Healthcare at the Intersection of Care Standards, SDoH, and Predictive Analytics

Team Innovaccer
Wed 27 Oct 2021
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Surgeons who use data and predictive modeling can help improve care quality and outcomes, and lower healthcare system costs, for one reason: they have a better understanding of what patients need, including social factors, and can marshal the appropriate resources to help them at the right time, in the right way.

Listen in as Dr. David Nace and Dr. Douglas Slakey discuss the outsized role of social determinants of health (SDoH) in influencing patient behavior, care, outcomes, and costs in healthcare. They also discuss why health systems need to share data across disciplines and care settings; and how providers can use analytics to go beyond standards—not giving up on them, but enhancing them with a broader approach—to understand and act on patient needs and resources to optimize outcomes.

Today's panel: David Nace, MD, chief medical officer at Innovaccer; and Douglas Slakey, MD, Professor and Chief Surgical Services at CMC, Program Director General Surgery Residency, Advocate Aurora Health.

They discuss:

  • How surgeons can use data and predictive modeling to anticipate patients’ needs and optimize resources in advance of surgical procedures
  • Why healthcare providers must get better at predicting which patients are most at risk, instead of working to recover from challenges
  • How social determinants of health (SDoH) can influence the many ways patients interact with healthcare systems
  • How to identify challenges patients deal with every day, and how those challenges can affect surgical outcomes
  • Why health systems must tear down data silos to give surgical teams a complete understanding of a patient’s life situation
  • How standards can be highly reliable in even the most complicated processes
  • How standards can be enhanced with predictive analytic insights derived from on unified patient data

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Tags: Podcasts
Team Innovaccer
Healthcare at the Intersection of Care Standards, SDoH, and Predictive Analytics

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