MACHINE LEARNING & AI: A HIMSS EVENT

LAS VEGAS, NV - MARCH 5, 2018

HIMSS18 Annual Conference
Wynn Las Vegas
Mar. 5, 2018

CASE STUDY 3: Predicting Hospital Readmissions at Point-of-Care

March 5, 2018
11:50am - 12:10pm
Lafleur

Excess unplanned hospital readmissions are a quality of care indicator, and pose a financial burden to hospitals.

In this session, attendees will learn how Children’s Hospital of Pittsburgh at UPMC developed an innovative real-time tool that calculates every inpatient's unique readmission risk, at point-of-discharge, from structured and unstructured elements in the EHR.  The hospital integrated this predictor into its EHR, and when run in silent mode (Jan-March '17), it accurately predicted 80% of discharges with a high-risk of readmission.

The hospital now has an intervention plan (based on nurse calls, home health visits) that has already shown a reduction in preventable readmissions.

Key discussion points:

  • The value (financial ROI, improved quality metrics) of machine learning and AI based technologies for improving specific patient care outcomes.
  • The importance of scientific rigor in developing such applications.
  • The critical nature of collaborative work (MDs, RNs, IT experts, biomedical scientists) in the build and implementation.

Speakers

Srinivasan Suresh

Chief Medical Information Officer
Children's Hospital of Pittsburgh of UPMC

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