Applying patient-level metrics in population management program

Joel HoffmanThe trend of providers taking on care coordination functions that have typically been the domain of payers is an encouraging one. Care coordination is a natural role for provider organizations, who can further their role as change agents for the many patients who need to get engaged in their own health.

Care coordination relies on data and analytics to identify, stratify and measure high-risk patients with chronic diseases. However, value-based providers may not know how to tap into the full value of metrics coming out of population data, especially if those metrics are based on a reference population and/or are historical in nature.

These data can produce highly actionable information that can enable changes in care delivery at a one-to-one level as well as a health care system level. In this post, I’ll focus on individual metrics.

Patient-level metrics, or individual metrics, can help providers identify specific patients who need care management services or other focused support to help them manage their health. Some health care providers may be familiar with these types of metrics, since they are used in clinical decision support systems.

Metrics such as these, which are specific to a patient and to a particular time period, can help providers understand the best way to deliver to that patient the right services, at the right time and in the right manner.

Patient-level metrics will improve the care of individual patients, and as such are critical to support population health initiatives. But they are just the tip of the iceberg in relation to the rest of their patients. Value-based provider organizations must undertake to optimize the delivery and financing of health care not just for those patients who present at their clinics or hospitals, but also for their entire population.

In my next post, I’ll discuss some of the basics of population metrics, and how patient and population metrics contribute together to the overall health of patient populations. For more on patient and population analytics, read the Optum® featured topic: A balanced approach to population health management.

About the author

Joel Hoffman is senior vice president and chief analytics officer of Optum.  In this role, he is responsible for the analysis and interpretation of data in support of Optum’s overall market activities and growth, working with strategic clients on innovative opportunities and advancing high-value external priorities, including those with select international and acquisition partners.  Joel most recently maintained responsibility for Payer Consulting, an OptumInsight Payer Solution’s business comprised of over 800 professionals focused on facilitating favorable performance and profitable growth for clients while reducing organizational exposure.  He graduated Summa Cum Laude from Temple University with a BA in Mathematics.  Prior to joining OptumInsight, Joel was a partner at Ernst & Young.

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