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09.11.2017 | Original Paper

Predicting psychiatric readmission: sex-specific models to predict 30-day readmission following acute psychiatric hospitalization

verfasst von: Lucy Church Barker, Andrea Gruneir, Kinwah Fung, Nathan Herrmann, Paul Kurdyak, Elizabeth Lin, Paula A. Rochon, Dallas Seitz, Valerie H. Taylor, Simone N. Vigod

Erschienen in: Social Psychiatry and Psychiatric Epidemiology | Ausgabe 2/2018

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Abstract

Purpose

Psychiatric readmission is a common negative outcome. Predictors of readmission may differ by sex. This study aimed to derive and internally validate sex-specific models to predict 30-day psychiatric readmission.

Methods

We used population-level health administrative data to identify predictors of 30-day psychiatric readmission among women (n = 33,353) and men (n = 32,436) discharged from all psychiatric units in Ontario, Canada (2008–2011). Predictor variables included sociodemographics, health service utilization, and clinical characteristics. Using derivation data sets, multivariable logistic regression models were fit to determine optimal predictive models for each sex separately. Results were presented as adjusted odds ratios (aORs) and 95% confidence intervals (CI). The multivariable models were then applied in the internal validation data sets.

Results

The 30-day readmission rates were 9.3% (women) and 9.1% (men). Many predictors were consistent between women and men. For women only, personality disorder (aOR 1.21, 95% CI 1.03–1.42) and positive symptom score (aOR 1.41, 95% CI 1.09–1.82 for score of 1 vs. 0; aOR 1.44, 95% CI 1.26–1.64 for ≥ 2 vs. 0) increased odds of readmission. For men only, self-care problems at admission (aOR 1.20, 95% CI 1.06–1.36) and discharge (aOR 1.44, 95% CI 1.26–1.64 for score of 1 vs. 0; aOR 1.79, 95% CI 1.17–2.74 for 2 vs. 0), and mild anxiety rating (score of 1 vs. 0: aOR 1.30, 95% CI 1.02–1.64, derivation model only) increased odds of readmission. Models had moderate discriminative ability in derivation and internal validation samples for both sexes (c-statistics 0.64–0.65).

Conclusions

Certain key predictors of psychiatric readmission differ by sex. This knowledge may help to reduce psychiatric hospital readmission rates by focusing interventions.
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Metadaten
Titel
Predicting psychiatric readmission: sex-specific models to predict 30-day readmission following acute psychiatric hospitalization
verfasst von
Lucy Church Barker
Andrea Gruneir
Kinwah Fung
Nathan Herrmann
Paul Kurdyak
Elizabeth Lin
Paula A. Rochon
Dallas Seitz
Valerie H. Taylor
Simone N. Vigod
Publikationsdatum
09.11.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
Social Psychiatry and Psychiatric Epidemiology / Ausgabe 2/2018
Print ISSN: 0933-7954
Elektronische ISSN: 1433-9285
DOI
https://doi.org/10.1007/s00127-017-1450-5

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