Electronic Health Data Quality and Population Health Management Algorithms
Published in: Population Health Management (2021). doi: 10.1089/pop.2021.0170
Posted on RAND.org on August 27, 2021
U.S. health care payment policy is shifting from fee for-service to more capitated or value-based payments. At the same time, technology is increasingly becoming a part of health care delivery. As a result, health care providers, health care systems, and health plans are relying more and more on population health management algorithms to identify potentially high-cost, high-utilization patients and target these patients in efforts to improve outcomes or reduce health care costs. Algorithms use a variety of data sources, including medical claims data, electronic health records (EHRs), and individual or neighborhood-level social determinants of health data to identify patients at high risk for hospitalization or death. Once the algorithm identifies a cohort of patients at greater risk for hospitalization or death, the provider or other stakeholders can act, including increasing outreach to these patients, involving care coordinators, or encouraging patients to participate in disease management programs.
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