Long-Term Impact of an Electronic Health Record-Enabled, Team-Based, and Scalable Population Health Strategy Based on the Chronic Care Model.

Abstract

The Chronic Care Model (CCM) is a promising framework for improving population health, but little is known regarding the long-term impact of scalable, informatics-enabled interventions based on this model. To address this challenge, this study evaluated the long-term impact of implementing a scalable, electronic health record (EHR)- enabled, and CCM-based population health program to replace a labor-intensive legacy program in 18 primary care practices. Interventions included point-of-care decision support, quality reporting, team-based care, patient engagement, and provider education. Among 6,768 patients with diabetes receiving care over 4 years, hemoglobin A1c levels remained stable during the 2-year pre-intervention and post-intervention periods (0.03% and 0% increases, respectively), compared to a 0.42% increase expected based on A1c progression observed in the United Kingdom Prospective Diabetes Study long-term outcomes cohort. The results indicate that an EHR-enabled, team- based, and scalable population health strategy based on the CCM may be effective and efficient for managing population health.

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Scholars@Duke

Anstrom

Kevin J. Anstrom

Adjunct Professor in the Department of Biostatistics & Bioinformatics

My research interests include clinical trial design, causal inference, coordinating centers, data monitoring, and pragmatic clinical research.

Anderson

John B. Anderson

Associate Professor of Family Medicine and Community Health
Bosworth

Hayden Barry Bosworth

Professor in Population Health Sciences

Dr. Bosworth is a health services researcher and Deputy Director of the Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT)  at the Durham VA Medical Center. He is also Vice Chair of Education and Professor of Population Health Sciences. He is also a Professor of Medicine, Psychiatry, and Nursing at Duke University Medical Center and Adjunct Professor in Health Policy and Administration at the School of Public Health at the University of North Carolina at Chapel Hill. His research interests comprise three overarching areas of research: 1) clinical research that provides knowledge for improving patients’ treatment adherence and self-management in chronic care; 2) translation research to improve access to quality of care; and 3) eliminate health care disparities. 

Dr. Bosworth is the recipient of an American Heart Association established investigator award, the 2013 VA Undersecretary Award for Outstanding Achievement in Health Services Research (The annual award is the highest honor for VA health services researchers), and a VA Senior Career Scientist Award. In terms of self-management, Dr. Bosworth has expertise developing interventions to improve health behaviors related to hypertension, coronary artery disease, and depression, and has been developing and implementing tailored patient interventions to reduce the burden of other chronic diseases. These trials focus on motivating individuals to initiate health behaviors and sustaining them long term and use members of the healthcare team, particularly pharmacists and nurses. He has been the Principal Investigator of over 30 trials resulting in over 400 peer reviewed publications and four books. This work has been or is being implemented in multiple arenas including Medicaid of North Carolina, private payers, The United Kingdom National Health System Direct, Kaiser Health care system, and the Veterans Affairs.

Areas of Expertise: Health Behavior, Health Services Research, Implementation Science, Health Measurement, and Health Policy

Lobach

David Franklin Lobach

Associate Consulting Professor in the Department of Family Medicine and Community Health

Development and evaluation of clinical decision support systems
Development and implementation of cliical practice guidelines
Computer-based Patient Record Systems
Human-computer interface design
Curriculum development for training in Medical Informatics


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