Interoperability Proving Ground (IPG) submissions within the ONC Tech Lab are submitted by healthcare, technology and development organizations that are invested in Health IT and Interoperability and want to share, learn and collaborate with similar stakeholders in the US, and around the world.

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Hardwiring Transitions of Care: Leverage AI to Predict COVIC19 Patient Outcomes

"Failed hand-offs are a longstanding, common problem in health care” (The Joint Commission, Sentinel Event Alert, Issue 58, September 2017) and arise primarily due to communication failures between healthcare workers.  Given that healthcare workers at the front lines of COVID19 are bearing disproportionate burden - higher proportion of nurses and physicians are experiencing symptoms of depression, anxiety, insomnia, and distress (, the chances of patient handoff failures are higher during this pandemic.

We are working with hospitals to hard wire patient handoffs, transfers, rounding between nurses and doctors. Our software solution, Caringly, integrates with hospital EMR - ingests patient clinical data as HL7 messages, transforms them into FHIR and runs our proprietary Rules Engine to prioritize data for information exchange between the handoff sender and the handoff receiver. Caringly hardwires the patient handoff process making it resilient to potential points of failure arising from mental health status of the sender and receiver or distractions. Our Rues Engine algorithms employ AI based tools to anticipate outcomes and safety events in COVID19 patients before they occur and alert nurses and physicians.
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Project Tags
  • Analytics
  • API
  • Artificial Intelligence
  • EHR
  • EHR Integration
  • FHIR
  • HAPI
  • HL7
  • Interoperability
  • Machine Learning
  • Patient Discharge
  • Patient Handoff
  • Patient Handover
  • Patient Report
  • Patient Rounding
  • Patient Transfer
  • Rounding
  • Transitions of Care
  • Caringly
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Project Results