Timely and Efficient AI Insights on EHR: System Design.

Journal: AMIA ... Annual Symposium proceedings. AMIA Symposium
Published Date:

Abstract

A patient's electronic health record (EHR) contains extensive documentation of the patient's medical history but is difficult for clinicians to review and find what they are looking for under the time constraints of the clinical setting. Although recent advances in artificial intelligence (AI) in healthcare have shown promise in enhancing clinical diagnosis and decision-making in clinicians' day-to-day tasks, the problem of how to implement and scale such computationally expensive analytics remains an open issue. In this work, we present a system architecture that generates AI-based insights from analysis of the entire patient medical record for a multispecialty outpatient facility of over 700,000 patients. Our resulting system is able to generate insights efficiently while handling complexities of scheduling to deliver the results in a timely manner, and handle more than 30,000 updates per day while achieving desirable operating cost-performance goals.

Authors

  • Parthasarathy Suryanarayanan
    IBM Research, Yorktown Heights, NY, USA.
  • Edward A Epstein
    IBM Research, Yorktown Heights, NY, USA.
  • Abhishek Malvankar
    IBM Research, Yorktown Heights, NY, USA.
  • Burn L Lewis
    IBM Research, Yorktown Heights, NY, USA.
  • Lou DeGenaro
    IBM Research, Yorktown Heights, NY, USA.
  • Jennifer J Liang
    IBM Research, Yorktown Heights, NY, USA.
  • Ching-Huei Tsou
    IBM Research, Yorktown Heights, NY, USA.
  • Divya Pathak
    IBM Research, Yorktown Heights, NY, USA.