The first time Kaiser Permanente Northwest launched an analytic tool to predict hospital readmission risk, the initiative flopped. The integrated health system wanted a tool that would identify high-risk patients before they were discharged so clinicians could arrange needed follow-up care to prevent complications.

“We had been using a subjective assessment or the physician’s gestalt on whether they thought the patient was at low, medium or high risk for readmitting,” said Delilah Moore, PhD, pharmacy analytics manager. “We were looking for a more objective measure.”

Register or login for access to this item and much more

All Information Management content is archived after seven days.

Community members receive:
  • All recent and archived articles
  • Conference offers and updates
  • A full menu of enewsletter options
  • Web seminars, white papers, ebooks

Don't have an account? Register for Free Unlimited Access