Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Jul 17;25(1):711.
doi: 10.1186/s12888-025-07149-9.

Crisis versus extended care: bimodal distribution of length of stay in psychiatric inpatients

Affiliations

Crisis versus extended care: bimodal distribution of length of stay in psychiatric inpatients

Andreas B Hofmann et al. BMC Psychiatry. .

Abstract

Background: The length of stay (LoS) in psychiatric facilities is a critical metric for healthcare planning and resource allocation. While previous research has established that LoS distributions are typically right-skewed across medical specialties, detailed characterizations of these distributions within psychiatric settings remain limited, particularly regarding variations across diagnostic categories.

Methods: We conducted a retrospective cross-sectional analysis of 17,687 psychiatric hospitalizations at the University Hospital of Psychiatry Zurich between 2013 and 2020. Using both linear and logarithmic visualizations, we examined LoS distribution patterns across diagnostic groups based on ICD-10 classifications.

Results: Following identified distribution patterns, patients could be categorized into short-stay (1-10 days) and long-stay (11-200 days) groups for comparative analysis. LoS distribution demonstrated a bimodal pattern when visualized on a logarithmic scale, with distinct peaks representing short-term crisis interventions and longer therapeutic hospitalizations. This bimodal distribution was particularly evident in anxiety and stress-related disorders and major depressive disorder. Diagnostic categories differed significantly in their LoS-distribution patterns, with schizophrenia spectrum disorders, organic mental disorders, and bipolar disorders more frequently requiring extended hospitalizations. Long-stay patients exhibited higher admission HoNOS scores (median 20 vs. 18) and were significantly older (median 49 vs. 39 years) than short-stay patients.

Conclusions: Our findings reveal that psychiatric hospitalization durations follow a bimodal rather than simply right-skewed distribution, suggesting two distinct patient populations requiring fundamentally different treatment approaches. This pattern varies systematically across diagnostic categories but transcends diagnostic boundaries, indicating that factors beyond primary diagnosis influence treatment duration. These results support the development of differentiated care structures addressing both acute crisis intervention and extended therapeutic needs within psychiatric care systems.

Keywords: Bimodal; Distribution; Hospitalization; Inpatient; Length of stay; Psychiatric hospital.

PubMed Disclaimer

Conflict of interest statement

Declarations. Ethics approval and consent to participate: The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the Canton of Zurich. Patient consent was waived due to approval by the Ethics Committee of the Canton of Zurich. (BASEC reference number: 2018 − 01906). Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Density distribution depicting duration of treatment in (a) continuous and (b) logarithmic scale for all diagnoses combined
Fig. 2
Fig. 2
Density distribution depicting duration of treatment in (a) continuous and (b) logarithmic scale for each diagnostic subgroup separately (please refer to Table1 for definitions)
Fig. 3
Fig. 3
Density distribution depicting duration of treatment on a logarithmic scale for each diagnostic subgroup separately stratified by admission status (please refer to Table 1 for definitions)

Similar articles

References

    1. Malone D, Fineberg NA, Gale TM. What is the usual length of stay in a psychiatric ward? Int J Psychiatry Clin Pract. 2004;8:53–6. - PubMed
    1. Doctoroff L, Herzig SJ. Predicting patients at risk for prolonged hospital stays. Med Care. 2020;58:778–84. - PMC - PubMed
    1. Williford E, Haley V, McNutt L-A, Lazariu V. Dealing with highly skewed hospital length of stay distributions: the use of gamma mixture models to study delivery hospitalizations. PLoS ONE. 2020;15:e0231825. - PMC - PubMed
    1. Dehouche N, Viravan S, Santawat U, Torsuwan N, Taijan S, Intharakosum A, et al. Hospital length of stay: A cross-specialty analysis and Beta-geometric model. PLoS ONE. 2023;18:e0288239. - PMC - PubMed
    1. Faddy M, Graves N, Pettitt A. Modeling length of stay in hospital and other right skewed data: comparison of phase-type, gamma and log-normal distributions. Value Health. 2009;12:309–14. - PubMed

LinkOut - more resources