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How to use predictive analytics for care management intervention

Care Management Healthcare Analytics Predictive Analytics

How do you find the most ‘actionable’ patients for care management — the ones who will most benefit from intervention?

Dr. Rich Parker first saw the value of care management as a practicing physician: it enabled him to deliver better care to some of his highest-risk patients. As an ACO leader, he experienced one of the core challenges of implementing and scaling a successful care management program: how does a health system accurately identify and target the patients who are most likely to respond to a given care management intervention?

In this talk, originally given at the NEHIMSS 2019 Spring Conference, Dr. Parker explains that care management programs can improve conditions and reduce cost and utilization. But because care management can be resource-intensive, you should carefully stratify your population to match the right patients with the right interventions.

In this presentation you’ll learn:

  • Why we need better patient stratification
  • How predictive analytics work
  • How health systems are using predictive analytics for stratification
  • How predictive analytics can be implemented to support care management