As population health management matures, both health providers and payers are moving beyond traditional clinical, risk-based analytics to focus on patient behavior. They are mining both traditional and emerging sources of data to gain visibility into patient behavior with the goal of influencing behavior to improve patient engagement and drive better patient clinical outcomes, efficiency, and satisfaction.
Traditional population health management programs focus on understanding and assessing clinical risk, such as disease prevalence, severity, and progression. This enables organizations to pinpoint opportunities for clinical improvement such as gaps in care, clinical quality, and healthcare outcomes.
Designed to empower clinicians to improve care and to promote evidence-based medicine, these traditional population health management analytics are created to facilitate clinical actions. They provide little to no insight into the challenges patients experience with positive clinical outcomes and satisfaction. This is unfortunate, since most problems in healthcare have significant patient engagement components.
Engagement analytics is a new behavior-focused approach to population health management that integrates conventional clinical risk-based analytics with a new breed of analytics and data sources that focus on behavioral risk, behavior change and patient engagement…