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Using machine learning to selectively highlight patient information.

Andrew J King¹, Gregory F Cooper², Gilles Clermont³

¹Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA; Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA.

Journal of Biomedical Informatics

|November 3, 2019

Summary

This summary is machine-generated.

A new Learning Electronic Medical Record (EMR) system uses machine learning to predict and display relevant patient data, reducing clinician cognitive load. This adaptive approach shows promise for improving information access in critical care settings.

Keywords:

Critical care Electronic medical records Information-seeking behavior Machine learning

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Area of Science:

Clinical Informatics
Machine Learning in Healthcare
Decision Support Systems

Background:

Electronic Medical Record (EMR) systems often contribute to cognitive overload for clinicians.
There is a need for EMR functionality that intelligently guides clinicians to critical data.
The Learning EMR (LEMR) system was developed to address these challenges.

Purpose of the Study:

To develop and evaluate a system that learns clinician information-seeking behavior.
To apply machine learning models to predict and display relevant patient data.
To reduce cognitive burden on clinicians in intensive care unit (ICU) settings.

Main Methods:

Critical care physicians identified relevant data for patient cases.
Machine learning models were trained using EMR data to predict data relevancy.
The predictive performance of high-performing models was prospectively evaluated.

Main Results:

25 models achieved a precision of 0.52 and recall of 0.77 in identifying relevant data.
For data missed by the system, 82% of cases had no or minor impact on patient care.
The system demonstrated effectiveness in highlighting crucial patient information.

Conclusions:

Data-driven, adaptive display of information in EMRs holds significant promise.
Learning from clinician information-seeking behavior can effectively identify and surface relevant data.
The LEMR system represents a step towards more intelligent and efficient EMRs.