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Predicting Future Hospital Utilization for Mental Health Conditions

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To develop a model using administrative variables to predict number of days in the hospital for a mental health condition in the year after discharge from a mental health hospitalization. Background, index hospitalization and preindex inpatient, emergency room, and outpatient utilization information were collected for 766 adult members discharged from a mental health hospitalization during a 1-year period. A regression model was developed to predict hospitalized days for a mental health condition in the year after discharge. A regression model was created containing five statistically significant predictors: Medicare insurance coverage, preindex mental health inpatient days, index length of stay, depression diagnosis, and number of mental health outpatient visits with a professional provider. It is possible to predict future mental health inpatient utilization at the time of discharge from a mental health hospitalization using administrative data, thus allowing disease managers to better identify members in greatest need of additional services and interventions.

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The authors would like to extend a special thanks to Abdul Jalil Khokhar, Spiru Monas, Nancy Fuentes, and Madeline Oliveras for generating data reports.

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Correspondence to Andrew Kolbasovsky PsyD.

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Kolbasovsky, A., Reich, L. & Futterman, R. Predicting Future Hospital Utilization for Mental Health Conditions. J Behav Health Serv Res 34, 34–42 (2007).

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