The Interoperability Proving Ground has been archived and is no longer actively maintained. All information identified as archived is provided for reference, research or recordkeeping purposes.

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.

To view all submissions, please view the IPG link located within the ONC Techlab.

Qventus Patient Flow Automation Platform

Description 
Qventus automates patient flow for leading hospitals and health systems. Integrating with EHRs, Qventus combines AI, behavioral science, and data science to predict operational issues before they occur, orchestrate actions among frontline teams and ancillaries, and manage accountability to drive continuous improvement.

Qventus is currently partnering with health systems to help them address the challenges of COVID-19 and its subsequent impact by predicting COVID-19 admits, mitigating critical resource shortages, and driving continued focus on discharge optimization to prepare for future surges.
Start Date 
03/01/2011
Projected End Date 

    

  





  

    Project Tags
    
  • Artificial Intelligence
  • Behavioral Science
  • COVID-19
  • Data Science
  • Discharge
  • EHR
  • HL7
  • interoperability
  • Machine Learning
  • Operations Management
  • Patient Flow

  

  

    Project Point of Contact:
    tchenremove@removeqventus.com  






  

    Project Results
    
With Qventus, organizations such as Emory, Mercy, and NewYork-Presbyterian are transforming operations, reducing inpatient LOS by 0.3 to 0.8 day, eliminating thousands of excess days, decreasing ED LWBS by 50%, and more.