HIMSSCast: New analytics strategies for patient-centric pop health

As health systems prioritize population health management, disparate factors such as patient engagement, social determinants of health and AI-enabled decision support all have roles to play, says Brian Dixon, research scientist at Regenstrief Institute.

By Mike Miliard

April 19, 2024

01:57 PM

Photo: Tetra Images/Getty Images

The shift toward value-based reimbursement demands that hospitals and health systems take a more thoughtful approach to population health management. That requires the development of robust analytics strategies to track care quality and help patients manage their chronic conditions.

To achieve this, provider organizations should embrace an enterprise-wide approach that focuses on integrating key data into clinical workflows to identify high-risk patients – and, crucially, provide proactive interventions. But surfacing the right data at the right time for the right patients is easier said than done, of course.

We spoke recently with Brian Dixon, research scientist at Indiana University's Regenstrief Institute and interim director of Regenstrief's Clem McDonald Center for Biomedical Informatics. He's a longtime leader in clinical data management and healthcare policy, and has been focused on population health strategies for many years.

He discussed strategies for improving the patient-provider collaboration and more closely involving patients in their care plans. And he suggested ways C-suite leadership can support analytics for value-based care, and how clinicians can make better use of information – EHR and claims, patient generated health data, social determinants – to inform their decision-making.

We also explored technology-enabled patient engagement strategies, how AI and automation can streamline clinical workflows and improve decision support – and how to prioritize the patient and provider experience.

This episode is brought to you by Wolters Kluwer.

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Talking points:

Regenstrief Institute's mission, and Dixon's pop health work at the Center for Biomedical Informatics.
How patient engagement and experience dovetail with population health management.
Remote patient monitoring, virtual care, patient generated data and social determinants of health.
Encouraging patients to be more active participants in their own care, and involving them in shared decision-making.
Combining EHR data with SDOH or PGDHD to better predict risk and prioritize interventions.
How can AI help – and where providers should tread carefully.