PICTURE: Adult General Floor Deterioration Prediction


Overview

PICTURE is a suite of machine learning algorithms that utilizes electronic health record (EHR) data to predict patient deterioration in hospital settings. This iteration is modeled specifically for adult inpatients on a general floor.

Unique Features:

  • Provides an explanation of the main factors contributing to its prediction in each instance

  • Uses data that is collected during routine medical care such as common lab values

  • Will not disrupt clinician workflows or practices, even if policy changes alter routine tests

  • Defined thresholds allow each hospital unit to specify their desired precision

  • Designed to model patient’s physiology as opposed to clinician behavior, ensuring the alarms provide novel information to care providers

Value Proposition to Michigan Medicine

Early detection of patient deterioration has been found to lead to reduced mortality risk, reduced length-of-stay and decreased hospital costs, yet identifying patient deterioration is a challenge for clinicians. PICTURE is a suite of machine learning algorithms utilizing electronic health record (EHR) data to passively and accurately predict ICU transfer or death as a proxy for patient deterioration. PICTURE also provides explanations for every single prediction, adding transparency to the model and how it calculated its output. This transparency is invaluable to clinicians who can use these explanations to guide decisions around patient care.

Principal Investigator(s)

Sardar Ansari, PhD
Kevin Ward, MD

Clinical Champion

Stephanie Taylor, MD, M.Sc

Digital Health Innovation Support

Digital Health Innovation providing hosting support and provided the mechanism for streaming real time data into the model for prospective validation.

Partnerships

Health Information Technology and Services  (HITS) 

Intellectual Property

Invention Disclosure # 2019-094, 2021-244, 2021-245, 2021-250, 2021-251

Patent Issued: #11587977