Sutter Health: Leveraging predictive analytics to lower 30-day readmit rates

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Sutter Health: Leveraging predictive analytics to lower 30-day readmit rates

Sutter Health is a not-for-profit health system serving more than 100 communities in Northern California. Each year its 5,000 physicians care for more than 10 million outpatient visits and discharge more than 200,000 in-patients.
As healthcare systems transition from “fee for service” to “fee for value” reimbursement models, there is an increasing focus to drive down 30-day re-admission rates, particularly for high risk patients. To this end, Sutter Health is piloting Project RED (Re-engineered Discharge) which leverages predictive analytics to identify high-risk patients and then prescribes alternative discharge workflows aimed at lowering the risk of re-admission.
Join us as Kristen Wilson-Jones, Sutter RD&D CTO, shares how Sutter Health has leveraged MuleSoft’s Anypoint Platform in an orchestrated plecosystem of technologies to power Project RED by enabling real-time patient risk scoring, clinical workflow management and bi-directional integration with Epic.

  • How Sutter Health is lowering 30-day re-admission rates by re-engineeing clinical workflows
  • The need for connectivity to enable workflow re-design
  • Best practice in moving from an application-centric to a data object-centric connectivity approach
Presented by:
Kristen Wilson-Jones, RD&D CTO, Sutter Health
David Chao, Director of Industry Solutions, MuleSoft​