Identifying high-cost patients in psychiatry: Optimal cut-off values for previous admissions and length of stay

Sou Bouy Loew1, Julian Moeller1, Roselind Lieb2

  • 1University Psychiatric Clinics (UPK), University of Basel, Basel, Switzerland; Division of Clinical Psychology and Epidemiology, Department of Psychology, University of Basel, Basel, Switzerland.

PubMed

Insights

Identifying high-cost patients (HCP) in psychiatry is crucial for effective care. This study suggests using inpatient treatment days as a predictor, but further factors are needed for precise identification of these patients.

Area of Science:

  • Psychiatry
  • Health Economics
  • Healthcare Management

Background:

  • High-cost patients (HCP) in psychiatry consume disproportionately high healthcare resources.
  • Accurate identification of HCP is essential for targeted interventions and resource allocation.
  • This study aimed to establish evidence-based definitions for identifying HCP in psychiatric care.

Purpose of the Study:

  • To define evidence-based criteria for identifying high-cost patients (HCP) in psychiatric care.
  • To evaluate the predictive accuracy of previous healthcare utilization for identifying HCP.
  • To determine optimal cut-off points for previous admissions and length of stay to define HCP.

Main Methods:

  • Utilized receiver-operator characteristic (ROC) curve analyses on 898 inpatients from a Swiss psychiatric university hospital.
  • Analyzed a 12-month post-index hospitalization period to define HCP based on the 90th cost percentile.
  • Examined retrospective data from 18- and 30-month periods preceding index hospitalization for admissions and length of stay.

Main Results:

  • Previous treatment utilization significantly predicted HCP status (AUC 0.70-0.74).
  • Models using cumulative inpatient treatment days showed higher positive predictive values (51.7%-53.9%) compared to admission counts.
  • Proposed cut-offs: >45.5 inpatient days (18 months prior) or >46.5 days (30 months prior) for HCP identification, though only identifying slightly over half of HCP.

Conclusions:

  • Current models based on past utilization inadequately identify all high-cost patients (HCP).
  • Additional predictors are necessary to improve the definition and identification of HCP.
  • Future research should explore and incorporate novel characteristics to enhance HCP identification strategies.
Abstract

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