DEMONSTRATING THE EFFECTIVENESS OF EVIDENCE-BASED CHRONIC DISEASE SELF-MANAGEMENT EDUCATION (CDSME) PROGRAMS IN THE UNITED STATES
Author(s)
Brian Ezeonu, PhD1, Ernest Dorilas, PhD2, Reena Sethi, DrPH3;
1Arlington, VA, USA, 2Cone Health, Greensboro, NC, USA, 3National Council on Aging, Research and Evaluation, Arlington, VA, USA
1Arlington, VA, USA, 2Cone Health, Greensboro, NC, USA, 3National Council on Aging, Research and Evaluation, Arlington, VA, USA
OBJECTIVES: Chronic diseases such as heart disease, diabetes, arthritis, and depression represent a growing public health crisis in the United States with 60-75% of older adults living with multiple chronic conditions. The demand for effective strategies to manage chronic diseases is more urgent than ever with one in five Americans projected to be aged 65 years or older by 2030. Evidence-based Chronic Disease Self-Management Education (CDSME) programs equip older adults to better manage health, reducing costs and improving quality of life. This research aims to explore the effectiveness of CDSME programs in improving self-efficacy of older adults.
METHODS: Data were drawn from the Healthy Aging Programs Integrated Database (HAPID), containing pre-post data from over 532,000 individuals enrolled in ACL-funded CDSME programs between 2010 and 2025. We employed analysis of covariance (ANCOVA) models to estimate program-related changes in self-reported self-efficacy, general health and loneliness, while adjusting for baseline characteristics and potential selection bias using a Heckman-style correction technique.
RESULTS: Baseline self-efficacy was the strongest predictor of post-program participation self-efficacy scores (0.31, p=0.000). After adjusting for baseline status, demographics, chronic disease burden, disability burden, and selection bias, CDSME program completion was associated with an 11.5 percentage-point increase in the likelihood of achieving high self-efficacy at post survey completion (p=0.000). Higher chronic disease and disability burden were associated with reduced self-efficacy, while education showed a positive effect. The inverse Mills ratio (IMR) was large and significant, indicating meaningful selection bias and supporting our use of the Heckman correction technique. Secondary models for self-reported general health and loneliness also showed similar results.
CONCLUSIONS: CDSME participation was significantly associated with improved self-efficacy among older adults, even after adjusting for baseline characteristics, health burden and selection bias. Program completion emerged as a key predictor of improvement, highlighting the importance of engagement and retention strategies for CDSME.
METHODS: Data were drawn from the Healthy Aging Programs Integrated Database (HAPID), containing pre-post data from over 532,000 individuals enrolled in ACL-funded CDSME programs between 2010 and 2025. We employed analysis of covariance (ANCOVA) models to estimate program-related changes in self-reported self-efficacy, general health and loneliness, while adjusting for baseline characteristics and potential selection bias using a Heckman-style correction technique.
RESULTS: Baseline self-efficacy was the strongest predictor of post-program participation self-efficacy scores (0.31, p=0.000). After adjusting for baseline status, demographics, chronic disease burden, disability burden, and selection bias, CDSME program completion was associated with an 11.5 percentage-point increase in the likelihood of achieving high self-efficacy at post survey completion (p=0.000). Higher chronic disease and disability burden were associated with reduced self-efficacy, while education showed a positive effect. The inverse Mills ratio (IMR) was large and significant, indicating meaningful selection bias and supporting our use of the Heckman correction technique. Secondary models for self-reported general health and loneliness also showed similar results.
CONCLUSIONS: CDSME participation was significantly associated with improved self-efficacy among older adults, even after adjusting for baseline characteristics, health burden and selection bias. Program completion emerged as a key predictor of improvement, highlighting the importance of engagement and retention strategies for CDSME.
Conference/Value in Health Info
2026-05, ISPOR 2026, Philadelphia, PA, USA
Value in Health, Volume 29, Issue S6
Code
CO122
Topic
Clinical Outcomes
Disease
SDC: Cardiovascular Disorders (including MI, Stroke, Circulatory), SDC: Diabetes/Endocrine/Metabolic Disorders (including obesity), SDC: Geriatrics, SDC: Musculoskeletal Disorders (Arthritis, Bone Disorders, Osteoporosis, Other Musculoskeletal), SDC: Respiratory-Related Disorders (Allergy, Asthma, Smoking, Other Respiratory)