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Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

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Predicting psychiatric emergency room recidivism.

Andrew Kolbasovsky¹, Robert Futterman

¹Health Insurance Plan of New York, New York City 10041, USA. akolbasovsky@hipusa.com

Managed Care Interface

|May 4, 2007

Summary

This study identified key predictors of psychiatric emergency room (ER) recidivism. Medicaid coverage and prior inpatient admissions for depression or substance abuse significantly increase the risk of repeat ER visits.

Area of Science:

Health Services Research
Psychiatric Epidemiology
Healthcare Management

Background:

Psychiatric emergency room (ER) recidivism poses a challenge to healthcare systems.
Continuity of care is crucial for individuals with psychiatric conditions.
Predictive models are needed to identify high-risk patients for targeted interventions.

Purpose of the Study:

To develop a predictive model for psychiatric ER visits within six months post-index visit.
To utilize administratively obtainable variables for risk prediction.
To inform case management strategies for reducing ER recidivism.

Main Methods:

A regression model was developed using data from 1,029 adult HMO members.
Data included member characteristics, preindex ER use, index ER information, and postindex utilization.

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The dataset was randomly divided into training and testing sets.

Main Results:

Medicaid insurance coverage was a significant predictor of future psychiatric ER utilization.
Preindex inpatient admissions for depression or substance abuse also predicted higher ER recidivism.
The model effectively identified members at elevated risk.

Conclusions:

Administratively identifiable variables can predict psychiatric ER recidivism.
Targeted case management interventions can be directed to high-risk individuals.
Improved identification of risk can enhance continuity of care and reduce ER burden.