The Evolution of Data, Social Determinants, and AI in Population Health Management

Population Health Management is the new foundation in the successful shift to value-based care and is evolving beyond risk management. It’s currently focused on understanding who the most vulnerable of our patients are, but true Population Health Management necessitates a more thorough collection of patient data across all spectrums and an in-depth analysis of that data to provide actionable insight that would improve patient outcomes and eventually reduce costs. Providers and payers must collaborate to accomplish successful population management and begin to usher in value-based care, as they hold the almighty data that is key to population health.

While claims data has historically been the primary source for evaluating the health of the covered population, it’s outdated and inadequate for the purposes of Population Health Management. EMRs and EHRs are a far more relevant source of data and allow for real-time analytics. As the various sources of patient data are integrated, payers and providers must work together to document and track the social determinants of health (SDOH) that typically fall outside their members’ medical records. This would include information about the patient’s childhood, family unit, social life, household status, income, available transportation, neighborhood characteristics, work conditions, and risk factors such as homelessness, stress, unemployment, addiction, social isolation, and food instability. Once identified, these risk factors can be addressed by implementing innovative behavioral change models. Combining these three important data sources (claims, EMRs/EHRs, and SDOH) into one Comprehensive Health Record will generate a more holistic view.

Technological advances in the field of artificial intelligence and deep learning will allow organizations of the future to gain a better insight into the health, risk factors, and behaviors of their populations. The more data that payers and providers compile now, the more accurate and useful the information will be upon analysis, resulting in the identification of trends, the discovery of causes, and the development of effective risk mitigation strategies. Until then, the importance of identifying the sickest of the population and adjusting your risk management strategy is critical.

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Betsy Knorr
Chief Operating Officer
HealthCare Information Management, Inc.