ArticleBMC psychiatry2015
Predictors of length of stay in psychiatry: analyses of electronic medical records.
Article in BMC psychiatry, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed, 72 citations in OpenAlex.
- Crisis versus extended care: bimodal distribution of length of stay in psychiatric inpatients.BMC psychiatry · 2025Article
- Influencing factors of the implementation of mechanical restraint in open psychiatric ward: a retrospective study (2016-2021).BMC psychiatry · 2025Article
- Metabolic syndrome and its components are associated with lengths of stay in a psychiatric hospital: Results from a Swiss psychiatric cohort and first-episode psychosis patients.European psychiatry : the journal of the Association of European Psychiatrists · 2025Article
- Factors Associated With Length of Hospital Stay for Forensic Psychiatric Inpatients With Intellectual Disabilities.Journal of applied research in intellectual disabilities : JARID · 2025Article
- Determinants of acute psychiatric inpatient length of stay in Ireland.Irish journal of medical science · 2025Article
- Development and validation of a novel risk classification tool for predicting long length of stay in NICU blood transfusion infants.Scientific reports · 2024Article
- Predictors of the length of stay in psychiatric inpatient units: a retrospective study for the Paris Psychiatry Hospital Group.Frontiers in psychiatry · 2024Article
- Article
- Machine learning-based prediction of hospital prolonged length of stay admission at emergency department: a Gradient Boosting algorithm analysis.Frontiers in artificial intelligence · 2023Article
- Predictors of Length of Hospitalization and Impact on Early Readmission for Mental Disorders.International journal of environmental research and public health · 2022Article
- Article
- Hospital Admission Rate, Cumulative Hospitalized Days, and Time to Admission Among Older Persons With Substance Use and Psychiatric Conditions.Frontiers in psychiatry · 2022Article
- [Predicting prolonged length of intensive care unit stayBeijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · 2021Article
- The prediction of hospital length of stay using unstructured data.BMC medical informatics and decision making · 2021Observational
- The Impact of Demographic, Clinical, and Institutional Factors on Psychiatric Inpatient Length-of-Stay.Administration and policy in mental health · 2021Article
- Predicting Prolonged Length of Hospital Stay for Peritoneal Dialysis-Treated Patients Using Stacked Generalization: Model Development and Validation Study.JMIR medical informatics · 2021Article
- Review
- Violent Behavior Prior to Admission Is Not a Factor in Further Prolonged Length of Stay: A Retrospective Cohort Study in a Japanese Psychiatric Hospital.Frontiers in psychiatry · 2021Article
- A polyepigenetic glucocorticoid exposure score at birth and childhood mental and behavioral disorders.Neurobiology of stress · 2020Article
- Use of psychiatric hospitals and social integration of patients with psychiatric disorders: a prospective cohort study in five European countries.Social psychiatry and psychiatric epidemiology · 2020Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLength of stay is a straightforward measure of hospital costs and retrospective data are widely available. However, a prospective idea of a patient's length of stay would be required to predetermine hospital reimbursement per case based on patient classifications. The aim of this study was to analyse the predictive power of patient characteristics in terms of length of stay in a psychiatric hospital setting. A further aim was to use patient characteristics to predict episodes with extreme length of stay.
methodsThe study included all inpatient episodes admitted in 2013 to a psychiatric hospital. Zero-truncated negative binomial regression was carried out to predict length of stay. Penalized maximum likelihood logistic regressions were carried out to predict episodes experiencing extreme length of stay. Independent variables were chosen on the basis of prior research and model fit was cross-validated.
resultsA total of 738 inpatient episodes were included. Seven patient characteristics showed significant effects on length of stay. The strongest increasing effects were found in the presence of affective disorders as main diagnosis, followed by severity of disease and chronicity of disease. The strongest decreasing effects were found in danger to others, followed by the presence of substance-related disorders as main diagnosis, the daily requirement of somatic care and male gender. The squared correlation between out-of-sample predictions and observed values was 0.14. The root-mean-square-error was 40 days.
conclusionProspectively defining reimbursement per case might not be feasible in mental health because length of stay cannot be predicted by patient characteristics. Per diem systems should be used.
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