MACHINE LEARNING & AI: A HIMSS EVENT

LAS VEGAS, NV - MARCH 5, 2018

HIMSS18 Annual Conference
Wynn Las Vegas
Mar. 5, 2018

Srinivasan Suresh

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

Dr. Suresh is a Visiting Professor of Pediatrics at the University of Pittsburgh School of Medicine. Board certified in pediatric emergency medicine and in clinical informatics, he has 20 years of experience as a pediatric emergency physician, and 7 years as an IT executive.
He has had senior leadership roles in two large children's hospitals in the areas of clinical care, information science, medical education, business development and corporate strategy. As an IT physician champion, he is passionate in the application of business intelligence tools and advanced data analytics in improving child health, and patient and provider satisfaction. He has presented on these topics at national and international conferences, and authored papers on big data and predictive analytics. He is also focused on creating more robust clinical decision support tools in the electronic health record.
In 2015, he was invited to give a TEDx talk on 'Applying big data to little patients'. He was instrumental in Children's Hospital of Pittsburgh of UPMC winning the HIMSS Davies award (2015), and in maintaining Stage 7 EMRAM designation (2016). In 2017, he was named by Becker's Hospital Review as one of '50 hospital and health system CMIOs to know'.
Dr. Suresh received his medical degree from the University of Madras, India. He completed his pediatric residency and pediatric emergency medicine fellowship training at Children's Hospital of Michigan, Detroit, and earned an MBA from the University of Michigan, Ann Arbor.
 

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.
March 5, 2018
12:40pm - 1:00pm
Lafleur

One of the best ways learn is to network with your peers. This session will provide an opportunity to meet speakers and attendees who have similar privacy and security challenges and discuss solutions to those challenges.

Here's how it works:

Speakers will be stationed at different tables in the ballroom, and attendees can circulate and speak one-on-one or in groups with individual speakers. The speakers have been assigned different topics, but other topics can also be addressed.

Mingle, share and learn in this interactive environment.

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