HIMSCast: New analytics strategies for patient-centered pop health

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

To achieve this, providers must 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 of course, turning up the right data at the right time for the right patients is easier said than done.

We recently spoke with Brian Dixon, research scientist at Indiana University’s Regenstrief Institute and interim director of Regenstrief’s Clem McDonald Center for Biomedical Informatics. He is a long-time leader in clinical data management and healthcare policy, with a long-standing focus on public health strategies.

He discussed strategies to improve patient-provider collaboration and more closely involve patients in their care plans. And he suggested ways C-suite leadership can support analytics for value-based care, and how physicians can better use 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 caregiver experience.

This episode is brought to you by Wolters Kluwer.

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Discussion points:

  • The mission of the Regenstrief Institute and Dixon’s pop health work at the Center for Biomedical Informatics

  • How patient engagement and experience align with population health management

  • Remote patient monitoring, virtual care, patient generated data and social determinants of health

  • Encourage patients to be more active participants in their own care, and involve them in shared decision-making

  • Combining EHR data with SDOH or PGDHD to better predict risks and prioritize interventions

  • How can AI help – and what providers should be careful with

More about this episode:

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AI-enabled analytics for public health and patient safety elevates HIMSS Davies Award winners
Scale SDOH initiatives with analytics and coordinated workflows
Targeted analytics helps Canadian health care groups combat homelessness and boost SDOH
HIMSSCast: Leveraging EHRs for Public Health Insights
CDC allocates $9 million for long COVID data system
Regenstrief launches initiative to disseminate SDOH data