Hostname: page-component-89b8bd64d-r6c6k Total loading time: 0 Render date: 2026-05-06T12:16:32.947Z Has data issue: false hasContentIssue false

Determinants of hospital length of stay for schizophrenia: retrospective negative binomial analysis in a university hospital

Published online by Cambridge University Press:  10 March 2026

Răzvan Pop
Affiliation:
Department of Medical Informatics and Biostatistics, Faculty of Medicine, Iuliu Hațieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania
Mihaela Iancu*
Affiliation:
Department of Medical Informatics and Biostatistics, Faculty of Nursing and Health Science, Iuliu Hațieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania
Ioana Valentina Micluția
Affiliation:
Department of Neurosciences, Faculty of Medicine, Iuliu Hațieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania
Cătălina Angela Crișan
Affiliation:
Department of Neurosciences, Faculty of Medicine, Iuliu Hațieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania
Emilia Pop
Affiliation:
Department of Medical Informatics and Biostatistics, Faculty of Medicine, Iuliu Hațieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania
Sorana D. Bolboacă
Affiliation:
Department of Medical Informatics and Biostatistics, Faculty of Nursing and Health Science, Iuliu Hațieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania
*
Correspondence: Mihaela Iancu. Email: miancu@umfcluj.ro
Rights & Permissions [Opens in a new window]

Abstract

Background

Limited data exist on factors influencing the length of hospital stay (HLoS) in patients with schizophrenia.

Aims

This study aimed to identify and quantify patient characteristics associated with HLoS.

Method

A retrospective study was conducted on patients diagnosed with schizophrenia (F20, ICD-10) admitted to the County Emergency Hospital of Cluj-Napoca, Romania, from 2018 to 2022. Demographics, comorbidities, symptom severity (Positive and Negative Syndrome Scale/Brief Psychiatric Rating Scale), antipsychotic treatment and adverse effects data were collected from medical charts. Predictors of HLoS for patients with one hospitalisation were assessed using negative binomial regression.

Results

The sample comprised 288 patients aged 18–65 years, with 75% over 30 years and a balanced gender distribution. Most patients had no comorbidities (64.24%) whereas 49.46% reported addictions. Men had higher rates of tobacco use (62.00 v. 53.49%) and self-reported use of substances/drugs (15.49 v. 3.91%). Independent predictors of HLoS (P < 0.05) in the multivariable model included gender, being retired, experiencing fear or violence in the context of psychotic decompensation, percentage score reduction in symptom severity score, first-generation antipsychotics treatment and the presence of reasons for late discharge. Men had an expected HLoS 39% longer than women. Experiencing fear (adjusted incidence rate ratio (aIRR) 1.13, 95% CI [1.01; 1.27]) and violence in the context of psychotic decompensation (aIRR 1.19, 95% CI [1.06; 1.34]), and first-generation antipsychotics treatment (aIRR 1.17, 95% CI [1.02; 1.35]) were associated with longer stay, whereas being retired predicted shorter HLoS (aIRR 0.83, 95% CI [0.70; 0.98]).

Conclusions

The length of hospital stay in patients with schizophrenia is influenced by demographic, clinical and treatment factors. Targeted interventions addressing these predictors may optimise the duration of hospitalisation.

Information

Type
Paper
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - SA
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike licence (https://creativecommons.org/licenses/by-nc-sa/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the same Creative Commons licence is used to distribute the re-used or adapted article and the original article is properly cited. The written permission of Cambridge University Press or the rights holder(s) must be obtained prior to any commercial use.
Copyright
© The Author(s), 2026. Published by Cambridge University Press on behalf of Royal College of Psychiatrists
Figure 0

Table 1 Sociodemographic characteristics of the studied sample

Figure 1

Table 2 Clinical characteristics of the studied sample

Figure 2

Table 3 Incidence rate ratios and confidence intervals (95% CI) from unadjusted and adjusted negative binomial regression models

Supplementary material: File

Pop et al. supplementary material

Pop et al. supplementary material
Download Pop et al. supplementary material(File)
File 35.5 KB
Submit a response

eLetters

No eLetters have been published for this article.