of arthritis for arthritis status were mutually exclusive. Two separate linear models were constructed for each of the 4 physical function measures, with change from baseline to 3 months as the outcome (dependent variable) and arthritis status, age, and body mass index (BMI) as predictors (independent variables). The first model compared any arthritis with no arthritis and the second model compared arthritis status (both upper and lower body arthritis vs lower body arthritis) with no arthritis. These models were used to obtain mean changes and 95% CIs in physical function and to test for differences in the change in physical function measures by arthritis status. Statistical analyses were performed using R software, version 4.0.3.

Results

Baseline and 3-month data were available for 737 Gerofit participants and included in the analysis. The mean (SD) age was 73.5 (7.1) years. A total of 707 participants were male (95.9%) and 322 (43.6%) reported some arthritis, with arthritis in both the upper and lower body being reported by 168 participants (52.2%) (Table 1). There were no differences in age, sex, or race for those with any arthritis compared with those with no arthritis, but BMI was significantly higher in those reporting any arthritis compared with no arthritis. For the baseline functional measures, statistically significant differences were observed between those with no arthritis and those reporting any arthritis for the 10MWT (P = .001), chair stands (P = .046), and 6MWD (P = .001), but not for arm curls (P = .77), with those with no arthritis performing better.

All 4 arthritis status groups showed improvements in each of the physical function measures over 3 months. For the 10MWT the mean change (95% CI) in gait speed (m/s) was 0.06 (0.04-0.08) for patients with no arthritis, 0.07 (0.05- 0.08) for any arthritis, 0.07 (0.04-0.11) for lower body arthritis, and 0.07 (0.04- 0.09) for both lower and upper body arthritis. For the number of arm curls in 30 seconds the mean change (95% CI) was 2.3 (1.8-2.8) for patients with no arthritis, 2.1 (1.5-2.6) for any arthritis, 2.0 (1.1-3.0) for lower body arthritis, and 1.9 (1.1-2.7) for both lower and upper body arthritis. For the number of chair stands in 30 seconds the mean change (95% CI) was 2.1 (1.7-2.4) for patients with no arthritis, 2.2 (1.8-2.6) for any arthritis, 2.3 (1.6-2.9), for lower body arthritis, and 2.0 (1.5-2.5) for both lower and upper body arthritis. For the 6MWD distance in meters the mean change (95% CI) was 21.5 (15.5-27.4) for patients with no arthritis, 28.6 (21.9-35.3) for any arthritis, 30.4 (19.5-41.3) for lower body arthritis, and 28.6 (19.2-38.0) for both lower and upper body arthritis (Figure).

We used 2 models to measure the change from baseline to 3 months for each of the arthritis groups. Model 1 compared any arthritis vs no arthritis and model 2 compared lower body arthritis and both upper and lower body arthritis vs no arthritis for each physical function measure (Table 2). There were no statistically significant differences in 3-month change in physical function for any of the physical function measures between arthritis groups after adjusting for age and BMI.

Discussion

Participation in Gerofit was associated with functional gains among all participants over 3 months, regardless of arthritis status. Older veterans reporting any arthritis had significantly lower physical function scores upon enrollment into Gerofit compared with those veterans reporting no arthritis. However, compared with individuals who reported no arthritis, individuals who reported arthritis (any arthritis, lower body arthritis only, or both lower and upper body arthritis) experienced similar improvements (ie, no statistically significant differences in mean change from baseline to follow-up among those with and without arthritis). This study suggests that progressive, multicomponent exercise programs for older adults may be beneficial for those with arthritis.

Involvement of multiple sites of arthritis is associated with moderate to severe functional limitations as well as lower healthrelated quality of life.²³ While it has been found that individuals with arthritis can improve function with supervised exercise, even though their baseline functional status is lower than individuals without arthritis, it was not clear whether individuals with multiple joint involvement also would benefit.¹² The results of this study suggest that these individuals can improve across various domains of physical function despite variation in arthritis location and status. As incidence of arthritis increases with age, targeting older adults for exercise programs such as Gerofit may improve functional limitations and health-related quality of life associated with arthritis.²

We evaluated physical function using multiple measures to assess upper (arm curls) and lower (chair stands, 10MWT) extremity physical function and aerobic endurance (6MWD). Participants in this study reached clinically meaningful changes with 3 months of participation in Gerofit for most of the physical function measures. Gerofit participants had a mean gait speed improvement of 0.05 to 0.07 m/s compared with 0.10 to 0.30 m/s, which was reported previously. ^24,25 In this study, nearly all groups achieved the clinically important improvements in the chair stand in 30 seconds (2.0 to 2.6) and the 6MWD (21.8 to 59.1 m) that have been reported in the literature.^24-26

The Osteoarthritis Research Society International recommends the chair stand and 6MWD performance-based tests for individuals with hip and knee arthritis because they align with patient-reported outcomes and represent the types of activities relevant to this population.²⁷ The findings of this study suggest that improvement in these physical function measures with participation in exercise align with data from arthritis-specific exercise programs designed for wide implementation. Hughes and colleagues reported improvements in the 6MWD after the 8-week Fit and Strong exercise intervention, which included walking and lower body resistance training.²⁸ The Arthritis Foundation’s Walk With Ease program is a 6-week walking program that has shown improvements in chair stands and gait speed.²⁹ Another Arthritis Foundation program, People with Arthritis Can Exercise, is an 8-week course consisting of a variety of resistance, aerobic, and balance activities. This program has been associated with increases in chair stands but not gait speed or 6MWD.^30,31

This study found that participation in a VHA outpatient clinical supervised exercise program results in improvements in physical function that can be realized by older adults regardless of arthritis burden. Gerofit programs typically require 1.5 to 2.0 dedicated full-time equivalent employees to run the program effectively and additional administrative support, depending on size of the program.³² The cost savings generated by the program include reductions in hospitalization rates, emergency department visits, days in hospital, and medication use and provide a compelling argument for the program’s financial viability to health care systems through long-term savings and improved health outcomes for older adults.^33-36

While evidenced-based arthritis programs exist, this study illustrates that an exercise program without a focus on arthritis also improves physical function, potentially reducing the risk of disability related to arthritis. The clinical implication for these findings is that arthritis-specific exercise programs may not be needed to achieve functional improvements in individuals with arthritis. This is critical for under-resourced or exercise- limited health care systems or communities. Therefore, if exercise programming is limited, or arthritis-specific programs and interventions are not available, nonspecific exercise programs will also be beneficial to individuals with arthritis. Thus, individuals with arthritis should be encouraged to participate in any available exercise programming to achieve improvements in physical function. In addition, many older adults have multiple comorbidities, most of which improve with participation in exercise. ³⁷ Disease-specific exercise programs can offer tailored exercises and coaching related to common barriers in participation, such as joint pain for arthritis.³¹ It is unclear whether these additional programmatic components are associated with greater improvements in outcomes, such as physical function. More research is needed to explore the benefits of disease-specific tailored exercise programs compared with general exercise programs.

Strengths and Limitations

This study demonstrated the effect of participation in a clinical, supervised exercise program in a real-world setting. It suggests that even exercise programs not specifically targeted for arthritis populations can improve physical function among those with arthritis.

As a VHA clinical supervised exercise program, Gerofit may not be generalizable to all older adults or other exercise programs. In addition, this analysis only included a veteran population that was > 95% male and may not be generalizable to other populations. Arthritis status was defined by self-report and not verified in the health record. However, this approach has been shown to be acceptable in this setting and the most common type of arthritis in this population (OA) is a painful musculoskeletal condition associated with functional limitations.^4,22,38,39 Self-reported arthritis or rheumatism is associated with functional limitations.¹ Therefore, it is unlikely that the results would differ for physician-diagnosed or radiographically defined OA. Additionally, the study did not have data on the total number of joints with arthritis or arthritis severity but rather used upper body, lower body, and both upper and lower body arthritis as a proxy for arthritis status. While our models were adjusted for age and BMI, 2 known confounding factors for the association between arthritis and physical function, there are other potential confounding factors that were not included in the models. ^40,41 Finally, this study only included individuals with completed baseline and 3-month follow-up assessments, and the individuals who participated for longer or shorter periods may have had different physical function outcomes than individuals included in this study.

Conclusions

Participation in 3 months VHA Gerofit outpatient supervised exercise programs can improve physical function for all older adults, regardless of arthritis status. These programs may increase access to exercise programming that is beneficial for common conditions affecting older adults, such as arthritis.

About half of US adults aged ≥ 65 years report arthritis, and of those, 44% have an arthritis-attributable activity limitation.^1,2 Arthritis is a significant health issue for veterans, with veterans reporting higher rates of disability compared with the civilian population.³

Osteoarthritis (OA) is the most common type of arthritis.⁴ Among individuals aged ≥ 40 years, the incidence of OA is nearly twice as high among veterans compared with civilians and is a leading cause of separation from military service and disability.^5,6 OA pain and disability have been shown to be associated with increases in health care and medication use, including opioids, nonsteroidal anti-inflammatory medications, and muscle relaxants.^7,8 Because OA is chronic and has no cure, safe and effective management strategies—such as exercise— are critical to minimize pain and maintain physical function.⁹

Exercise can reduce pain and disability associated with OA and is a first-line recommendation in guidelines for the treatment of knee and hip OA.⁹ Given the limited exercise and high levels of physical inactivity among veterans with OA, there is a need to identify opportunities that support veterans with OA engaging in regular exercise.

Gerofit, an outpatient clinical exercise program available at 30 Veterans Health Administration (VHA) sites, may provide an opportunity for older veterans with arthritis to engage in exercise.¹⁰ Gerofit is specifically designed for veterans aged ≥ 65 years. It is not disease-specific and supports older veterans with multiple chronic conditions, including OA. Veterans aged ≥ 65 years with a referral from a VA clinician are eligible for Gerofit. Those who are unable to perform activities of daily living; unable to independently function without assistance; have a history of unstable angina, proliferative diabetic retinopathy, oxygen dependence, volatile behavioral issues, or are unable to work successfully in a group environment/setting; experience active substance abuse, homelessness, or uncontrolled incontinence; and have open wounds that cannot be appropriately dressed are excluded from Gerofit. Exercise sessions are held 3 times per week and last from 60 to 90 minutes. Sessions are supervised by Gerofit staff and include personalized exercise prescriptions based on functional assessments. Exercise prescriptions include aerobic, resistance, and balance/flexibility components and are modified by the Gerofit program staff as needed. Gerofit adopts a functional fitness approach and includes individual progression as appropriate according to evidence-based guidelines, using the Borg ratings of perceived exertion. ¹¹ Assessments are performed at baseline, 3 months, 6 months, and annually thereafter. Clinical staff conduct all assessments, including physical function testing, and record them in a database. Assessments are reviewed with the veteran to chart progress and identify future goals or needs. Veterans perform personalized self-paced exercises in the Gerofit group setting. Exercise prescriptions are continuously modified to meet individualized needs and goals. Veterans may participate continuously with no end date.

Participation in supervised exercise is associated with improved physical function and individuals with arthritis can improve function even though their baseline functional status is lower than individuals without arthritis. ¹² In this analysis, we examine the impact of exercise on the status and location of arthritis (upper body, lower body, or both). Lower body arthritis is more common than upper body arthritis and lower extremity function is associated with increased ability to perform activities of daily living, resulting in independence among older adults.^13,14 We also include upper body strength measures to capture important functional movements such as reaching and pulling.¹⁵ Among those who participate in Gerofit, the greatest gains in physical function occur during the initial 3 months, which tend to be sustained over 12 months.¹⁶ For this reason, this study focused on the initial 3 months of the program.

Older adults with arthritis may have pain and functional limitations that exceed those of the general older adult population. Exercise programs for older adults that do not specifically target arthritis but are able to improve physical function among those with arthritis could potentially increase access to exercise for older adults living with arthritis. Therefore, the purpose of this study was to determine whether change in physical function with participation in Gerofit for 3 months varies by arthritis status, including no arthritis, any arthritis, lower body arthritis, or both upper and lower body arthritis compared with no arthritis.

Methods

This is a secondary analysis of previously collected data from 10 VHA Gerofit sites (Ann Arbor, Baltimore, Greater Los Angeles, Canandaigua, Cincinnati, Miami, Honolulu, Denver, Durham, and Pittsburgh) from 2002 to 2019. Implementation data regarding the consistency of the program delivery at Gerofit expansion sites have been previously published.¹⁶ Although the delivery of Gerofit transitioned to telehealth due to COVID-19, data for this analysis were collected from in-person exercise sessions prior to the pandemic.¹⁷ Data were collected for clinical purposes. This project was part of the Gerofit quality improvement initiative and was reviewed and approved by the Durham Institutional Review Board as quality improvement.

Participants in Gerofit who completed baseline and 3-month assessments were included to analyze the effects of exercise on physical function. At each of the time points, physical functional assessments included: (1) usual gait speed (> 10 meters [m/s], or 10- meter walk test [10MWT]); (2) lower body strength (chair stands [number completed in 30 seconds]); (3) upper body strength (number of arm curls [5-lb for females/8-lb for males] completed in 30 seconds); and (4) 6-minute walk distance [6MWD] in meters to measure aerobic endurance). These measures have been validated in older adults.^18-21 Arm curls were added to the physical function assessments after the 10MWT, chair stands, and 6MWD; therefore, fewer participants had data for this measure. Participants self-reported at baseline on 45 common medical conditions, including arthritis or rheumatism (both upper body and lower body were offered as choices). Self-reporting has been shown to be an acceptable method of identifying arthritis in adults.²²

Descriptive statistics at baseline were calculated for all participants. One-way analysis of variance and X² tests were used to determine differences in baseline characteristics across arthritis status. The primary outcomes were changes in physical function measures from baseline to 3 months by arthritis status. Arthritis status was defined as: any arthritis, which includes individuals who reported upper body arthritis, lower body arthritis, or both; and arthritis status individuals reporting either upper body arthritis, lower body arthritis, or both. Categories of arthritis for arthritis status were mutually exclusive. Two separate linear models were constructed for each of the 4 physical function measures, with change from baseline to 3 months as the outcome (dependent variable) and arthritis status, age, and body mass index (BMI) as predictors (independent variables). The first model compared any arthritis with no arthritis and the second model compared arthritis status (both upper and lower body arthritis vs lower body arthritis) with no arthritis. These models were used to obtain mean changes and 95% CIs in physical function and to test for differences in the change in physical function measures by arthritis status. Statistical analyses were performed using R software, version 4.0.3.

Results

Baseline and 3-month data were available for 737 Gerofit participants and included in the analysis. The mean (SD) age was 73.5 (7.1) years. A total of 707 participants were male (95.9%) and 322 (43.6%) reported some arthritis, with arthritis in both the upper and lower body being reported by 168 participants (52.2%) (Table 1). There were no differences in age, sex, or race for those with any arthritis compared with those with no arthritis, but BMI was significantly higher in those reporting any arthritis compared with no arthritis. For the baseline functional measures, statistically significant differences were observed between those with no arthritis and those reporting any arthritis for the 10MWT (P = .001), chair stands (P = .046), and 6MWD (P = .001), but not for arm curls (P = .77), with those with no arthritis performing better.

All 4 arthritis status groups showed improvements in each of the physical function measures over 3 months. For the 10MWT the mean change (95% CI) in gait speed (m/s) was 0.06 (0.04-0.08) for patients with no arthritis, 0.07 (0.05- 0.08) for any arthritis, 0.07 (0.04-0.11) for lower body arthritis, and 0.07 (0.04- 0.09) for both lower and upper body arthritis. For the number of arm curls in 30 seconds the mean change (95% CI) was 2.3 (1.8-2.8) for patients with no arthritis, 2.1 (1.5-2.6) for any arthritis, 2.0 (1.1-3.0) for lower body arthritis, and 1.9 (1.1-2.7) for both lower and upper body arthritis. For the number of chair stands in 30 seconds the mean change (95% CI) was 2.1 (1.7-2.4) for patients with no arthritis, 2.2 (1.8-2.6) for any arthritis, 2.3 (1.6-2.9), for lower body arthritis, and 2.0 (1.5-2.5) for both lower and upper body arthritis. For the 6MWD distance in meters the mean change (95% CI) was 21.5 (15.5-27.4) for patients with no arthritis, 28.6 (21.9-35.3) for any arthritis, 30.4 (19.5-41.3) for lower body arthritis, and 28.6 (19.2-38.0) for both lower and upper body arthritis (Figure).

We used 2 models to measure the change from baseline to 3 months for each of the arthritis groups. Model 1 compared any arthritis vs no arthritis and model 2 compared lower body arthritis and both upper and lower body arthritis vs no arthritis for each physical function measure (Table 2). There were no statistically significant differences in 3-month change in physical function for any of the physical function measures between arthritis groups after adjusting for age and BMI.

Discussion

Participation in Gerofit was associated with functional gains among all participants over 3 months, regardless of arthritis status. Older veterans reporting any arthritis had significantly lower physical function scores upon enrollment into Gerofit compared with those veterans reporting no arthritis. However, compared with individuals who reported no arthritis, individuals who reported arthritis (any arthritis, lower body arthritis only, or both lower and upper body arthritis) experienced similar improvements (ie, no statistically significant differences in mean change from baseline to follow-up among those with and without arthritis). This study suggests that progressive, multicomponent exercise programs for older adults may be beneficial for those with arthritis.

Involvement of multiple sites of arthritis is associated with moderate to severe functional limitations as well as lower healthrelated quality of life.²³ While it has been found that individuals with arthritis can improve function with supervised exercise, even though their baseline functional status is lower than individuals without arthritis, it was not clear whether individuals with multiple joint involvement also would benefit.¹² The results of this study suggest that these individuals can improve across various domains of physical function despite variation in arthritis location and status. As incidence of arthritis increases with age, targeting older adults for exercise programs such as Gerofit may improve functional limitations and health-related quality of life associated with arthritis.²

We evaluated physical function using multiple measures to assess upper (arm curls) and lower (chair stands, 10MWT) extremity physical function and aerobic endurance (6MWD). Participants in this study reached clinically meaningful changes with 3 months of participation in Gerofit for most of the physical function measures. Gerofit participants had a mean gait speed improvement of 0.05 to 0.07 m/s compared with 0.10 to 0.30 m/s, which was reported previously. ^24,25 In this study, nearly all groups achieved the clinically important improvements in the chair stand in 30 seconds (2.0 to 2.6) and the 6MWD (21.8 to 59.1 m) that have been reported in the literature.^24-26

The Osteoarthritis Research Society International recommends the chair stand and 6MWD performance-based tests for individuals with hip and knee arthritis because they align with patient-reported outcomes and represent the types of activities relevant to this population.²⁷ The findings of this study suggest that improvement in these physical function measures with participation in exercise align with data from arthritis-specific exercise programs designed for wide implementation. Hughes and colleagues reported improvements in the 6MWD after the 8-week Fit and Strong exercise intervention, which included walking and lower body resistance training.²⁸ The Arthritis Foundation’s Walk With Ease program is a 6-week walking program that has shown improvements in chair stands and gait speed.²⁹ Another Arthritis Foundation program, People with Arthritis Can Exercise, is an 8-week course consisting of a variety of resistance, aerobic, and balance activities. This program has been associated with increases in chair stands but not gait speed or 6MWD.^30,31

This study found that participation in a VHA outpatient clinical supervised exercise program results in improvements in physical function that can be realized by older adults regardless of arthritis burden. Gerofit programs typically require 1.5 to 2.0 dedicated full-time equivalent employees to run the program effectively and additional administrative support, depending on size of the program.³² The cost savings generated by the program include reductions in hospitalization rates, emergency department visits, days in hospital, and medication use and provide a compelling argument for the program’s financial viability to health care systems through long-term savings and improved health outcomes for older adults.^33-36

While evidenced-based arthritis programs exist, this study illustrates that an exercise program without a focus on arthritis also improves physical function, potentially reducing the risk of disability related to arthritis. The clinical implication for these findings is that arthritis-specific exercise programs may not be needed to achieve functional improvements in individuals with arthritis. This is critical for under-resourced or exercise- limited health care systems or communities. Therefore, if exercise programming is limited, or arthritis-specific programs and interventions are not available, nonspecific exercise programs will also be beneficial to individuals with arthritis. Thus, individuals with arthritis should be encouraged to participate in any available exercise programming to achieve improvements in physical function. In addition, many older adults have multiple comorbidities, most of which improve with participation in exercise. ³⁷ Disease-specific exercise programs can offer tailored exercises and coaching related to common barriers in participation, such as joint pain for arthritis.³¹ It is unclear whether these additional programmatic components are associated with greater improvements in outcomes, such as physical function. More research is needed to explore the benefits of disease-specific tailored exercise programs compared with general exercise programs.

Strengths and Limitations

This study demonstrated the effect of participation in a clinical, supervised exercise program in a real-world setting. It suggests that even exercise programs not specifically targeted for arthritis populations can improve physical function among those with arthritis.

As a VHA clinical supervised exercise program, Gerofit may not be generalizable to all older adults or other exercise programs. In addition, this analysis only included a veteran population that was > 95% male and may not be generalizable to other populations. Arthritis status was defined by self-report and not verified in the health record. However, this approach has been shown to be acceptable in this setting and the most common type of arthritis in this population (OA) is a painful musculoskeletal condition associated with functional limitations.^4,22,38,39 Self-reported arthritis or rheumatism is associated with functional limitations.¹ Therefore, it is unlikely that the results would differ for physician-diagnosed or radiographically defined OA. Additionally, the study did not have data on the total number of joints with arthritis or arthritis severity but rather used upper body, lower body, and both upper and lower body arthritis as a proxy for arthritis status. While our models were adjusted for age and BMI, 2 known confounding factors for the association between arthritis and physical function, there are other potential confounding factors that were not included in the models. ^40,41 Finally, this study only included individuals with completed baseline and 3-month follow-up assessments, and the individuals who participated for longer or shorter periods may have had different physical function outcomes than individuals included in this study.

Conclusions

Participation in 3 months VHA Gerofit outpatient supervised exercise programs can improve physical function for all older adults, regardless of arthritis status. These programs may increase access to exercise programming that is beneficial for common conditions affecting older adults, such as arthritis.

About half of US adults aged ≥ 65 years report arthritis, and of those, 44% have an arthritis-attributable activity limitation.^1,2 Arthritis is a significant health issue for veterans, with veterans reporting higher rates of disability compared with the civilian population.³

Osteoarthritis (OA) is the most common type of arthritis.⁴ Among individuals aged ≥ 40 years, the incidence of OA is nearly twice as high among veterans compared with civilians and is a leading cause of separation from military service and disability.^5,6 OA pain and disability have been shown to be associated with increases in health care and medication use, including opioids, nonsteroidal anti-inflammatory medications, and muscle relaxants.^7,8 Because OA is chronic and has no cure, safe and effective management strategies—such as exercise— are critical to minimize pain and maintain physical function.⁹

Exercise can reduce pain and disability associated with OA and is a first-line recommendation in guidelines for the treatment of knee and hip OA.⁹ Given the limited exercise and high levels of physical inactivity among veterans with OA, there is a need to identify opportunities that support veterans with OA engaging in regular exercise.

Gerofit, an outpatient clinical exercise program available at 30 Veterans Health Administration (VHA) sites, may provide an opportunity for older veterans with arthritis to engage in exercise.¹⁰ Gerofit is specifically designed for veterans aged ≥ 65 years. It is not disease-specific and supports older veterans with multiple chronic conditions, including OA. Veterans aged ≥ 65 years with a referral from a VA clinician are eligible for Gerofit. Those who are unable to perform activities of daily living; unable to independently function without assistance; have a history of unstable angina, proliferative diabetic retinopathy, oxygen dependence, volatile behavioral issues, or are unable to work successfully in a group environment/setting; experience active substance abuse, homelessness, or uncontrolled incontinence; and have open wounds that cannot be appropriately dressed are excluded from Gerofit. Exercise sessions are held 3 times per week and last from 60 to 90 minutes. Sessions are supervised by Gerofit staff and include personalized exercise prescriptions based on functional assessments. Exercise prescriptions include aerobic, resistance, and balance/flexibility components and are modified by the Gerofit program staff as needed. Gerofit adopts a functional fitness approach and includes individual progression as appropriate according to evidence-based guidelines, using the Borg ratings of perceived exertion. ¹¹ Assessments are performed at baseline, 3 months, 6 months, and annually thereafter. Clinical staff conduct all assessments, including physical function testing, and record them in a database. Assessments are reviewed with the veteran to chart progress and identify future goals or needs. Veterans perform personalized self-paced exercises in the Gerofit group setting. Exercise prescriptions are continuously modified to meet individualized needs and goals. Veterans may participate continuously with no end date.

Participation in supervised exercise is associated with improved physical function and individuals with arthritis can improve function even though their baseline functional status is lower than individuals without arthritis. ¹² In this analysis, we examine the impact of exercise on the status and location of arthritis (upper body, lower body, or both). Lower body arthritis is more common than upper body arthritis and lower extremity function is associated with increased ability to perform activities of daily living, resulting in independence among older adults.^13,14 We also include upper body strength measures to capture important functional movements such as reaching and pulling.¹⁵ Among those who participate in Gerofit, the greatest gains in physical function occur during the initial 3 months, which tend to be sustained over 12 months.¹⁶ For this reason, this study focused on the initial 3 months of the program.

Older adults with arthritis may have pain and functional limitations that exceed those of the general older adult population. Exercise programs for older adults that do not specifically target arthritis but are able to improve physical function among those with arthritis could potentially increase access to exercise for older adults living with arthritis. Therefore, the purpose of this study was to determine whether change in physical function with participation in Gerofit for 3 months varies by arthritis status, including no arthritis, any arthritis, lower body arthritis, or both upper and lower body arthritis compared with no arthritis.

Methods

This is a secondary analysis of previously collected data from 10 VHA Gerofit sites (Ann Arbor, Baltimore, Greater Los Angeles, Canandaigua, Cincinnati, Miami, Honolulu, Denver, Durham, and Pittsburgh) from 2002 to 2019. Implementation data regarding the consistency of the program delivery at Gerofit expansion sites have been previously published.¹⁶ Although the delivery of Gerofit transitioned to telehealth due to COVID-19, data for this analysis were collected from in-person exercise sessions prior to the pandemic.¹⁷ Data were collected for clinical purposes. This project was part of the Gerofit quality improvement initiative and was reviewed and approved by the Durham Institutional Review Board as quality improvement.

Participants in Gerofit who completed baseline and 3-month assessments were included to analyze the effects of exercise on physical function. At each of the time points, physical functional assessments included: (1) usual gait speed (> 10 meters [m/s], or 10- meter walk test [10MWT]); (2) lower body strength (chair stands [number completed in 30 seconds]); (3) upper body strength (number of arm curls [5-lb for females/8-lb for males] completed in 30 seconds); and (4) 6-minute walk distance [6MWD] in meters to measure aerobic endurance). These measures have been validated in older adults.^18-21 Arm curls were added to the physical function assessments after the 10MWT, chair stands, and 6MWD; therefore, fewer participants had data for this measure. Participants self-reported at baseline on 45 common medical conditions, including arthritis or rheumatism (both upper body and lower body were offered as choices). Self-reporting has been shown to be an acceptable method of identifying arthritis in adults.²²

Descriptive statistics at baseline were calculated for all participants. One-way analysis of variance and X² tests were used to determine differences in baseline characteristics across arthritis status. The primary outcomes were changes in physical function measures from baseline to 3 months by arthritis status. Arthritis status was defined as: any arthritis, which includes individuals who reported upper body arthritis, lower body arthritis, or both; and arthritis status individuals reporting either upper body arthritis, lower body arthritis, or both. Categories of arthritis for arthritis status were mutually exclusive. Two separate linear models were constructed for each of the 4 physical function measures, with change from baseline to 3 months as the outcome (dependent variable) and arthritis status, age, and body mass index (BMI) as predictors (independent variables). The first model compared any arthritis with no arthritis and the second model compared arthritis status (both upper and lower body arthritis vs lower body arthritis) with no arthritis. These models were used to obtain mean changes and 95% CIs in physical function and to test for differences in the change in physical function measures by arthritis status. Statistical analyses were performed using R software, version 4.0.3.

Results

Baseline and 3-month data were available for 737 Gerofit participants and included in the analysis. The mean (SD) age was 73.5 (7.1) years. A total of 707 participants were male (95.9%) and 322 (43.6%) reported some arthritis, with arthritis in both the upper and lower body being reported by 168 participants (52.2%) (Table 1). There were no differences in age, sex, or race for those with any arthritis compared with those with no arthritis, but BMI was significantly higher in those reporting any arthritis compared with no arthritis. For the baseline functional measures, statistically significant differences were observed between those with no arthritis and those reporting any arthritis for the 10MWT (P = .001), chair stands (P = .046), and 6MWD (P = .001), but not for arm curls (P = .77), with those with no arthritis performing better.

All 4 arthritis status groups showed improvements in each of the physical function measures over 3 months. For the 10MWT the mean change (95% CI) in gait speed (m/s) was 0.06 (0.04-0.08) for patients with no arthritis, 0.07 (0.05- 0.08) for any arthritis, 0.07 (0.04-0.11) for lower body arthritis, and 0.07 (0.04- 0.09) for both lower and upper body arthritis. For the number of arm curls in 30 seconds the mean change (95% CI) was 2.3 (1.8-2.8) for patients with no arthritis, 2.1 (1.5-2.6) for any arthritis, 2.0 (1.1-3.0) for lower body arthritis, and 1.9 (1.1-2.7) for both lower and upper body arthritis. For the number of chair stands in 30 seconds the mean change (95% CI) was 2.1 (1.7-2.4) for patients with no arthritis, 2.2 (1.8-2.6) for any arthritis, 2.3 (1.6-2.9), for lower body arthritis, and 2.0 (1.5-2.5) for both lower and upper body arthritis. For the 6MWD distance in meters the mean change (95% CI) was 21.5 (15.5-27.4) for patients with no arthritis, 28.6 (21.9-35.3) for any arthritis, 30.4 (19.5-41.3) for lower body arthritis, and 28.6 (19.2-38.0) for both lower and upper body arthritis (Figure).

We used 2 models to measure the change from baseline to 3 months for each of the arthritis groups. Model 1 compared any arthritis vs no arthritis and model 2 compared lower body arthritis and both upper and lower body arthritis vs no arthritis for each physical function measure (Table 2). There were no statistically significant differences in 3-month change in physical function for any of the physical function measures between arthritis groups after adjusting for age and BMI.

Discussion

Participation in Gerofit was associated with functional gains among all participants over 3 months, regardless of arthritis status. Older veterans reporting any arthritis had significantly lower physical function scores upon enrollment into Gerofit compared with those veterans reporting no arthritis. However, compared with individuals who reported no arthritis, individuals who reported arthritis (any arthritis, lower body arthritis only, or both lower and upper body arthritis) experienced similar improvements (ie, no statistically significant differences in mean change from baseline to follow-up among those with and without arthritis). This study suggests that progressive, multicomponent exercise programs for older adults may be beneficial for those with arthritis.

Involvement of multiple sites of arthritis is associated with moderate to severe functional limitations as well as lower healthrelated quality of life.²³ While it has been found that individuals with arthritis can improve function with supervised exercise, even though their baseline functional status is lower than individuals without arthritis, it was not clear whether individuals with multiple joint involvement also would benefit.¹² The results of this study suggest that these individuals can improve across various domains of physical function despite variation in arthritis location and status. As incidence of arthritis increases with age, targeting older adults for exercise programs such as Gerofit may improve functional limitations and health-related quality of life associated with arthritis.²

We evaluated physical function using multiple measures to assess upper (arm curls) and lower (chair stands, 10MWT) extremity physical function and aerobic endurance (6MWD). Participants in this study reached clinically meaningful changes with 3 months of participation in Gerofit for most of the physical function measures. Gerofit participants had a mean gait speed improvement of 0.05 to 0.07 m/s compared with 0.10 to 0.30 m/s, which was reported previously. ^24,25 In this study, nearly all groups achieved the clinically important improvements in the chair stand in 30 seconds (2.0 to 2.6) and the 6MWD (21.8 to 59.1 m) that have been reported in the literature.^24-26

The Osteoarthritis Research Society International recommends the chair stand and 6MWD performance-based tests for individuals with hip and knee arthritis because they align with patient-reported outcomes and represent the types of activities relevant to this population.²⁷ The findings of this study suggest that improvement in these physical function measures with participation in exercise align with data from arthritis-specific exercise programs designed for wide implementation. Hughes and colleagues reported improvements in the 6MWD after the 8-week Fit and Strong exercise intervention, which included walking and lower body resistance training.²⁸ The Arthritis Foundation’s Walk With Ease program is a 6-week walking program that has shown improvements in chair stands and gait speed.²⁹ Another Arthritis Foundation program, People with Arthritis Can Exercise, is an 8-week course consisting of a variety of resistance, aerobic, and balance activities. This program has been associated with increases in chair stands but not gait speed or 6MWD.^30,31

This study found that participation in a VHA outpatient clinical supervised exercise program results in improvements in physical function that can be realized by older adults regardless of arthritis burden. Gerofit programs typically require 1.5 to 2.0 dedicated full-time equivalent employees to run the program effectively and additional administrative support, depending on size of the program.³² The cost savings generated by the program include reductions in hospitalization rates, emergency department visits, days in hospital, and medication use and provide a compelling argument for the program’s financial viability to health care systems through long-term savings and improved health outcomes for older adults.^33-36

While evidenced-based arthritis programs exist, this study illustrates that an exercise program without a focus on arthritis also improves physical function, potentially reducing the risk of disability related to arthritis. The clinical implication for these findings is that arthritis-specific exercise programs may not be needed to achieve functional improvements in individuals with arthritis. This is critical for under-resourced or exercise- limited health care systems or communities. Therefore, if exercise programming is limited, or arthritis-specific programs and interventions are not available, nonspecific exercise programs will also be beneficial to individuals with arthritis. Thus, individuals with arthritis should be encouraged to participate in any available exercise programming to achieve improvements in physical function. In addition, many older adults have multiple comorbidities, most of which improve with participation in exercise. ³⁷ Disease-specific exercise programs can offer tailored exercises and coaching related to common barriers in participation, such as joint pain for arthritis.³¹ It is unclear whether these additional programmatic components are associated with greater improvements in outcomes, such as physical function. More research is needed to explore the benefits of disease-specific tailored exercise programs compared with general exercise programs.

Strengths and Limitations

This study demonstrated the effect of participation in a clinical, supervised exercise program in a real-world setting. It suggests that even exercise programs not specifically targeted for arthritis populations can improve physical function among those with arthritis.

As a VHA clinical supervised exercise program, Gerofit may not be generalizable to all older adults or other exercise programs. In addition, this analysis only included a veteran population that was > 95% male and may not be generalizable to other populations. Arthritis status was defined by self-report and not verified in the health record. However, this approach has been shown to be acceptable in this setting and the most common type of arthritis in this population (OA) is a painful musculoskeletal condition associated with functional limitations.^4,22,38,39 Self-reported arthritis or rheumatism is associated with functional limitations.¹ Therefore, it is unlikely that the results would differ for physician-diagnosed or radiographically defined OA. Additionally, the study did not have data on the total number of joints with arthritis or arthritis severity but rather used upper body, lower body, and both upper and lower body arthritis as a proxy for arthritis status. While our models were adjusted for age and BMI, 2 known confounding factors for the association between arthritis and physical function, there are other potential confounding factors that were not included in the models. ^40,41 Finally, this study only included individuals with completed baseline and 3-month follow-up assessments, and the individuals who participated for longer or shorter periods may have had different physical function outcomes than individuals included in this study.

Conclusions

Participation in 3 months VHA Gerofit outpatient supervised exercise programs can improve physical function for all older adults, regardless of arthritis status. These programs may increase access to exercise programming that is beneficial for common conditions affecting older adults, such as arthritis.

Osteoporotic fragility fractures constitute a significant public health concern, with 1 in 2 women and 1 in 5 men aged > 50 years sustaining an osteoporotic fracture.¹ Osteoporotic fractures are costly and associated with reduced quality of life and impaired survival.^2-6 Many interventions including fall mitigation, calcium, vitamin D supplementation, and osteoporosis—specific medications reduce fracture risk.⁷ New medications for treating osteoporosis, including anabolic therapies, are costly and require clinical oversight to ensure safe delivery. This includes laboratory monitoring, timing of in-clinic dosing and provision of sequence therapy.^8,9 COVID-19 introduced numerous barriers to osteoporosis care, raising concerns for medication interruption and patients lost to follow-up, which made monitoring these high risk and costly medications even more important.

The US Department of Veterans Affairs (VA) was an early adopter of using the electronic health record to analyze and implement system-wide processes for population management and quality improvement.¹⁰ This enabled the creation of clinical dashboards to display key performance indicator data that support quality improvement and patient care initiatives.^11-15 The VA Puget Sound Health Care System (VAPSHCS) has a dedicated osteoporosis clinic focused on preventing and treating veterans at high risk for fracture. Considering the growing utilization of osteoporosis medications, particularly those requiring timed sequential therapy to prevent bone mineral density loss and rebound osteoporotic fractures, close monitoring and follow-up is required. The COVID-19 pandemic made clear the need for proactive osteoporosis management. This article describes the creation and use of an automated clinic dashboard to identify and contact veterans with osteoporosis-related care needs, such as prescription refills, laboratory tests, and clinical visits.

Methods

An automated dashboard was created in partnership with VA pharmacy clinical informatics to display the osteoporosis medication prescription (including last refill), monitoring laboratory test values and most recent osteoporosis clinic visit for each clinic patient. Data from the VA Corporate Data Warehouse were extracted. The resulting tables were used to create a patient cohort with ≥ 1 active medication for alendronate, zoledronic acid, the parathyroid hormone analogues (PTH) teriparatide or abaloparatide, denosumab, or romosozumab. Notably, alendronate was the only oral bisphosphonate prescribed in the clinic. These data were formatted and displayed using Microsoft SQL Server Reporting Services. The secure and encrypted dashboard alerts the clinic staff when prescriptions, appointments, or laboratory tests, such as estimated glomerular filtration rate, 25-hydroxy vitamin D, calcium, and PTH are overdue or out of reference range. The dashboard tracked the most recent clinic visit or dual-energy X-ray absorptiometry (DXA) scan if performed within the VA. Overdue laboratory test alerts for bisphosphonates were flagged if delayed 12 months and 6 months for all other medications.

On March 20, 2021, the VAPSHCS osteoporosis clinic was staffed by 1 endocrinologist, 1 geriatrician, 1 rheumatologist, and 1 registered nurse (RN) coordinator. Overdue or out-of-range alerts were reviewed weekly by the RN coordinator, who addressed alerts. For any overdue laboratory work or prescription refills, the RN coordinator alerted the primary osteoporosis physician via the electronic health record for updated orders. Patients were contacted by phone to schedule a clinic visit, complete ordered laboratory work, or discuss osteoporosis medication refills based on the need identified by the dashboard. A letter was mailed to the patient requesting they contact the osteoporosis clinic for patients who could not be reached by phone after 2 attempts. If 3 attempts (2 phone calls and a letter) were unsuccessful, the osteoporosis physician was alerted so they could either call the patient, alert the primary referring clinician, or discontinue the osteoporosis medication.

Results

As of March 20, 2021, 139 patients were included on the dashboard. Ninety-two patients (66%) had unmet care needs and 29% were female. Ages ranged from 40 to 100 years (Table). The dashboard alerted the team to 3 patients lost to follow-up, all of whom had transferred to care outside the clinic. Twenty-three patients (17%) had overdue medications, including 2 (9%) who had not refilled oral bisphosphonate and 18 (78%) who were overdue for intravenous bisphosphonate treatment. One veteran flagged as overdue for their denosumab injection was unable to receive it due to a significant change in health status. Two veterans were overdue for a PTH analogue refill, 1 of whom had completed their course and transitioned to bisphosphonate.

The most common alert was 40 patients (29%) with overdue laboratory tests, 37 of which were receiving bisphosphonates. One patient included on the dashboard was taking romosozumab and all their monitoring parameters were up to date, thus their data were not included in the Table to prevent possible identification.

Discussion

A dashboard alerted the osteoporosis clinic team to veterans who were overdue for visits, laboratory work, and prescription renewals. Overall, 92 patients (66%) had unmet care needs identified by the dashboard, all of which were addressed with phone calls and/or letters. Most of the overdue medication refills and laboratory tests were for patients taking bisphosphonates avoiding VAPSHCS during the COVID-19 pandemic. The dashboard enabled the RN coordinator to promptly contact the patient, facilitate coordination of care requirements, and guarantee the safe and efficient delivery of osteoporosis care.

The VA has historically been a leader in the creation of clinical dashboards to support health campaigns.^11,12 These dashboards have successfully improved quality metrics towards the treatment of hepatitis C virus, heart failure, and highrisk opioid prescribing.^13-15 Data have shown that successful clinical dashboard implementation must be done in conjunction with protected time or staff to support care improvements.¹⁶ Additionally, the time required for clinical dashboards can limit their sustainability and feasibility.¹⁷ A study aimed at improving osteoporosis care for patients with Parkinson disease found that weekly multidisciplinary review of at-risk patients resulted in all new patients and 91% of follow-up patients receiving evidence- based osteoporosis treatments.¹⁷ However, despite the benefits, the intervention required significant time and resources. In contrast, the osteoporosis dashboard implemented at VAPSHCS was not time or resource intensive, requiring about 1 hour per week for the RN coordinator to review the dashboard and coordinate patient care needs.

Limitations

This study setting is unique from other health care organizations or VA health care systems. Implementation of a similar dashboard in other clinical settings where patients receive medical care in multiple health care systems may differ. The VA dedicates resources to support veteran population health management, which may not be available in other health care systems.^11,12 These issues may pose a barrier to implementing a similar osteoporosis dashboard in non-VA facilities. In addition, it is significant that while the dashboard can be reconfigured and adapted to track veterans across different VA facilities, certain complexities arise if essential data, such as laboratory tests and DXA imaging, are conducted outside of VA facilities. In such cases, manual entry of this information into the dashboard would be necessary. Because the dashboard was quickly developed during the COVID-19 pandemic, this study lacked preimplementation data on laboratory testing, medication refills, and DXA imaging, which would have enabled a comparison of adherence before and after dashboard implementation. Finally, we acknowledge the delay in publishing these findings; however, we believe sharing innovative approaches to providing care for high-risk populations is essential, as demonstrated during the COVID-19 pandemic.

Conclusions

An osteoporosis clinic dashboard served as a valuable clinical support tool to ensure safe and effective osteoporosis medication delivery at VAPSHCS. Considering the growing utilization of osteoporosis medications, this dashboard plays a vital role in facilitating care coordination for patients receiving these high-risk treatments.¹⁸ Use of the dashboard supported the effective use of high-cost osteoporosis medications and is likely to improve clinical osteoporosis outcomes.

Despite the known fracture risk reduction, osteoporosis medication adherence is low.^19,20 Maintaining consistent pharmacotherapy for osteoporosis is essential not only for fracture prevention but also reducing health care costs related to osteoporosis and preserving patient independence and functionality.^21-24 While initially developed in response to the COVID-19 pandemic, the dashboard remains useful. The VAPSHCS osteoporosis clinic is now staffed by 2 physicians (endocrine and rheumatology) and the dashboard is still in use. The RN coordinator spends about 15 minutes per week using the dashboard and managing the 67 veterans on osteoporosis therapy. This dashboard represents a sustainable clinical tool with the capacity to minimize osteoporosis care gaps and improve outcomes.

Osteoporotic fragility fractures constitute a significant public health concern, with 1 in 2 women and 1 in 5 men aged > 50 years sustaining an osteoporotic fracture.¹ Osteoporotic fractures are costly and associated with reduced quality of life and impaired survival.^2-6 Many interventions including fall mitigation, calcium, vitamin D supplementation, and osteoporosis—specific medications reduce fracture risk.⁷ New medications for treating osteoporosis, including anabolic therapies, are costly and require clinical oversight to ensure safe delivery. This includes laboratory monitoring, timing of in-clinic dosing and provision of sequence therapy.^8,9 COVID-19 introduced numerous barriers to osteoporosis care, raising concerns for medication interruption and patients lost to follow-up, which made monitoring these high risk and costly medications even more important.

The US Department of Veterans Affairs (VA) was an early adopter of using the electronic health record to analyze and implement system-wide processes for population management and quality improvement.¹⁰ This enabled the creation of clinical dashboards to display key performance indicator data that support quality improvement and patient care initiatives.^11-15 The VA Puget Sound Health Care System (VAPSHCS) has a dedicated osteoporosis clinic focused on preventing and treating veterans at high risk for fracture. Considering the growing utilization of osteoporosis medications, particularly those requiring timed sequential therapy to prevent bone mineral density loss and rebound osteoporotic fractures, close monitoring and follow-up is required. The COVID-19 pandemic made clear the need for proactive osteoporosis management. This article describes the creation and use of an automated clinic dashboard to identify and contact veterans with osteoporosis-related care needs, such as prescription refills, laboratory tests, and clinical visits.

Methods

An automated dashboard was created in partnership with VA pharmacy clinical informatics to display the osteoporosis medication prescription (including last refill), monitoring laboratory test values and most recent osteoporosis clinic visit for each clinic patient. Data from the VA Corporate Data Warehouse were extracted. The resulting tables were used to create a patient cohort with ≥ 1 active medication for alendronate, zoledronic acid, the parathyroid hormone analogues (PTH) teriparatide or abaloparatide, denosumab, or romosozumab. Notably, alendronate was the only oral bisphosphonate prescribed in the clinic. These data were formatted and displayed using Microsoft SQL Server Reporting Services. The secure and encrypted dashboard alerts the clinic staff when prescriptions, appointments, or laboratory tests, such as estimated glomerular filtration rate, 25-hydroxy vitamin D, calcium, and PTH are overdue or out of reference range. The dashboard tracked the most recent clinic visit or dual-energy X-ray absorptiometry (DXA) scan if performed within the VA. Overdue laboratory test alerts for bisphosphonates were flagged if delayed 12 months and 6 months for all other medications.

On March 20, 2021, the VAPSHCS osteoporosis clinic was staffed by 1 endocrinologist, 1 geriatrician, 1 rheumatologist, and 1 registered nurse (RN) coordinator. Overdue or out-of-range alerts were reviewed weekly by the RN coordinator, who addressed alerts. For any overdue laboratory work or prescription refills, the RN coordinator alerted the primary osteoporosis physician via the electronic health record for updated orders. Patients were contacted by phone to schedule a clinic visit, complete ordered laboratory work, or discuss osteoporosis medication refills based on the need identified by the dashboard. A letter was mailed to the patient requesting they contact the osteoporosis clinic for patients who could not be reached by phone after 2 attempts. If 3 attempts (2 phone calls and a letter) were unsuccessful, the osteoporosis physician was alerted so they could either call the patient, alert the primary referring clinician, or discontinue the osteoporosis medication.

Results

As of March 20, 2021, 139 patients were included on the dashboard. Ninety-two patients (66%) had unmet care needs and 29% were female. Ages ranged from 40 to 100 years (Table). The dashboard alerted the team to 3 patients lost to follow-up, all of whom had transferred to care outside the clinic. Twenty-three patients (17%) had overdue medications, including 2 (9%) who had not refilled oral bisphosphonate and 18 (78%) who were overdue for intravenous bisphosphonate treatment. One veteran flagged as overdue for their denosumab injection was unable to receive it due to a significant change in health status. Two veterans were overdue for a PTH analogue refill, 1 of whom had completed their course and transitioned to bisphosphonate.

The most common alert was 40 patients (29%) with overdue laboratory tests, 37 of which were receiving bisphosphonates. One patient included on the dashboard was taking romosozumab and all their monitoring parameters were up to date, thus their data were not included in the Table to prevent possible identification.

Discussion

A dashboard alerted the osteoporosis clinic team to veterans who were overdue for visits, laboratory work, and prescription renewals. Overall, 92 patients (66%) had unmet care needs identified by the dashboard, all of which were addressed with phone calls and/or letters. Most of the overdue medication refills and laboratory tests were for patients taking bisphosphonates avoiding VAPSHCS during the COVID-19 pandemic. The dashboard enabled the RN coordinator to promptly contact the patient, facilitate coordination of care requirements, and guarantee the safe and efficient delivery of osteoporosis care.

The VA has historically been a leader in the creation of clinical dashboards to support health campaigns.^11,12 These dashboards have successfully improved quality metrics towards the treatment of hepatitis C virus, heart failure, and highrisk opioid prescribing.^13-15 Data have shown that successful clinical dashboard implementation must be done in conjunction with protected time or staff to support care improvements.¹⁶ Additionally, the time required for clinical dashboards can limit their sustainability and feasibility.¹⁷ A study aimed at improving osteoporosis care for patients with Parkinson disease found that weekly multidisciplinary review of at-risk patients resulted in all new patients and 91% of follow-up patients receiving evidence- based osteoporosis treatments.¹⁷ However, despite the benefits, the intervention required significant time and resources. In contrast, the osteoporosis dashboard implemented at VAPSHCS was not time or resource intensive, requiring about 1 hour per week for the RN coordinator to review the dashboard and coordinate patient care needs.

Limitations

This study setting is unique from other health care organizations or VA health care systems. Implementation of a similar dashboard in other clinical settings where patients receive medical care in multiple health care systems may differ. The VA dedicates resources to support veteran population health management, which may not be available in other health care systems.^11,12 These issues may pose a barrier to implementing a similar osteoporosis dashboard in non-VA facilities. In addition, it is significant that while the dashboard can be reconfigured and adapted to track veterans across different VA facilities, certain complexities arise if essential data, such as laboratory tests and DXA imaging, are conducted outside of VA facilities. In such cases, manual entry of this information into the dashboard would be necessary. Because the dashboard was quickly developed during the COVID-19 pandemic, this study lacked preimplementation data on laboratory testing, medication refills, and DXA imaging, which would have enabled a comparison of adherence before and after dashboard implementation. Finally, we acknowledge the delay in publishing these findings; however, we believe sharing innovative approaches to providing care for high-risk populations is essential, as demonstrated during the COVID-19 pandemic.

Conclusions

An osteoporosis clinic dashboard served as a valuable clinical support tool to ensure safe and effective osteoporosis medication delivery at VAPSHCS. Considering the growing utilization of osteoporosis medications, this dashboard plays a vital role in facilitating care coordination for patients receiving these high-risk treatments.¹⁸ Use of the dashboard supported the effective use of high-cost osteoporosis medications and is likely to improve clinical osteoporosis outcomes.

Despite the known fracture risk reduction, osteoporosis medication adherence is low.^19,20 Maintaining consistent pharmacotherapy for osteoporosis is essential not only for fracture prevention but also reducing health care costs related to osteoporosis and preserving patient independence and functionality.^21-24 While initially developed in response to the COVID-19 pandemic, the dashboard remains useful. The VAPSHCS osteoporosis clinic is now staffed by 2 physicians (endocrine and rheumatology) and the dashboard is still in use. The RN coordinator spends about 15 minutes per week using the dashboard and managing the 67 veterans on osteoporosis therapy. This dashboard represents a sustainable clinical tool with the capacity to minimize osteoporosis care gaps and improve outcomes.

Osteoporotic fragility fractures constitute a significant public health concern, with 1 in 2 women and 1 in 5 men aged > 50 years sustaining an osteoporotic fracture.¹ Osteoporotic fractures are costly and associated with reduced quality of life and impaired survival.^2-6 Many interventions including fall mitigation, calcium, vitamin D supplementation, and osteoporosis—specific medications reduce fracture risk.⁷ New medications for treating osteoporosis, including anabolic therapies, are costly and require clinical oversight to ensure safe delivery. This includes laboratory monitoring, timing of in-clinic dosing and provision of sequence therapy.^8,9 COVID-19 introduced numerous barriers to osteoporosis care, raising concerns for medication interruption and patients lost to follow-up, which made monitoring these high risk and costly medications even more important.

The US Department of Veterans Affairs (VA) was an early adopter of using the electronic health record to analyze and implement system-wide processes for population management and quality improvement.¹⁰ This enabled the creation of clinical dashboards to display key performance indicator data that support quality improvement and patient care initiatives.^11-15 The VA Puget Sound Health Care System (VAPSHCS) has a dedicated osteoporosis clinic focused on preventing and treating veterans at high risk for fracture. Considering the growing utilization of osteoporosis medications, particularly those requiring timed sequential therapy to prevent bone mineral density loss and rebound osteoporotic fractures, close monitoring and follow-up is required. The COVID-19 pandemic made clear the need for proactive osteoporosis management. This article describes the creation and use of an automated clinic dashboard to identify and contact veterans with osteoporosis-related care needs, such as prescription refills, laboratory tests, and clinical visits.

Methods

An automated dashboard was created in partnership with VA pharmacy clinical informatics to display the osteoporosis medication prescription (including last refill), monitoring laboratory test values and most recent osteoporosis clinic visit for each clinic patient. Data from the VA Corporate Data Warehouse were extracted. The resulting tables were used to create a patient cohort with ≥ 1 active medication for alendronate, zoledronic acid, the parathyroid hormone analogues (PTH) teriparatide or abaloparatide, denosumab, or romosozumab. Notably, alendronate was the only oral bisphosphonate prescribed in the clinic. These data were formatted and displayed using Microsoft SQL Server Reporting Services. The secure and encrypted dashboard alerts the clinic staff when prescriptions, appointments, or laboratory tests, such as estimated glomerular filtration rate, 25-hydroxy vitamin D, calcium, and PTH are overdue or out of reference range. The dashboard tracked the most recent clinic visit or dual-energy X-ray absorptiometry (DXA) scan if performed within the VA. Overdue laboratory test alerts for bisphosphonates were flagged if delayed 12 months and 6 months for all other medications.

On March 20, 2021, the VAPSHCS osteoporosis clinic was staffed by 1 endocrinologist, 1 geriatrician, 1 rheumatologist, and 1 registered nurse (RN) coordinator. Overdue or out-of-range alerts were reviewed weekly by the RN coordinator, who addressed alerts. For any overdue laboratory work or prescription refills, the RN coordinator alerted the primary osteoporosis physician via the electronic health record for updated orders. Patients were contacted by phone to schedule a clinic visit, complete ordered laboratory work, or discuss osteoporosis medication refills based on the need identified by the dashboard. A letter was mailed to the patient requesting they contact the osteoporosis clinic for patients who could not be reached by phone after 2 attempts. If 3 attempts (2 phone calls and a letter) were unsuccessful, the osteoporosis physician was alerted so they could either call the patient, alert the primary referring clinician, or discontinue the osteoporosis medication.

Results

As of March 20, 2021, 139 patients were included on the dashboard. Ninety-two patients (66%) had unmet care needs and 29% were female. Ages ranged from 40 to 100 years (Table). The dashboard alerted the team to 3 patients lost to follow-up, all of whom had transferred to care outside the clinic. Twenty-three patients (17%) had overdue medications, including 2 (9%) who had not refilled oral bisphosphonate and 18 (78%) who were overdue for intravenous bisphosphonate treatment. One veteran flagged as overdue for their denosumab injection was unable to receive it due to a significant change in health status. Two veterans were overdue for a PTH analogue refill, 1 of whom had completed their course and transitioned to bisphosphonate.

The most common alert was 40 patients (29%) with overdue laboratory tests, 37 of which were receiving bisphosphonates. One patient included on the dashboard was taking romosozumab and all their monitoring parameters were up to date, thus their data were not included in the Table to prevent possible identification.

Discussion

A dashboard alerted the osteoporosis clinic team to veterans who were overdue for visits, laboratory work, and prescription renewals. Overall, 92 patients (66%) had unmet care needs identified by the dashboard, all of which were addressed with phone calls and/or letters. Most of the overdue medication refills and laboratory tests were for patients taking bisphosphonates avoiding VAPSHCS during the COVID-19 pandemic. The dashboard enabled the RN coordinator to promptly contact the patient, facilitate coordination of care requirements, and guarantee the safe and efficient delivery of osteoporosis care.

The VA has historically been a leader in the creation of clinical dashboards to support health campaigns.^11,12 These dashboards have successfully improved quality metrics towards the treatment of hepatitis C virus, heart failure, and highrisk opioid prescribing.^13-15 Data have shown that successful clinical dashboard implementation must be done in conjunction with protected time or staff to support care improvements.¹⁶ Additionally, the time required for clinical dashboards can limit their sustainability and feasibility.¹⁷ A study aimed at improving osteoporosis care for patients with Parkinson disease found that weekly multidisciplinary review of at-risk patients resulted in all new patients and 91% of follow-up patients receiving evidence- based osteoporosis treatments.¹⁷ However, despite the benefits, the intervention required significant time and resources. In contrast, the osteoporosis dashboard implemented at VAPSHCS was not time or resource intensive, requiring about 1 hour per week for the RN coordinator to review the dashboard and coordinate patient care needs.

Limitations

This study setting is unique from other health care organizations or VA health care systems. Implementation of a similar dashboard in other clinical settings where patients receive medical care in multiple health care systems may differ. The VA dedicates resources to support veteran population health management, which may not be available in other health care systems.^11,12 These issues may pose a barrier to implementing a similar osteoporosis dashboard in non-VA facilities. In addition, it is significant that while the dashboard can be reconfigured and adapted to track veterans across different VA facilities, certain complexities arise if essential data, such as laboratory tests and DXA imaging, are conducted outside of VA facilities. In such cases, manual entry of this information into the dashboard would be necessary. Because the dashboard was quickly developed during the COVID-19 pandemic, this study lacked preimplementation data on laboratory testing, medication refills, and DXA imaging, which would have enabled a comparison of adherence before and after dashboard implementation. Finally, we acknowledge the delay in publishing these findings; however, we believe sharing innovative approaches to providing care for high-risk populations is essential, as demonstrated during the COVID-19 pandemic.

Conclusions

An osteoporosis clinic dashboard served as a valuable clinical support tool to ensure safe and effective osteoporosis medication delivery at VAPSHCS. Considering the growing utilization of osteoporosis medications, this dashboard plays a vital role in facilitating care coordination for patients receiving these high-risk treatments.¹⁸ Use of the dashboard supported the effective use of high-cost osteoporosis medications and is likely to improve clinical osteoporosis outcomes.

Despite the known fracture risk reduction, osteoporosis medication adherence is low.^19,20 Maintaining consistent pharmacotherapy for osteoporosis is essential not only for fracture prevention but also reducing health care costs related to osteoporosis and preserving patient independence and functionality.^21-24 While initially developed in response to the COVID-19 pandemic, the dashboard remains useful. The VAPSHCS osteoporosis clinic is now staffed by 2 physicians (endocrine and rheumatology) and the dashboard is still in use. The RN coordinator spends about 15 minutes per week using the dashboard and managing the 67 veterans on osteoporosis therapy. This dashboard represents a sustainable clinical tool with the capacity to minimize osteoporosis care gaps and improve outcomes.

The impact of obesity in the United States is significant. Between August 2021 and August 2023, the prevalence of obesity (body mass index ≥ 30) in US adults was 40.3%.¹ The prevalence of obesity in adults aged 40 to 59 years was 46.4%, higher than the prevalence in adults aged 20 to 39 years (35.5%) and those aged ≥ 60 years (38.9%).¹ The excess annual medical costs associated with obesity in the US are estimated at nearly $173 billion.²

The first-line treatment for obesity is lifestyle modifications, including a healthy diet and exercise. When lifestyle modifications are not enough to achieve weight-loss goals, bariatric surgery and anti-obesity medications (AOMs) are often considered. Five medications were approved for the long-term tretament of obesity by the US Food and Drug Administration (FDA) between 2021 and 2023, when this study was conducted: semaglutide (Wegovy), liraglutide (Saxenda), phentermine and topiramate, naltrexone and bupropion, and orlistat. The clinically meaningful (and commonly accepted) weight-loss target for these medications is ≥ 5% from baseline by week 12 of the maximally tolerated dose of therapy. A 5% weight loss has been shown to be clinically significant in improving cardiometabolic risk factors.^3,4 These medications are intended to be used as an adjunct to healthy diet and exercise. Of note, semaglutide and liraglutide carry brand names, which are associated with different dosing for the treatment of type 2 diabetes mellitus (T2DM).

All 5 FDA-approved AOMs were available at the Veterans Affairs Sioux Falls Health Care System (VASFHCS) for the treatment of obesity at the time of the study. To qualify for an AOM, a veteran at VASFHCS must first work with a dietitian or be enrolled in the MOVE! clinic to participate in the weight management program, which focuses on dietary, exercise, and behavioral changes. At VASFHCS, AOMs are prescribed by primary care practitioners, clinical pharmacy providers, and advanced practitioners within the MOVE! program.

Ample data exist for the efficacy of AOMs. However, no published research has reported on AOM efficacy by age group (Appendix).^5-11 While most of the AOM clinical trials included older adults, the average age of participants was typically between 40 and 50 years. It is well-known that pharmacokinetic and pharmacodynamic changes occur as age increases. Renal and hepatic clearance is reduced while the volume distribution and sensitivities to some medications may increase. ¹² Although this study did not focus on specific pharmacokinetic and pharmacodynamic changes with respect to AOM, it is important to recognize that this may play a role in the efficacy and safety of AOMs in older adults.

Methods

This retrospective single-center chart review was performed using the VASFHCS Computerized Patient Record System to compare the efficacy of AOMs in older adults (aged ≥ 65 years) vs adults (aged < 65 years). The primary endpoint was the percent change in body weight from baseline to 6 and 12 months after initiation of AOM therapy in the older adult vs adult population. Secondary endpoints included changes in low-density lipoprotein (LDL), hemoglobin A_1c (HbA_1c), and blood pressure (BP) from baseline compared to 12 months on AOM therapy. HbA_1c was assessed in patients with T2DM or prediabetes at the time of AOM initiation. Two safety endpoints were also explored to determine the incidence of medication adverse events (AEs) and subsequent discontinuation of AOM. A subset analysis was performed to determine whether there was a difference in percent change in body weight between patients in 3 age groups: 18 to 40 years, 41 to 64 years, and ≥ 65 years.

The study population included patients who were prescribed an AOM between January 1, 2021, and June 30, 2023. Patients were excluded if they did not continue AOM therapy for ≥ 6 months after initiation or if they underwent gastric bypass surgery while undergoing AOM therapy. Patients taking semaglutide (Ozempic) or liraglutide (Victoza) for both T2DM and weight loss who were eventually switched to the weight loss formulations (Wegovy or Saxenda) were included. Patients who switched between semaglutide and liraglutide for weight loss were also included. Those taking semaglutide or liraglutide solely for T2DM treatment were excluded because they are dosed differently.

Collected data included age, gender, race, weight (baseline, 6 and 12 months after initiation of AOM), metabolic laboratory values/vital signs (HbA_1c, LDL, and BP at baseline and 12 months after initiation of AOM), diagnosis of T2DM or prediabetes, reported AEs associated with AOM therapy, and date of AOM initiation and discontinuation (if applicable). Baseline values were defined at the time of medication initiation or values documented within 6 months prior to medication initiation if true baseline data were not reported. If values were not recorded at months 6 and 12 after AOM initiation, values documented closest to those targets were used. Weights were used for baseline, 6-, and 12-month data unless they were unavailable due to use of virtual care modalities. In these cases, patient-reported weights were used. Patients were included in the 6-month data, but not the 12-month data, if they were taking AOMs for > 6 months but not for 12 months. If patients had been on multiple AOMs, baseline data were recorded at the start of the first medication that was used for 6 months or longer. Twelve-month data were recorded after subsequent medication change. Twelve-month metabolic laboratory values/vital signs were recorded for patients included in the study even if they did not complete ≥ 12 months of AOM therapy.

Statistical Analysis

Data from patients who were prescribed an AOM from January 2021 to June 2023 and who remained on the medication for ≥ 6 months were analyzed. Baseline characteristics were analyzed using descriptive statistics. The primary and secondary endpoints were evaluated using the t test. The safety endpoints were analyzed using descriptive statistics. An analysis of variance test was used for the subset analysis. Results with P < .05 were statistically significant.

Results

A total of 144 participants were included in this study, 116 in the adult group (aged < 65 years) and 28 in the older adult group (aged ≥ 65 years). Sixty-seven patients were excluded due to prespecified inclusion and exclusion criteria.

Other than the predetermined mean age differences (48 years vs 71 years), there were multiple differences in patient baseline characteristics. When comparing older adults and adults, average weight (283 lb vs 269 lb) and White race (89% vs 87%) were slightly higher in the older adult group. Also, a higher prevalence of T2DM (54% and 18%) and a lower prevalence of prediabetes (21% and 33%) was noted in the older adult group. HbA_1c and BP were similar between both groups at baseline, while LDL was slightly lower in the older adult group (Table 1).

Patients in the adult group lost a mean 7.0% and 8.7% of body weight at 6 and 12 months, respectively, while the older adult group lost 5.0% and 6.6% body weight at 6 and 12 months, respectively. The difference in percent change in body weight was not statistically different at 6 (P = .08) or 12 (P = .26) months between patients in the adult group vs the older adult group or in the specific age groups (18-40 years, 41-64 years, ≥ 65 years) at 6 months (P = .24) or 12 months (P = .53) (Figure).

At 12 months, the difference between the adult group vs the older adult group was not statistically significant for HbA_1c in patients with T2DM or prediabetes (P = .73), LDL (P = .95), systolic BP (P = .58), or diastolic BP (P = .51) (Table 2).

For the safety endpoint, the incidence of AEs was found to be different between groups. There were more reported AEs (61.2% vs 39.3%) and a greater increase in therapy discontinuation due to AEs (6.0% vs 0%) in the adult group compared to the older adult group (Table 3).

Discussion

Patients taking AOMs revealed no statistically significant difference in percent change in body weight at 6 or 12 months between adults aged < 65 years and older adults aged ≥ 65 years. The subset analysis also showed no statistically significant difference in change in percent body weight between more narrowly defined age groups of 18 to 40 years, 41 to 64 years, and ≥ 65 years. This suggests that AOM may have similar efficacy for weight loss in all ages of adults.

Secondary endpoint findings showed no statistically significant difference in HbA_1c (in patients with T2DM or prediabetes), LDL, or BP at 12 months between the 2 groups. Although this study did not differentiate secondary outcomes based on the individual AOM, the change in HbA_1c in both groups was expected, given that 70% of the patients included in this study were taking a glucagon-like peptide-1 agonist (liraglutide and semaglutide) at some point during the study. It’s also worth noting that secondary endpoints were collected for patients who discontinued the AOM between 6 and 12 months. Therefore, the patients’ HbA_1c, LDL, and BP may not have accurately reflected the change that could have been expected if they had continued AOM therapy beyond the 12-month period.

Due to the different mechanisms and range in efficacy that AOMs have in regard to weight loss, changes in all outcomes, including weight, HbA_1c, LDL, and BP were expected to vary as patients were included even after switching AOM (collection of data started after ≥ 6 months on a single AOM). Switching of AOM after the first 6 months of therapy was recorded in 25% of the patients in the ≥ 65 years group and 330% of the patients in the < 65 years group.

The incidence of AEs and subsequent discontinuation of AOMs in this study was higher in the adult group. This study excluded patients who did not continue taking an AOM for at least 6 months. As a result, the incidence of AEs between the 2 groups within the first 6 months of AOM therapy remains unknown. It is possible that during the first 6 months of therapy, patients aged < 65 years were more willing to tolerate or had fewer severe AEs compared with the older adult group. It’s also possible that the smaller number of patients in the older adult group was due to increased AEs that led them to discontinue early (before completion of 6 months of therapy) and/or prescriber discomfort in using AOMs in the older adult population. In addition, because the specific medication(s) taken by patients in each group were not detailed, it is unknown whether the adult group was taking AOMs associated with a greater number of AEs.

Limitations

This was a retrospective study with a relatively small sample size. A larger sample size may have shown more precise differences between age groups and may be more representative of the general population. Additionally, data were reliant on appropriate documentation, and adherence to AOM therapy was not assessed due to the retrospective nature of this study. At times, the study relied on patient reported data points, such as weight, if a clinic weight was not available. Also, this study did not account for many potential confounding factors such as other medications taken by the patient, which can affect outcomes including weight, HbA_1c, LDL, blood pressure, and AEs.

Conclusions

This retrospective study of patients taking AOMs showed no statistically significant difference in weight loss at 6 or 12 months between adults aged < 65 years and older adults aged ≥ 65 years. A subset analysis found no statistically significant difference in change in body weight between specific age groups (18-40 years, 41-64 years, and ≥ 65 years). There was also no statistically significant difference in secondary outcomes, including change in HbA_1c (in patients with T2DM or prediabetes), LDL or BP between age groups. The safety endpoints showed a higher incidence of medication AEs in the adult group, with more of these adults discontinuing therapy due to AEs. This study indicates that AOM may have similar outcomes for weight loss and metabolic laboratory values/vital sign changes between adults and older adults. Also, our findings suggest that patients aged < 65 years may experience more AEs than patients aged ≥ 65 years after ≥ 6 months of AOM therapy. Larger studies are needed to further evaluate these age-specific findings.

The impact of obesity in the United States is significant. Between August 2021 and August 2023, the prevalence of obesity (body mass index ≥ 30) in US adults was 40.3%.¹ The prevalence of obesity in adults aged 40 to 59 years was 46.4%, higher than the prevalence in adults aged 20 to 39 years (35.5%) and those aged ≥ 60 years (38.9%).¹ The excess annual medical costs associated with obesity in the US are estimated at nearly $173 billion.²

The first-line treatment for obesity is lifestyle modifications, including a healthy diet and exercise. When lifestyle modifications are not enough to achieve weight-loss goals, bariatric surgery and anti-obesity medications (AOMs) are often considered. Five medications were approved for the long-term tretament of obesity by the US Food and Drug Administration (FDA) between 2021 and 2023, when this study was conducted: semaglutide (Wegovy), liraglutide (Saxenda), phentermine and topiramate, naltrexone and bupropion, and orlistat. The clinically meaningful (and commonly accepted) weight-loss target for these medications is ≥ 5% from baseline by week 12 of the maximally tolerated dose of therapy. A 5% weight loss has been shown to be clinically significant in improving cardiometabolic risk factors.^3,4 These medications are intended to be used as an adjunct to healthy diet and exercise. Of note, semaglutide and liraglutide carry brand names, which are associated with different dosing for the treatment of type 2 diabetes mellitus (T2DM).

All 5 FDA-approved AOMs were available at the Veterans Affairs Sioux Falls Health Care System (VASFHCS) for the treatment of obesity at the time of the study. To qualify for an AOM, a veteran at VASFHCS must first work with a dietitian or be enrolled in the MOVE! clinic to participate in the weight management program, which focuses on dietary, exercise, and behavioral changes. At VASFHCS, AOMs are prescribed by primary care practitioners, clinical pharmacy providers, and advanced practitioners within the MOVE! program.

Ample data exist for the efficacy of AOMs. However, no published research has reported on AOM efficacy by age group (Appendix).^5-11 While most of the AOM clinical trials included older adults, the average age of participants was typically between 40 and 50 years. It is well-known that pharmacokinetic and pharmacodynamic changes occur as age increases. Renal and hepatic clearance is reduced while the volume distribution and sensitivities to some medications may increase. ¹² Although this study did not focus on specific pharmacokinetic and pharmacodynamic changes with respect to AOM, it is important to recognize that this may play a role in the efficacy and safety of AOMs in older adults.

Methods

This retrospective single-center chart review was performed using the VASFHCS Computerized Patient Record System to compare the efficacy of AOMs in older adults (aged ≥ 65 years) vs adults (aged < 65 years). The primary endpoint was the percent change in body weight from baseline to 6 and 12 months after initiation of AOM therapy in the older adult vs adult population. Secondary endpoints included changes in low-density lipoprotein (LDL), hemoglobin A_1c (HbA_1c), and blood pressure (BP) from baseline compared to 12 months on AOM therapy. HbA_1c was assessed in patients with T2DM or prediabetes at the time of AOM initiation. Two safety endpoints were also explored to determine the incidence of medication adverse events (AEs) and subsequent discontinuation of AOM. A subset analysis was performed to determine whether there was a difference in percent change in body weight between patients in 3 age groups: 18 to 40 years, 41 to 64 years, and ≥ 65 years.

The study population included patients who were prescribed an AOM between January 1, 2021, and June 30, 2023. Patients were excluded if they did not continue AOM therapy for ≥ 6 months after initiation or if they underwent gastric bypass surgery while undergoing AOM therapy. Patients taking semaglutide (Ozempic) or liraglutide (Victoza) for both T2DM and weight loss who were eventually switched to the weight loss formulations (Wegovy or Saxenda) were included. Patients who switched between semaglutide and liraglutide for weight loss were also included. Those taking semaglutide or liraglutide solely for T2DM treatment were excluded because they are dosed differently.

Collected data included age, gender, race, weight (baseline, 6 and 12 months after initiation of AOM), metabolic laboratory values/vital signs (HbA_1c, LDL, and BP at baseline and 12 months after initiation of AOM), diagnosis of T2DM or prediabetes, reported AEs associated with AOM therapy, and date of AOM initiation and discontinuation (if applicable). Baseline values were defined at the time of medication initiation or values documented within 6 months prior to medication initiation if true baseline data were not reported. If values were not recorded at months 6 and 12 after AOM initiation, values documented closest to those targets were used. Weights were used for baseline, 6-, and 12-month data unless they were unavailable due to use of virtual care modalities. In these cases, patient-reported weights were used. Patients were included in the 6-month data, but not the 12-month data, if they were taking AOMs for > 6 months but not for 12 months. If patients had been on multiple AOMs, baseline data were recorded at the start of the first medication that was used for 6 months or longer. Twelve-month data were recorded after subsequent medication change. Twelve-month metabolic laboratory values/vital signs were recorded for patients included in the study even if they did not complete ≥ 12 months of AOM therapy.

Statistical Analysis

Data from patients who were prescribed an AOM from January 2021 to June 2023 and who remained on the medication for ≥ 6 months were analyzed. Baseline characteristics were analyzed using descriptive statistics. The primary and secondary endpoints were evaluated using the t test. The safety endpoints were analyzed using descriptive statistics. An analysis of variance test was used for the subset analysis. Results with P < .05 were statistically significant.

Results

A total of 144 participants were included in this study, 116 in the adult group (aged < 65 years) and 28 in the older adult group (aged ≥ 65 years). Sixty-seven patients were excluded due to prespecified inclusion and exclusion criteria.

Other than the predetermined mean age differences (48 years vs 71 years), there were multiple differences in patient baseline characteristics. When comparing older adults and adults, average weight (283 lb vs 269 lb) and White race (89% vs 87%) were slightly higher in the older adult group. Also, a higher prevalence of T2DM (54% and 18%) and a lower prevalence of prediabetes (21% and 33%) was noted in the older adult group. HbA_1c and BP were similar between both groups at baseline, while LDL was slightly lower in the older adult group (Table 1).

Patients in the adult group lost a mean 7.0% and 8.7% of body weight at 6 and 12 months, respectively, while the older adult group lost 5.0% and 6.6% body weight at 6 and 12 months, respectively. The difference in percent change in body weight was not statistically different at 6 (P = .08) or 12 (P = .26) months between patients in the adult group vs the older adult group or in the specific age groups (18-40 years, 41-64 years, ≥ 65 years) at 6 months (P = .24) or 12 months (P = .53) (Figure).

At 12 months, the difference between the adult group vs the older adult group was not statistically significant for HbA_1c in patients with T2DM or prediabetes (P = .73), LDL (P = .95), systolic BP (P = .58), or diastolic BP (P = .51) (Table 2).

For the safety endpoint, the incidence of AEs was found to be different between groups. There were more reported AEs (61.2% vs 39.3%) and a greater increase in therapy discontinuation due to AEs (6.0% vs 0%) in the adult group compared to the older adult group (Table 3).

Discussion

Patients taking AOMs revealed no statistically significant difference in percent change in body weight at 6 or 12 months between adults aged < 65 years and older adults aged ≥ 65 years. The subset analysis also showed no statistically significant difference in change in percent body weight between more narrowly defined age groups of 18 to 40 years, 41 to 64 years, and ≥ 65 years. This suggests that AOM may have similar efficacy for weight loss in all ages of adults.

Secondary endpoint findings showed no statistically significant difference in HbA_1c (in patients with T2DM or prediabetes), LDL, or BP at 12 months between the 2 groups. Although this study did not differentiate secondary outcomes based on the individual AOM, the change in HbA_1c in both groups was expected, given that 70% of the patients included in this study were taking a glucagon-like peptide-1 agonist (liraglutide and semaglutide) at some point during the study. It’s also worth noting that secondary endpoints were collected for patients who discontinued the AOM between 6 and 12 months. Therefore, the patients’ HbA_1c, LDL, and BP may not have accurately reflected the change that could have been expected if they had continued AOM therapy beyond the 12-month period.

Due to the different mechanisms and range in efficacy that AOMs have in regard to weight loss, changes in all outcomes, including weight, HbA_1c, LDL, and BP were expected to vary as patients were included even after switching AOM (collection of data started after ≥ 6 months on a single AOM). Switching of AOM after the first 6 months of therapy was recorded in 25% of the patients in the ≥ 65 years group and 330% of the patients in the < 65 years group.

The incidence of AEs and subsequent discontinuation of AOMs in this study was higher in the adult group. This study excluded patients who did not continue taking an AOM for at least 6 months. As a result, the incidence of AEs between the 2 groups within the first 6 months of AOM therapy remains unknown. It is possible that during the first 6 months of therapy, patients aged < 65 years were more willing to tolerate or had fewer severe AEs compared with the older adult group. It’s also possible that the smaller number of patients in the older adult group was due to increased AEs that led them to discontinue early (before completion of 6 months of therapy) and/or prescriber discomfort in using AOMs in the older adult population. In addition, because the specific medication(s) taken by patients in each group were not detailed, it is unknown whether the adult group was taking AOMs associated with a greater number of AEs.

Limitations

This was a retrospective study with a relatively small sample size. A larger sample size may have shown more precise differences between age groups and may be more representative of the general population. Additionally, data were reliant on appropriate documentation, and adherence to AOM therapy was not assessed due to the retrospective nature of this study. At times, the study relied on patient reported data points, such as weight, if a clinic weight was not available. Also, this study did not account for many potential confounding factors such as other medications taken by the patient, which can affect outcomes including weight, HbA_1c, LDL, blood pressure, and AEs.

Conclusions

This retrospective study of patients taking AOMs showed no statistically significant difference in weight loss at 6 or 12 months between adults aged < 65 years and older adults aged ≥ 65 years. A subset analysis found no statistically significant difference in change in body weight between specific age groups (18-40 years, 41-64 years, and ≥ 65 years). There was also no statistically significant difference in secondary outcomes, including change in HbA_1c (in patients with T2DM or prediabetes), LDL or BP between age groups. The safety endpoints showed a higher incidence of medication AEs in the adult group, with more of these adults discontinuing therapy due to AEs. This study indicates that AOM may have similar outcomes for weight loss and metabolic laboratory values/vital sign changes between adults and older adults. Also, our findings suggest that patients aged < 65 years may experience more AEs than patients aged ≥ 65 years after ≥ 6 months of AOM therapy. Larger studies are needed to further evaluate these age-specific findings.

The impact of obesity in the United States is significant. Between August 2021 and August 2023, the prevalence of obesity (body mass index ≥ 30) in US adults was 40.3%.¹ The prevalence of obesity in adults aged 40 to 59 years was 46.4%, higher than the prevalence in adults aged 20 to 39 years (35.5%) and those aged ≥ 60 years (38.9%).¹ The excess annual medical costs associated with obesity in the US are estimated at nearly $173 billion.²

The first-line treatment for obesity is lifestyle modifications, including a healthy diet and exercise. When lifestyle modifications are not enough to achieve weight-loss goals, bariatric surgery and anti-obesity medications (AOMs) are often considered. Five medications were approved for the long-term tretament of obesity by the US Food and Drug Administration (FDA) between 2021 and 2023, when this study was conducted: semaglutide (Wegovy), liraglutide (Saxenda), phentermine and topiramate, naltrexone and bupropion, and orlistat. The clinically meaningful (and commonly accepted) weight-loss target for these medications is ≥ 5% from baseline by week 12 of the maximally tolerated dose of therapy. A 5% weight loss has been shown to be clinically significant in improving cardiometabolic risk factors.^3,4 These medications are intended to be used as an adjunct to healthy diet and exercise. Of note, semaglutide and liraglutide carry brand names, which are associated with different dosing for the treatment of type 2 diabetes mellitus (T2DM).

All 5 FDA-approved AOMs were available at the Veterans Affairs Sioux Falls Health Care System (VASFHCS) for the treatment of obesity at the time of the study. To qualify for an AOM, a veteran at VASFHCS must first work with a dietitian or be enrolled in the MOVE! clinic to participate in the weight management program, which focuses on dietary, exercise, and behavioral changes. At VASFHCS, AOMs are prescribed by primary care practitioners, clinical pharmacy providers, and advanced practitioners within the MOVE! program.

Ample data exist for the efficacy of AOMs. However, no published research has reported on AOM efficacy by age group (Appendix).^5-11 While most of the AOM clinical trials included older adults, the average age of participants was typically between 40 and 50 years. It is well-known that pharmacokinetic and pharmacodynamic changes occur as age increases. Renal and hepatic clearance is reduced while the volume distribution and sensitivities to some medications may increase. ¹² Although this study did not focus on specific pharmacokinetic and pharmacodynamic changes with respect to AOM, it is important to recognize that this may play a role in the efficacy and safety of AOMs in older adults.

Methods

This retrospective single-center chart review was performed using the VASFHCS Computerized Patient Record System to compare the efficacy of AOMs in older adults (aged ≥ 65 years) vs adults (aged < 65 years). The primary endpoint was the percent change in body weight from baseline to 6 and 12 months after initiation of AOM therapy in the older adult vs adult population. Secondary endpoints included changes in low-density lipoprotein (LDL), hemoglobin A_1c (HbA_1c), and blood pressure (BP) from baseline compared to 12 months on AOM therapy. HbA_1c was assessed in patients with T2DM or prediabetes at the time of AOM initiation. Two safety endpoints were also explored to determine the incidence of medication adverse events (AEs) and subsequent discontinuation of AOM. A subset analysis was performed to determine whether there was a difference in percent change in body weight between patients in 3 age groups: 18 to 40 years, 41 to 64 years, and ≥ 65 years.

The study population included patients who were prescribed an AOM between January 1, 2021, and June 30, 2023. Patients were excluded if they did not continue AOM therapy for ≥ 6 months after initiation or if they underwent gastric bypass surgery while undergoing AOM therapy. Patients taking semaglutide (Ozempic) or liraglutide (Victoza) for both T2DM and weight loss who were eventually switched to the weight loss formulations (Wegovy or Saxenda) were included. Patients who switched between semaglutide and liraglutide for weight loss were also included. Those taking semaglutide or liraglutide solely for T2DM treatment were excluded because they are dosed differently.

Collected data included age, gender, race, weight (baseline, 6 and 12 months after initiation of AOM), metabolic laboratory values/vital signs (HbA_1c, LDL, and BP at baseline and 12 months after initiation of AOM), diagnosis of T2DM or prediabetes, reported AEs associated with AOM therapy, and date of AOM initiation and discontinuation (if applicable). Baseline values were defined at the time of medication initiation or values documented within 6 months prior to medication initiation if true baseline data were not reported. If values were not recorded at months 6 and 12 after AOM initiation, values documented closest to those targets were used. Weights were used for baseline, 6-, and 12-month data unless they were unavailable due to use of virtual care modalities. In these cases, patient-reported weights were used. Patients were included in the 6-month data, but not the 12-month data, if they were taking AOMs for > 6 months but not for 12 months. If patients had been on multiple AOMs, baseline data were recorded at the start of the first medication that was used for 6 months or longer. Twelve-month data were recorded after subsequent medication change. Twelve-month metabolic laboratory values/vital signs were recorded for patients included in the study even if they did not complete ≥ 12 months of AOM therapy.

Statistical Analysis

Data from patients who were prescribed an AOM from January 2021 to June 2023 and who remained on the medication for ≥ 6 months were analyzed. Baseline characteristics were analyzed using descriptive statistics. The primary and secondary endpoints were evaluated using the t test. The safety endpoints were analyzed using descriptive statistics. An analysis of variance test was used for the subset analysis. Results with P < .05 were statistically significant.

Results

A total of 144 participants were included in this study, 116 in the adult group (aged < 65 years) and 28 in the older adult group (aged ≥ 65 years). Sixty-seven patients were excluded due to prespecified inclusion and exclusion criteria.

Other than the predetermined mean age differences (48 years vs 71 years), there were multiple differences in patient baseline characteristics. When comparing older adults and adults, average weight (283 lb vs 269 lb) and White race (89% vs 87%) were slightly higher in the older adult group. Also, a higher prevalence of T2DM (54% and 18%) and a lower prevalence of prediabetes (21% and 33%) was noted in the older adult group. HbA_1c and BP were similar between both groups at baseline, while LDL was slightly lower in the older adult group (Table 1).

Patients in the adult group lost a mean 7.0% and 8.7% of body weight at 6 and 12 months, respectively, while the older adult group lost 5.0% and 6.6% body weight at 6 and 12 months, respectively. The difference in percent change in body weight was not statistically different at 6 (P = .08) or 12 (P = .26) months between patients in the adult group vs the older adult group or in the specific age groups (18-40 years, 41-64 years, ≥ 65 years) at 6 months (P = .24) or 12 months (P = .53) (Figure).

At 12 months, the difference between the adult group vs the older adult group was not statistically significant for HbA_1c in patients with T2DM or prediabetes (P = .73), LDL (P = .95), systolic BP (P = .58), or diastolic BP (P = .51) (Table 2).

For the safety endpoint, the incidence of AEs was found to be different between groups. There were more reported AEs (61.2% vs 39.3%) and a greater increase in therapy discontinuation due to AEs (6.0% vs 0%) in the adult group compared to the older adult group (Table 3).

Discussion

Patients taking AOMs revealed no statistically significant difference in percent change in body weight at 6 or 12 months between adults aged < 65 years and older adults aged ≥ 65 years. The subset analysis also showed no statistically significant difference in change in percent body weight between more narrowly defined age groups of 18 to 40 years, 41 to 64 years, and ≥ 65 years. This suggests that AOM may have similar efficacy for weight loss in all ages of adults.

Secondary endpoint findings showed no statistically significant difference in HbA_1c (in patients with T2DM or prediabetes), LDL, or BP at 12 months between the 2 groups. Although this study did not differentiate secondary outcomes based on the individual AOM, the change in HbA_1c in both groups was expected, given that 70% of the patients included in this study were taking a glucagon-like peptide-1 agonist (liraglutide and semaglutide) at some point during the study. It’s also worth noting that secondary endpoints were collected for patients who discontinued the AOM between 6 and 12 months. Therefore, the patients’ HbA_1c, LDL, and BP may not have accurately reflected the change that could have been expected if they had continued AOM therapy beyond the 12-month period.

Due to the different mechanisms and range in efficacy that AOMs have in regard to weight loss, changes in all outcomes, including weight, HbA_1c, LDL, and BP were expected to vary as patients were included even after switching AOM (collection of data started after ≥ 6 months on a single AOM). Switching of AOM after the first 6 months of therapy was recorded in 25% of the patients in the ≥ 65 years group and 330% of the patients in the < 65 years group.

The incidence of AEs and subsequent discontinuation of AOMs in this study was higher in the adult group. This study excluded patients who did not continue taking an AOM for at least 6 months. As a result, the incidence of AEs between the 2 groups within the first 6 months of AOM therapy remains unknown. It is possible that during the first 6 months of therapy, patients aged < 65 years were more willing to tolerate or had fewer severe AEs compared with the older adult group. It’s also possible that the smaller number of patients in the older adult group was due to increased AEs that led them to discontinue early (before completion of 6 months of therapy) and/or prescriber discomfort in using AOMs in the older adult population. In addition, because the specific medication(s) taken by patients in each group were not detailed, it is unknown whether the adult group was taking AOMs associated with a greater number of AEs.

Limitations

This was a retrospective study with a relatively small sample size. A larger sample size may have shown more precise differences between age groups and may be more representative of the general population. Additionally, data were reliant on appropriate documentation, and adherence to AOM therapy was not assessed due to the retrospective nature of this study. At times, the study relied on patient reported data points, such as weight, if a clinic weight was not available. Also, this study did not account for many potential confounding factors such as other medications taken by the patient, which can affect outcomes including weight, HbA_1c, LDL, blood pressure, and AEs.

Conclusions

This retrospective study of patients taking AOMs showed no statistically significant difference in weight loss at 6 or 12 months between adults aged < 65 years and older adults aged ≥ 65 years. A subset analysis found no statistically significant difference in change in body weight between specific age groups (18-40 years, 41-64 years, and ≥ 65 years). There was also no statistically significant difference in secondary outcomes, including change in HbA_1c (in patients with T2DM or prediabetes), LDL or BP between age groups. The safety endpoints showed a higher incidence of medication AEs in the adult group, with more of these adults discontinuing therapy due to AEs. This study indicates that AOM may have similar outcomes for weight loss and metabolic laboratory values/vital sign changes between adults and older adults. Also, our findings suggest that patients aged < 65 years may experience more AEs than patients aged ≥ 65 years after ≥ 6 months of AOM therapy. Larger studies are needed to further evaluate these age-specific findings.

Chronic pruritus is a common problem among older individuals. During a session at the Dermatology Days of Paris 2024 conference dedicated to general practitioners, Juliette Delaunay, MD, a dermatologist and venereologist at Angers University Hospital Center in Angers, France, and Gabrielle Lisembard, MD, a general practitioner in the French town Grand-Fort-Philippe, discussed diagnostic approaches and key principles for the therapeutic management of pruritus.

Identifying Causes

“Pruritus in older people is most often linked to physiological changes in the skin caused by aging, leading to significant xerosis. However, before attributing it to aging, we need to rule out several causes,” Delaunay noted.

Beyond simple aging, one must consider autoimmune bullous dermatoses (bullous pemphigoid), drug-related causes, metabolic disorders (can occur at any age), cutaneous T-cell lymphomas, scabies, lice, and HIV infection.

 

Senile Pruritus

Aging-related xerosis can cause senile pruritus, often presenting as itching with scratch marks and dry skin. “This is a diagnosis of exclusion,” Delaunay insisted.

In older individuals with pruritus, initial examinations should include complete blood cell count (CBC), liver function tests, and thyroid-stimulating hormone levels. Syphilis serology, HIV testing, and beta-2 microglobulin levels are secondary evaluations. Renal function analysis may also be performed, and imaging may be required to investigate neoplasia.

“Annual etiological reassessment is essential if the initial evaluation is negative, as patients may later develop or report a neoplasia or hematological disorder,” Delaunay emphasized.

Paraneoplastic pruritus can occur, particularly those linked to hematological disorders (lymphomas, polycythemia, or myeloma).

 

Bullous Pemphigoid

Bullous pemphigoid often begins with pruritus, which can be severe and lead to insomnia. General practitioners should consider bullous pemphigoids when there is a bullous rash (tense blisters with citrine content) or an urticarial or chronic eczematous rash that does not heal spontaneously within a few days. The first-line biologic test to confirm the diagnosis is the CBC, which may reveal significant hypereosinophilia.

The diagnosis is confirmed by a skin biopsy showing a subepidermal blister with a preserved roof, unlike intraepidermal dermatoses, where the roof ruptures.

Direct immunofluorescence revealed deposits of immunoglobulin G antibodies along the dermoepidermal junction.

Approximately 40% of cases of bullous pemphigoid are associated with neurodegenerative diseases, such as stroke, parkinsonism, or dementia syndromes — occurring at a rate two to three times higher than in the general population.

It’s important to identify drugs that induce bullous pemphigoid, such as gliptins, anti-programmed cell death protein 1-programmed death-ligand 1 agents, loop diuretics (furosemide and bumetanide), anti-aldosterones (spironolactone), antiarrhythmics (amiodarone), and neuroleptics (phenothiazines).

“Stopping the medication is not mandatory if the bullous pemphigoid is well controlled by local or systemic treatments and the medication is essential. The decision to stop should be made on a case-by-case basis in consultation with the treating specialist,” Delaunay emphasized.

Treatment consists of very strong local corticosteroid therapy as the first-line treatment. If ineffective, systemic treatments based on methotrexate, oral corticosteroids, or immunomodulatory agents may be considered. Hospitalization is sometimes required.

 

Drug-Induced Pruritus

Drug-induced pruritus is common because older individuals often take multiple medications (antihypertensives, statins, oral hypoglycemics, psychotropic drugs, antiarrhythmics, etc.). “Sometimes, drug-induced pruritus can occur even if the medication was started several months or years ago,” Delaunay emphasized.

The lesions are generally nonspecific and scratching.

“This is a diagnosis of exclusion for other causes of pruritus. In the absence of specific lesions pointing to a dermatosis, eviction/reintroduction tests with treatments should be conducted one by one, which can be quite lengthy,” she explained.

 

Awareness for Scabies

Delaunay reminded attendees to consider scabies in older individuals when classic signs of pruritus flare up at night, with a rash affecting the face, scabs, or vesicles in the interdigital spaces of the hands, wrists, scrotal area, or the peri-mammary region.

“The incidence is increasing, particularly in nursing homes, where outbreaks pose a significant risk of rapid spread. Treatment involves three courses of topical and oral treatments administered on days 0, 7, and 14. All contact cases must also be treated. Sometimes, these thick lesions are stripped with 10% salicylated petroleum jelly. Environmental treatment with acaricides is essential, along with strict isolation measures,” Delaunay emphasized.

Adherent nits on the scalp or other hairy areas should raise suspicion of pediculosis.

 

Neurogenic and Psychogenic Origins

Neurogenic pruritus can occur during a stroke, presenting as contralateral pruritus, or in the presence of a brain tumor or following neurosurgery. Opioid-containing medications may also induce neurogenic pruritus.

The presence of unilateral painful or itchy sensations should prompt the investigation of shingles in older individuals.

Psychogenic pruritus is also common and can arise in the context of psychosis with parasitophobia or as part of anxiety-depression syndromes.

 

Supportive Measures

For managing pruritus, it is essential to:

• Keep nails trimmed short
• Wash with cold or lukewarm water
• Use lipid-rice soaps and syndets
• Avoid irritants, including antiseptics, cologne, no-rinse cleansers, and steroidal or nonsteroidal anti-inflammatory drugs
• Limit bathing frequency
• Avoid wearing nylon, wool, or tight clothing
• Minimize exposure to heat and excessive heating

“Alternatives to scratching, such as applying a moisturizing emollient, can be beneficial and may have a placebo effect,” explained the dermatologist. She further emphasized that local corticosteroids are effective only in the presence of inflammatory dermatosis and should not be applied to healthy skin. Similarly, antihistamines should only be prescribed if the pruritus is histamine-mediated.

Capsaicin may be useful in the treatment of localized neuropathic pruritus.

In cases of neurogenic pruritus, gabapentin and pregabalin may be prescribed, but tolerance can be problematic at this age. Other measures include acupuncture, cryotherapy, relaxation, hypnosis, psychotherapy, and music therapy. In cases of repeated therapeutic failure, patients may be treated with biotherapy (dupilumab) by a dermatologist.

 

This story was translated from Medscape’s French edition using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.

Chronic pruritus is a common problem among older individuals. During a session at the Dermatology Days of Paris 2024 conference dedicated to general practitioners, Juliette Delaunay, MD, a dermatologist and venereologist at Angers University Hospital Center in Angers, France, and Gabrielle Lisembard, MD, a general practitioner in the French town Grand-Fort-Philippe, discussed diagnostic approaches and key principles for the therapeutic management of pruritus.

Identifying Causes

“Pruritus in older people is most often linked to physiological changes in the skin caused by aging, leading to significant xerosis. However, before attributing it to aging, we need to rule out several causes,” Delaunay noted.

Beyond simple aging, one must consider autoimmune bullous dermatoses (bullous pemphigoid), drug-related causes, metabolic disorders (can occur at any age), cutaneous T-cell lymphomas, scabies, lice, and HIV infection.

 

Senile Pruritus

Aging-related xerosis can cause senile pruritus, often presenting as itching with scratch marks and dry skin. “This is a diagnosis of exclusion,” Delaunay insisted.

In older individuals with pruritus, initial examinations should include complete blood cell count (CBC), liver function tests, and thyroid-stimulating hormone levels. Syphilis serology, HIV testing, and beta-2 microglobulin levels are secondary evaluations. Renal function analysis may also be performed, and imaging may be required to investigate neoplasia.

“Annual etiological reassessment is essential if the initial evaluation is negative, as patients may later develop or report a neoplasia or hematological disorder,” Delaunay emphasized.

Paraneoplastic pruritus can occur, particularly those linked to hematological disorders (lymphomas, polycythemia, or myeloma).

 

Bullous Pemphigoid

Bullous pemphigoid often begins with pruritus, which can be severe and lead to insomnia. General practitioners should consider bullous pemphigoids when there is a bullous rash (tense blisters with citrine content) or an urticarial or chronic eczematous rash that does not heal spontaneously within a few days. The first-line biologic test to confirm the diagnosis is the CBC, which may reveal significant hypereosinophilia.

The diagnosis is confirmed by a skin biopsy showing a subepidermal blister with a preserved roof, unlike intraepidermal dermatoses, where the roof ruptures.

Direct immunofluorescence revealed deposits of immunoglobulin G antibodies along the dermoepidermal junction.

Approximately 40% of cases of bullous pemphigoid are associated with neurodegenerative diseases, such as stroke, parkinsonism, or dementia syndromes — occurring at a rate two to three times higher than in the general population.

It’s important to identify drugs that induce bullous pemphigoid, such as gliptins, anti-programmed cell death protein 1-programmed death-ligand 1 agents, loop diuretics (furosemide and bumetanide), anti-aldosterones (spironolactone), antiarrhythmics (amiodarone), and neuroleptics (phenothiazines).

“Stopping the medication is not mandatory if the bullous pemphigoid is well controlled by local or systemic treatments and the medication is essential. The decision to stop should be made on a case-by-case basis in consultation with the treating specialist,” Delaunay emphasized.

Treatment consists of very strong local corticosteroid therapy as the first-line treatment. If ineffective, systemic treatments based on methotrexate, oral corticosteroids, or immunomodulatory agents may be considered. Hospitalization is sometimes required.

 

Drug-Induced Pruritus

Drug-induced pruritus is common because older individuals often take multiple medications (antihypertensives, statins, oral hypoglycemics, psychotropic drugs, antiarrhythmics, etc.). “Sometimes, drug-induced pruritus can occur even if the medication was started several months or years ago,” Delaunay emphasized.

The lesions are generally nonspecific and scratching.

“This is a diagnosis of exclusion for other causes of pruritus. In the absence of specific lesions pointing to a dermatosis, eviction/reintroduction tests with treatments should be conducted one by one, which can be quite lengthy,” she explained.

 

Awareness for Scabies

Delaunay reminded attendees to consider scabies in older individuals when classic signs of pruritus flare up at night, with a rash affecting the face, scabs, or vesicles in the interdigital spaces of the hands, wrists, scrotal area, or the peri-mammary region.

“The incidence is increasing, particularly in nursing homes, where outbreaks pose a significant risk of rapid spread. Treatment involves three courses of topical and oral treatments administered on days 0, 7, and 14. All contact cases must also be treated. Sometimes, these thick lesions are stripped with 10% salicylated petroleum jelly. Environmental treatment with acaricides is essential, along with strict isolation measures,” Delaunay emphasized.

Adherent nits on the scalp or other hairy areas should raise suspicion of pediculosis.

 

Neurogenic and Psychogenic Origins

Neurogenic pruritus can occur during a stroke, presenting as contralateral pruritus, or in the presence of a brain tumor or following neurosurgery. Opioid-containing medications may also induce neurogenic pruritus.

The presence of unilateral painful or itchy sensations should prompt the investigation of shingles in older individuals.

Psychogenic pruritus is also common and can arise in the context of psychosis with parasitophobia or as part of anxiety-depression syndromes.

 

Supportive Measures

For managing pruritus, it is essential to:

• Keep nails trimmed short
• Wash with cold or lukewarm water
• Use lipid-rice soaps and syndets
• Avoid irritants, including antiseptics, cologne, no-rinse cleansers, and steroidal or nonsteroidal anti-inflammatory drugs
• Limit bathing frequency
• Avoid wearing nylon, wool, or tight clothing
• Minimize exposure to heat and excessive heating

“Alternatives to scratching, such as applying a moisturizing emollient, can be beneficial and may have a placebo effect,” explained the dermatologist. She further emphasized that local corticosteroids are effective only in the presence of inflammatory dermatosis and should not be applied to healthy skin. Similarly, antihistamines should only be prescribed if the pruritus is histamine-mediated.

Capsaicin may be useful in the treatment of localized neuropathic pruritus.

In cases of neurogenic pruritus, gabapentin and pregabalin may be prescribed, but tolerance can be problematic at this age. Other measures include acupuncture, cryotherapy, relaxation, hypnosis, psychotherapy, and music therapy. In cases of repeated therapeutic failure, patients may be treated with biotherapy (dupilumab) by a dermatologist.

 

This story was translated from Medscape’s French edition using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.

Chronic pruritus is a common problem among older individuals. During a session at the Dermatology Days of Paris 2024 conference dedicated to general practitioners, Juliette Delaunay, MD, a dermatologist and venereologist at Angers University Hospital Center in Angers, France, and Gabrielle Lisembard, MD, a general practitioner in the French town Grand-Fort-Philippe, discussed diagnostic approaches and key principles for the therapeutic management of pruritus.

Identifying Causes

“Pruritus in older people is most often linked to physiological changes in the skin caused by aging, leading to significant xerosis. However, before attributing it to aging, we need to rule out several causes,” Delaunay noted.

Beyond simple aging, one must consider autoimmune bullous dermatoses (bullous pemphigoid), drug-related causes, metabolic disorders (can occur at any age), cutaneous T-cell lymphomas, scabies, lice, and HIV infection.

 

Senile Pruritus

Aging-related xerosis can cause senile pruritus, often presenting as itching with scratch marks and dry skin. “This is a diagnosis of exclusion,” Delaunay insisted.

In older individuals with pruritus, initial examinations should include complete blood cell count (CBC), liver function tests, and thyroid-stimulating hormone levels. Syphilis serology, HIV testing, and beta-2 microglobulin levels are secondary evaluations. Renal function analysis may also be performed, and imaging may be required to investigate neoplasia.

“Annual etiological reassessment is essential if the initial evaluation is negative, as patients may later develop or report a neoplasia or hematological disorder,” Delaunay emphasized.

Paraneoplastic pruritus can occur, particularly those linked to hematological disorders (lymphomas, polycythemia, or myeloma).

 

Bullous Pemphigoid

Bullous pemphigoid often begins with pruritus, which can be severe and lead to insomnia. General practitioners should consider bullous pemphigoids when there is a bullous rash (tense blisters with citrine content) or an urticarial or chronic eczematous rash that does not heal spontaneously within a few days. The first-line biologic test to confirm the diagnosis is the CBC, which may reveal significant hypereosinophilia.

The diagnosis is confirmed by a skin biopsy showing a subepidermal blister with a preserved roof, unlike intraepidermal dermatoses, where the roof ruptures.

Direct immunofluorescence revealed deposits of immunoglobulin G antibodies along the dermoepidermal junction.

Approximately 40% of cases of bullous pemphigoid are associated with neurodegenerative diseases, such as stroke, parkinsonism, or dementia syndromes — occurring at a rate two to three times higher than in the general population.

It’s important to identify drugs that induce bullous pemphigoid, such as gliptins, anti-programmed cell death protein 1-programmed death-ligand 1 agents, loop diuretics (furosemide and bumetanide), anti-aldosterones (spironolactone), antiarrhythmics (amiodarone), and neuroleptics (phenothiazines).

“Stopping the medication is not mandatory if the bullous pemphigoid is well controlled by local or systemic treatments and the medication is essential. The decision to stop should be made on a case-by-case basis in consultation with the treating specialist,” Delaunay emphasized.

Treatment consists of very strong local corticosteroid therapy as the first-line treatment. If ineffective, systemic treatments based on methotrexate, oral corticosteroids, or immunomodulatory agents may be considered. Hospitalization is sometimes required.

 

Drug-Induced Pruritus

Drug-induced pruritus is common because older individuals often take multiple medications (antihypertensives, statins, oral hypoglycemics, psychotropic drugs, antiarrhythmics, etc.). “Sometimes, drug-induced pruritus can occur even if the medication was started several months or years ago,” Delaunay emphasized.

The lesions are generally nonspecific and scratching.

“This is a diagnosis of exclusion for other causes of pruritus. In the absence of specific lesions pointing to a dermatosis, eviction/reintroduction tests with treatments should be conducted one by one, which can be quite lengthy,” she explained.

 

Awareness for Scabies

Delaunay reminded attendees to consider scabies in older individuals when classic signs of pruritus flare up at night, with a rash affecting the face, scabs, or vesicles in the interdigital spaces of the hands, wrists, scrotal area, or the peri-mammary region.

“The incidence is increasing, particularly in nursing homes, where outbreaks pose a significant risk of rapid spread. Treatment involves three courses of topical and oral treatments administered on days 0, 7, and 14. All contact cases must also be treated. Sometimes, these thick lesions are stripped with 10% salicylated petroleum jelly. Environmental treatment with acaricides is essential, along with strict isolation measures,” Delaunay emphasized.

Adherent nits on the scalp or other hairy areas should raise suspicion of pediculosis.

 

Neurogenic and Psychogenic Origins

Neurogenic pruritus can occur during a stroke, presenting as contralateral pruritus, or in the presence of a brain tumor or following neurosurgery. Opioid-containing medications may also induce neurogenic pruritus.

The presence of unilateral painful or itchy sensations should prompt the investigation of shingles in older individuals.

Psychogenic pruritus is also common and can arise in the context of psychosis with parasitophobia or as part of anxiety-depression syndromes.

 

Supportive Measures

For managing pruritus, it is essential to:

• Keep nails trimmed short
• Wash with cold or lukewarm water
• Use lipid-rice soaps and syndets
• Avoid irritants, including antiseptics, cologne, no-rinse cleansers, and steroidal or nonsteroidal anti-inflammatory drugs
• Limit bathing frequency
• Avoid wearing nylon, wool, or tight clothing
• Minimize exposure to heat and excessive heating

“Alternatives to scratching, such as applying a moisturizing emollient, can be beneficial and may have a placebo effect,” explained the dermatologist. She further emphasized that local corticosteroids are effective only in the presence of inflammatory dermatosis and should not be applied to healthy skin. Similarly, antihistamines should only be prescribed if the pruritus is histamine-mediated.

Capsaicin may be useful in the treatment of localized neuropathic pruritus.

In cases of neurogenic pruritus, gabapentin and pregabalin may be prescribed, but tolerance can be problematic at this age. Other measures include acupuncture, cryotherapy, relaxation, hypnosis, psychotherapy, and music therapy. In cases of repeated therapeutic failure, patients may be treated with biotherapy (dupilumab) by a dermatologist.

 

This story was translated from Medscape’s French edition using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.

TOPLINE:

Among 57,086 older adults, new gabapentin users demonstrated lower fall-related healthcare visits than duloxetine users, with a weighted cumulative incidence of 84.44 vs 158.21 per 1000 person-years at 180 days. Incident gabapentin use showed a 48% lower hazard of falls at 6-month follow-up, with no increase in severe fall-related events.
 

METHODOLOGY:

• Researchers conducted a new user, active comparator cohort study using IBM MarketScan Research Databases from January 2014 to December 2021.
• Analysis included 57,086 adults aged 65 years or older with postherpetic neuralgia, diabetic neuropathy, or fibromyalgia, excluding those with depression, anxiety, seizures, or cancer in the prior 365 days.
• The primary outcome measured the hazard of experiencing any fall-related visit in the 6 months after initiating gabapentin or duloxetine until treatment discontinuation.
• Secondary outcomes examined severe fall-related events, including falls with hip fractures or emergency department visits/hospitalizations associated with falls.

TAKEAWAY:

• The analytic cohort included 52,152 gabapentin users and 4934 duloxetine users, with a median follow-up duration of 30 days (interquartile range, 30-90 days).
• Weighted cumulative incidence of fall-related visits per 1000 person-years at 30, 90, and 180 days was 103.60, 90.44, and 84.44 for gabapentin users vs 203.43, 177.73, and 158.21 for duloxetine users.
• At 6-month follow-up, incident gabapentin users demonstrated lower hazard of falls (hazard ratio, 0.52; 95% CI, 0.43-0.64), with no difference in hazards of severe falls.
• Results remained consistent across sensitivity and subgroup analyses.

IN PRACTICE:

“One bioplausible explanation for our results is that gabapentin is a highly titratable medication and many in our cohort started on low doses. Alternatively, duloxetine is usually titrated only once or twice. Thus, although it may be that gabapentin is simply safer than duloxetine from a falls perspective, it may also be likely that we are measuring specific clinical scenarios, the peri-initiation and titration period, in which gabapentin may be less likely to cause falls than duloxetine,” the authors wrote.
 

SOURCE:

The study was led by Alexander Chaitoff, MD, MPH, Department of Internal Medicine, University of Michigan School of Medicine in Ann Arbor, and Center for Healthcare Delivery Sciences, Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School in Boston. It was published online in Annals of Internal Medicine.
 

LIMITATIONS:

Despite the design aimed at limiting confounding effects, the observational nature of the study introduces potential bias. Claims data may undercount falls for which patients do not seek care, though this limitation likely affects both medication groups equally. The commercial claims database includes only Medicare supplemental insurance beneficiaries, potentially limiting generalizability. Regional variations in prescribing patterns could not be accounted for in the analysis.
 

DISCLOSURES:

No funding was provided for this study.
 

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com. 

TOPLINE:

Among 57,086 older adults, new gabapentin users demonstrated lower fall-related healthcare visits than duloxetine users, with a weighted cumulative incidence of 84.44 vs 158.21 per 1000 person-years at 180 days. Incident gabapentin use showed a 48% lower hazard of falls at 6-month follow-up, with no increase in severe fall-related events.
 

METHODOLOGY:

• Researchers conducted a new user, active comparator cohort study using IBM MarketScan Research Databases from January 2014 to December 2021.
• Analysis included 57,086 adults aged 65 years or older with postherpetic neuralgia, diabetic neuropathy, or fibromyalgia, excluding those with depression, anxiety, seizures, or cancer in the prior 365 days.
• The primary outcome measured the hazard of experiencing any fall-related visit in the 6 months after initiating gabapentin or duloxetine until treatment discontinuation.
• Secondary outcomes examined severe fall-related events, including falls with hip fractures or emergency department visits/hospitalizations associated with falls.

TAKEAWAY:

• The analytic cohort included 52,152 gabapentin users and 4934 duloxetine users, with a median follow-up duration of 30 days (interquartile range, 30-90 days).
• Weighted cumulative incidence of fall-related visits per 1000 person-years at 30, 90, and 180 days was 103.60, 90.44, and 84.44 for gabapentin users vs 203.43, 177.73, and 158.21 for duloxetine users.
• At 6-month follow-up, incident gabapentin users demonstrated lower hazard of falls (hazard ratio, 0.52; 95% CI, 0.43-0.64), with no difference in hazards of severe falls.
• Results remained consistent across sensitivity and subgroup analyses.

IN PRACTICE:

“One bioplausible explanation for our results is that gabapentin is a highly titratable medication and many in our cohort started on low doses. Alternatively, duloxetine is usually titrated only once or twice. Thus, although it may be that gabapentin is simply safer than duloxetine from a falls perspective, it may also be likely that we are measuring specific clinical scenarios, the peri-initiation and titration period, in which gabapentin may be less likely to cause falls than duloxetine,” the authors wrote.
 

SOURCE:

The study was led by Alexander Chaitoff, MD, MPH, Department of Internal Medicine, University of Michigan School of Medicine in Ann Arbor, and Center for Healthcare Delivery Sciences, Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School in Boston. It was published online in Annals of Internal Medicine.
 

LIMITATIONS:

Despite the design aimed at limiting confounding effects, the observational nature of the study introduces potential bias. Claims data may undercount falls for which patients do not seek care, though this limitation likely affects both medication groups equally. The commercial claims database includes only Medicare supplemental insurance beneficiaries, potentially limiting generalizability. Regional variations in prescribing patterns could not be accounted for in the analysis.
 

DISCLOSURES:

No funding was provided for this study.
 

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com. 

TOPLINE:

Among 57,086 older adults, new gabapentin users demonstrated lower fall-related healthcare visits than duloxetine users, with a weighted cumulative incidence of 84.44 vs 158.21 per 1000 person-years at 180 days. Incident gabapentin use showed a 48% lower hazard of falls at 6-month follow-up, with no increase in severe fall-related events.
 

METHODOLOGY:

• Researchers conducted a new user, active comparator cohort study using IBM MarketScan Research Databases from January 2014 to December 2021.
• Analysis included 57,086 adults aged 65 years or older with postherpetic neuralgia, diabetic neuropathy, or fibromyalgia, excluding those with depression, anxiety, seizures, or cancer in the prior 365 days.
• The primary outcome measured the hazard of experiencing any fall-related visit in the 6 months after initiating gabapentin or duloxetine until treatment discontinuation.
• Secondary outcomes examined severe fall-related events, including falls with hip fractures or emergency department visits/hospitalizations associated with falls.

TAKEAWAY:

• The analytic cohort included 52,152 gabapentin users and 4934 duloxetine users, with a median follow-up duration of 30 days (interquartile range, 30-90 days).
• Weighted cumulative incidence of fall-related visits per 1000 person-years at 30, 90, and 180 days was 103.60, 90.44, and 84.44 for gabapentin users vs 203.43, 177.73, and 158.21 for duloxetine users.
• At 6-month follow-up, incident gabapentin users demonstrated lower hazard of falls (hazard ratio, 0.52; 95% CI, 0.43-0.64), with no difference in hazards of severe falls.
• Results remained consistent across sensitivity and subgroup analyses.

IN PRACTICE:

“One bioplausible explanation for our results is that gabapentin is a highly titratable medication and many in our cohort started on low doses. Alternatively, duloxetine is usually titrated only once or twice. Thus, although it may be that gabapentin is simply safer than duloxetine from a falls perspective, it may also be likely that we are measuring specific clinical scenarios, the peri-initiation and titration period, in which gabapentin may be less likely to cause falls than duloxetine,” the authors wrote.
 

SOURCE:

The study was led by Alexander Chaitoff, MD, MPH, Department of Internal Medicine, University of Michigan School of Medicine in Ann Arbor, and Center for Healthcare Delivery Sciences, Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School in Boston. It was published online in Annals of Internal Medicine.
 

LIMITATIONS:

Despite the design aimed at limiting confounding effects, the observational nature of the study introduces potential bias. Claims data may undercount falls for which patients do not seek care, though this limitation likely affects both medication groups equally. The commercial claims database includes only Medicare supplemental insurance beneficiaries, potentially limiting generalizability. Regional variations in prescribing patterns could not be accounted for in the analysis.
 

DISCLOSURES:

No funding was provided for this study.
 

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com. 

TOPLINE:

About one third of US adults aged 50-80 years report feeling lonely and socially isolated, a new study of data from 2018-2024 shows. While the levels have returned to the prepandemic range, investigators say the findings suggest clinicians should screen for loneliness and isolation.

METHODOLOGY:

• Researchers conducted a nationally representative survey of US adults aged 50-80 years through the University of Michigan National Poll on Healthy Aging at six timepoints between 2018 and 2024.
• Data collection involved online surveys conducted using the Ipsos KnowledgePanel from 2018 to 2021, transitioning to online and phone surveys conducted using the National Opinion Research Center AmeriSpeak panel from 2022 to 2024.
• Sample sizes ranged between 2051 and 2576 respondents, with completion rates ranging from 61% to 78% across the survey periods.

TAKEAWAY:

• Loneliness rates among adults aged 50-80 years showed notable fluctuation, starting at 34% (95% CI, 31.7%-36.2%) in 2018, rising to 41% (95% CI, 39.1%-43.7%) in 2020, and returning to 33% (95% CI, 31.7%-35.1%) by 2024.
• Social isolation showed a similar pattern in the study group, starting at 27% (95% CI, 24.5%-28.8%) in 2018, peaking at 56% (95% CI, 53.4%-58.1%) in 2020, and declining to 29% (95% CI, 27.5%-30.9%) by 2024.
• Higher loneliness and social isolation rates were frequently reported among individuals who did not work, lived alone, had lower household incomes, and had self-reported fair and poor physical and mental health than those who reported excellent, very good, or good health.

IN PRACTICE:

The findings suggest that “much like routinely asking about diet and exercise, clinicians should consider screening older adults for loneliness and social isolation and connect them with appropriate resources,” the investigators wrote.

SOURCE:

The study was led by Preeti N. Malani, MD, MSJ, University of Michigan Medical School, Ann Arbor. It was published online on December 9 in JAMA.

LIMITATIONS:

The study was limited by possible recall bias, reliance on self-reported data, lack of longitudinal results, and differences in survey timing, panels, and question framing across years. The findings may not have been applicable to excluded groups such as nursing home residents or individuals aged > 80 years, which limited their generalizability.

DISCLOSURES:

The study was supported by AARP and Michigan Medicine and the Department of Veterans Affairs, Veterans Health Administration, and Health Systems Research. One author reported receiving consulting fees and honoraria from various organizations. Details are provided in the original article.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.

TOPLINE:

About one third of US adults aged 50-80 years report feeling lonely and socially isolated, a new study of data from 2018-2024 shows. While the levels have returned to the prepandemic range, investigators say the findings suggest clinicians should screen for loneliness and isolation.

METHODOLOGY:

• Researchers conducted a nationally representative survey of US adults aged 50-80 years through the University of Michigan National Poll on Healthy Aging at six timepoints between 2018 and 2024.
• Data collection involved online surveys conducted using the Ipsos KnowledgePanel from 2018 to 2021, transitioning to online and phone surveys conducted using the National Opinion Research Center AmeriSpeak panel from 2022 to 2024.
• Sample sizes ranged between 2051 and 2576 respondents, with completion rates ranging from 61% to 78% across the survey periods.

TAKEAWAY:

• Loneliness rates among adults aged 50-80 years showed notable fluctuation, starting at 34% (95% CI, 31.7%-36.2%) in 2018, rising to 41% (95% CI, 39.1%-43.7%) in 2020, and returning to 33% (95% CI, 31.7%-35.1%) by 2024.
• Social isolation showed a similar pattern in the study group, starting at 27% (95% CI, 24.5%-28.8%) in 2018, peaking at 56% (95% CI, 53.4%-58.1%) in 2020, and declining to 29% (95% CI, 27.5%-30.9%) by 2024.
• Higher loneliness and social isolation rates were frequently reported among individuals who did not work, lived alone, had lower household incomes, and had self-reported fair and poor physical and mental health than those who reported excellent, very good, or good health.

IN PRACTICE:

The findings suggest that “much like routinely asking about diet and exercise, clinicians should consider screening older adults for loneliness and social isolation and connect them with appropriate resources,” the investigators wrote.

SOURCE:

The study was led by Preeti N. Malani, MD, MSJ, University of Michigan Medical School, Ann Arbor. It was published online on December 9 in JAMA.

LIMITATIONS:

The study was limited by possible recall bias, reliance on self-reported data, lack of longitudinal results, and differences in survey timing, panels, and question framing across years. The findings may not have been applicable to excluded groups such as nursing home residents or individuals aged > 80 years, which limited their generalizability.

DISCLOSURES:

The study was supported by AARP and Michigan Medicine and the Department of Veterans Affairs, Veterans Health Administration, and Health Systems Research. One author reported receiving consulting fees and honoraria from various organizations. Details are provided in the original article.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.

TOPLINE:

About one third of US adults aged 50-80 years report feeling lonely and socially isolated, a new study of data from 2018-2024 shows. While the levels have returned to the prepandemic range, investigators say the findings suggest clinicians should screen for loneliness and isolation.

METHODOLOGY:

• Researchers conducted a nationally representative survey of US adults aged 50-80 years through the University of Michigan National Poll on Healthy Aging at six timepoints between 2018 and 2024.
• Data collection involved online surveys conducted using the Ipsos KnowledgePanel from 2018 to 2021, transitioning to online and phone surveys conducted using the National Opinion Research Center AmeriSpeak panel from 2022 to 2024.
• Sample sizes ranged between 2051 and 2576 respondents, with completion rates ranging from 61% to 78% across the survey periods.

TAKEAWAY:

• Loneliness rates among adults aged 50-80 years showed notable fluctuation, starting at 34% (95% CI, 31.7%-36.2%) in 2018, rising to 41% (95% CI, 39.1%-43.7%) in 2020, and returning to 33% (95% CI, 31.7%-35.1%) by 2024.
• Social isolation showed a similar pattern in the study group, starting at 27% (95% CI, 24.5%-28.8%) in 2018, peaking at 56% (95% CI, 53.4%-58.1%) in 2020, and declining to 29% (95% CI, 27.5%-30.9%) by 2024.
• Higher loneliness and social isolation rates were frequently reported among individuals who did not work, lived alone, had lower household incomes, and had self-reported fair and poor physical and mental health than those who reported excellent, very good, or good health.

IN PRACTICE:

The findings suggest that “much like routinely asking about diet and exercise, clinicians should consider screening older adults for loneliness and social isolation and connect them with appropriate resources,” the investigators wrote.

SOURCE:

The study was led by Preeti N. Malani, MD, MSJ, University of Michigan Medical School, Ann Arbor. It was published online on December 9 in JAMA.

LIMITATIONS:

The study was limited by possible recall bias, reliance on self-reported data, lack of longitudinal results, and differences in survey timing, panels, and question framing across years. The findings may not have been applicable to excluded groups such as nursing home residents or individuals aged > 80 years, which limited their generalizability.

DISCLOSURES:

The study was supported by AARP and Michigan Medicine and the Department of Veterans Affairs, Veterans Health Administration, and Health Systems Research. One author reported receiving consulting fees and honoraria from various organizations. Details are provided in the original article.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.

Older adults with major depressive disorder (MDD) exhibit riskier driving behaviors, compared with their nondepressed peers, including hard braking, cornering, and unpredictable driving patterns, new research showed.

Data for the study came from commercial vehicle data trackers installed in participants’ vehicles. After about a year of follow-up, the investigators found that MDD was associated with an increase in the amount and severity of risking driving, even after they controlled for antidepressant use.

Late-life depression often goes undiagnosed, and the new findings highlight the importance of routine depression screening and targeted interventions to ensure driving safety among older adults, the study team said.

“By using longitudinal, real-world driving data rather than controlled settings or self-reports, the study provides robust evidence of how MDD influences driving behaviors in day-to-day contexts,” first author Ganesh M. Babulal, PhD, OTD, with the Department of Neurology, Washington University School of Medicine in St Louis, Missouri, said in an interview.

“By analyzing the influence of antidepressant use and overall medication load, the study disentangles the effects of MDD from those of driver-impairing medications, further clarifying the unique contributions of depression to driving behaviors,” Babulal noted.

The study was published online in JAMA Network Open.

 

Road Risks 

As the number of older adults grows, safe driving practices in this age group become increasingly crucial. By 2050, one quarter of drivers in the United States will be older than 65 years. MDD affects about 8% of US adults and is linked to cognitive impairments that may compromise driving safety.

Prior studies revealed a link between depression and increased car crash risk, regardless of age. And earlier research by Babulal and colleagues showed that older adults with depression were three times more likely to receive a marginal or failing score on a standardized road test.

To further study the issue, Babulal and colleagues examined the impact of MDD on naturalistic driving behaviors among older adults using longitudinal data.

Participants were recruited from the Driving Real-World In-Vehicle Evaluation System Project, where their daily driving behaviors were recorded using commercial vehicle data loggers installed in their personal vehicles.

The cohort included 85 adults with MDD (mean age, 69 years; 71% women) and 310 adults without MDD (mean age, 70 years; 49% women). The majority of participants in both groups were non-Hispanic White individuals.

Based on intercepts, adults with MDD had a propensity toward riskier driving habits with a higher frequency of speeding events and spending more time on the road than those without MDD, they found.

During a mean of 1.1 years of follow-up, compared with older adults without MDD, those with MDD exhibited significantly more hard braking (P < .001) and hard cornering events per trip (P = .04) over time. They also traveled farther from home and visited more unique destinations (P < .001 for both).

Over time, older adults also displayed increased entropy in driving patterns (P < .001), indicated less predictable driving routes.

“Driving unpredictability, as evidenced by increased random entropy, highlights the unique challenges posed by MDD in maintaining safe driving practices,” the researchers wrote.

Adjustment for antidepressant use, which could impair driving, or total medication burden did not change the findings, suggesting MDD independently affects driving.

“Most importantly, our findings demonstrate that MDD — a common and treatable illness in older adults — was associated with an increase in both the amount and magnitude of risky driving behaviors over time,” the researchers wrote.

The researchers noted that the study did not account for changes in depression severity over time and other psychiatric conditions co-occurring with MDD were not adjusted for. Also, situational factors like weather or traffic conditions were not assessed.

 

Clear Clinical Implications

There is a “pressing need” for targeted interventions to manage and mitigate the driving risks associated with late-life depression, the researchers wrote.

“The study emphasizes the need for interventions tailored to the mental health and driving behaviors of older adults. These could include cognitive retraining, driver rehabilitation programs, and routine depression screening to enhance road safety and preserve independence,” Babulal said.

“Encouraging older adults with MDD to self-regulate their driving habits (eg, avoiding night driving or high-traffic situations) and educating them about potential driving challenges related to their condition can enhance safety,” he added.

Commenting on this study, Ipsit Vahia, MD, McLean Hospital, Belmont, Massachusetts, and Harvard Medical School, Boston, Massachusetts, said it “adds nuance to our understanding of how depression can impact driving among older adults.

“While the connection between depression and a higher incident of crashes is known, this study demonstrates an association with riskier driving behaviors such as speeding,” Vahia said. “It highlights the importance of clinicians proactively initiating discussion of driving and safety when working with older adults with depressive symptoms.”

This work was funded by grants from the National Institutes of Health and National Institute on Aging. Babulal had no relevant disclosures. Vahia had served as a consultant for Otsuka.

A version of this article appeared on Medscape.com.

Older adults with major depressive disorder (MDD) exhibit riskier driving behaviors, compared with their nondepressed peers, including hard braking, cornering, and unpredictable driving patterns, new research showed.

Data for the study came from commercial vehicle data trackers installed in participants’ vehicles. After about a year of follow-up, the investigators found that MDD was associated with an increase in the amount and severity of risking driving, even after they controlled for antidepressant use.

Late-life depression often goes undiagnosed, and the new findings highlight the importance of routine depression screening and targeted interventions to ensure driving safety among older adults, the study team said.

“By using longitudinal, real-world driving data rather than controlled settings or self-reports, the study provides robust evidence of how MDD influences driving behaviors in day-to-day contexts,” first author Ganesh M. Babulal, PhD, OTD, with the Department of Neurology, Washington University School of Medicine in St Louis, Missouri, said in an interview.

“By analyzing the influence of antidepressant use and overall medication load, the study disentangles the effects of MDD from those of driver-impairing medications, further clarifying the unique contributions of depression to driving behaviors,” Babulal noted.

The study was published online in JAMA Network Open.

 

Road Risks 

As the number of older adults grows, safe driving practices in this age group become increasingly crucial. By 2050, one quarter of drivers in the United States will be older than 65 years. MDD affects about 8% of US adults and is linked to cognitive impairments that may compromise driving safety.

Prior studies revealed a link between depression and increased car crash risk, regardless of age. And earlier research by Babulal and colleagues showed that older adults with depression were three times more likely to receive a marginal or failing score on a standardized road test.

To further study the issue, Babulal and colleagues examined the impact of MDD on naturalistic driving behaviors among older adults using longitudinal data.

Participants were recruited from the Driving Real-World In-Vehicle Evaluation System Project, where their daily driving behaviors were recorded using commercial vehicle data loggers installed in their personal vehicles.

The cohort included 85 adults with MDD (mean age, 69 years; 71% women) and 310 adults without MDD (mean age, 70 years; 49% women). The majority of participants in both groups were non-Hispanic White individuals.

Based on intercepts, adults with MDD had a propensity toward riskier driving habits with a higher frequency of speeding events and spending more time on the road than those without MDD, they found.

During a mean of 1.1 years of follow-up, compared with older adults without MDD, those with MDD exhibited significantly more hard braking (P < .001) and hard cornering events per trip (P = .04) over time. They also traveled farther from home and visited more unique destinations (P < .001 for both).

Over time, older adults also displayed increased entropy in driving patterns (P < .001), indicated less predictable driving routes.

“Driving unpredictability, as evidenced by increased random entropy, highlights the unique challenges posed by MDD in maintaining safe driving practices,” the researchers wrote.

Adjustment for antidepressant use, which could impair driving, or total medication burden did not change the findings, suggesting MDD independently affects driving.

“Most importantly, our findings demonstrate that MDD — a common and treatable illness in older adults — was associated with an increase in both the amount and magnitude of risky driving behaviors over time,” the researchers wrote.

The researchers noted that the study did not account for changes in depression severity over time and other psychiatric conditions co-occurring with MDD were not adjusted for. Also, situational factors like weather or traffic conditions were not assessed.

 

Clear Clinical Implications

There is a “pressing need” for targeted interventions to manage and mitigate the driving risks associated with late-life depression, the researchers wrote.

“The study emphasizes the need for interventions tailored to the mental health and driving behaviors of older adults. These could include cognitive retraining, driver rehabilitation programs, and routine depression screening to enhance road safety and preserve independence,” Babulal said.

“Encouraging older adults with MDD to self-regulate their driving habits (eg, avoiding night driving or high-traffic situations) and educating them about potential driving challenges related to their condition can enhance safety,” he added.

Commenting on this study, Ipsit Vahia, MD, McLean Hospital, Belmont, Massachusetts, and Harvard Medical School, Boston, Massachusetts, said it “adds nuance to our understanding of how depression can impact driving among older adults.

“While the connection between depression and a higher incident of crashes is known, this study demonstrates an association with riskier driving behaviors such as speeding,” Vahia said. “It highlights the importance of clinicians proactively initiating discussion of driving and safety when working with older adults with depressive symptoms.”

This work was funded by grants from the National Institutes of Health and National Institute on Aging. Babulal had no relevant disclosures. Vahia had served as a consultant for Otsuka.

A version of this article appeared on Medscape.com.

Older adults with major depressive disorder (MDD) exhibit riskier driving behaviors, compared with their nondepressed peers, including hard braking, cornering, and unpredictable driving patterns, new research showed.

Data for the study came from commercial vehicle data trackers installed in participants’ vehicles. After about a year of follow-up, the investigators found that MDD was associated with an increase in the amount and severity of risking driving, even after they controlled for antidepressant use.

Late-life depression often goes undiagnosed, and the new findings highlight the importance of routine depression screening and targeted interventions to ensure driving safety among older adults, the study team said.

“By using longitudinal, real-world driving data rather than controlled settings or self-reports, the study provides robust evidence of how MDD influences driving behaviors in day-to-day contexts,” first author Ganesh M. Babulal, PhD, OTD, with the Department of Neurology, Washington University School of Medicine in St Louis, Missouri, said in an interview.

“By analyzing the influence of antidepressant use and overall medication load, the study disentangles the effects of MDD from those of driver-impairing medications, further clarifying the unique contributions of depression to driving behaviors,” Babulal noted.

The study was published online in JAMA Network Open.

 

Road Risks 

As the number of older adults grows, safe driving practices in this age group become increasingly crucial. By 2050, one quarter of drivers in the United States will be older than 65 years. MDD affects about 8% of US adults and is linked to cognitive impairments that may compromise driving safety.

Prior studies revealed a link between depression and increased car crash risk, regardless of age. And earlier research by Babulal and colleagues showed that older adults with depression were three times more likely to receive a marginal or failing score on a standardized road test.

To further study the issue, Babulal and colleagues examined the impact of MDD on naturalistic driving behaviors among older adults using longitudinal data.

Participants were recruited from the Driving Real-World In-Vehicle Evaluation System Project, where their daily driving behaviors were recorded using commercial vehicle data loggers installed in their personal vehicles.

The cohort included 85 adults with MDD (mean age, 69 years; 71% women) and 310 adults without MDD (mean age, 70 years; 49% women). The majority of participants in both groups were non-Hispanic White individuals.

Based on intercepts, adults with MDD had a propensity toward riskier driving habits with a higher frequency of speeding events and spending more time on the road than those without MDD, they found.

During a mean of 1.1 years of follow-up, compared with older adults without MDD, those with MDD exhibited significantly more hard braking (P < .001) and hard cornering events per trip (P = .04) over time. They also traveled farther from home and visited more unique destinations (P < .001 for both).

Over time, older adults also displayed increased entropy in driving patterns (P < .001), indicated less predictable driving routes.

“Driving unpredictability, as evidenced by increased random entropy, highlights the unique challenges posed by MDD in maintaining safe driving practices,” the researchers wrote.

Adjustment for antidepressant use, which could impair driving, or total medication burden did not change the findings, suggesting MDD independently affects driving.

“Most importantly, our findings demonstrate that MDD — a common and treatable illness in older adults — was associated with an increase in both the amount and magnitude of risky driving behaviors over time,” the researchers wrote.

The researchers noted that the study did not account for changes in depression severity over time and other psychiatric conditions co-occurring with MDD were not adjusted for. Also, situational factors like weather or traffic conditions were not assessed.

 

Clear Clinical Implications

There is a “pressing need” for targeted interventions to manage and mitigate the driving risks associated with late-life depression, the researchers wrote.

“The study emphasizes the need for interventions tailored to the mental health and driving behaviors of older adults. These could include cognitive retraining, driver rehabilitation programs, and routine depression screening to enhance road safety and preserve independence,” Babulal said.

“Encouraging older adults with MDD to self-regulate their driving habits (eg, avoiding night driving or high-traffic situations) and educating them about potential driving challenges related to their condition can enhance safety,” he added.

Commenting on this study, Ipsit Vahia, MD, McLean Hospital, Belmont, Massachusetts, and Harvard Medical School, Boston, Massachusetts, said it “adds nuance to our understanding of how depression can impact driving among older adults.

“While the connection between depression and a higher incident of crashes is known, this study demonstrates an association with riskier driving behaviors such as speeding,” Vahia said. “It highlights the importance of clinicians proactively initiating discussion of driving and safety when working with older adults with depressive symptoms.”

This work was funded by grants from the National Institutes of Health and National Institute on Aging. Babulal had no relevant disclosures. Vahia had served as a consultant for Otsuka.

A version of this article appeared on Medscape.com.