Encompass Health predictive intelligence models help improve care coordination

Unplanned acute-care transfers and falls in inpatient rehabilitation hospitals can affect patient outcomes and be costly to the post-acute care organization. Encompass Health, the nation’s largest system of rehabilitation hospitals, has collaborated with Cerner to develop predictive models to identify patients at risk for an unplanned acute-care transfers, as well as falls risks, by leveraging original research, machine learning and statistical analysis. The goal is early identification of risk with early interventional strategies so the patient can complete the rehab experience successfully and return home as soon as possible. The acute-care transfer functionality will soon be available to Cerner clients.

  • Session Type:Client HIT talk
  • Learning objective 1:Describe how Encompass Health uses the acute-care transfer algorithm to identify patients at risk of an unplanned acute-care transfer.
  • Learning objective 2:Identify how Encompass uses the system to give clinicians early warnings so they can provide timely interventions to reduce the likelihood of negative outcomes.
  • Learning objective 3:Define how technology is helping inpatient rehabilitation organizations.
  • Content topics:Care Continuum
  • Solutions:Rehabilitation
  • Target audience:Analytics, Care Management, Population Health Management
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