Evidence map›Paper›PMID 39716097›Full record

ArticleBMC psychiatry2024

Exploring correlates of high psychiatric inpatient utilization in Switzerland: a descriptive and machine learning analysis.

Mariela E Jaffé, Stefan Weinmann, Andrea H Meyer, Helen Stepulovs, Regula Luethi, Stefan Borgwardt, Roselind Lieb, Undine E Lang, Christian G Huber, Julian Moeller

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PubMed Full text at PMC Publisher
In one paragraph

Article in BMC psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Mariela E JafféUniversity Psychiatric Clinics (UPK), University of Basel, Basel, Switzerland.
Stefan WeinmannUniversity Psychiatric Clinics (UPK), University of Basel, Basel, Switzerland.
Andrea H MeyerDivision of Clinical Psychology and Epidemiology, Department of Psychology, University of Basel, Basel, Switzerland.
Helen StepulovsUniversity Psychiatric Clinics (UPK), University of Basel, Basel, Switzerland.
Regula LuethiUniversity Psychiatric Clinics (UPK), University of Basel, Basel, Switzerland.
Stefan BorgwardtDepartment of Psychiatry and Psychotherapy, University of Luebeck, Luebeck, Germany.
Roselind LiebDivision of Clinical Psychology and Epidemiology, Department of Psychology, University of Basel, Basel, Switzerland.
Undine E LangUniversity Psychiatric Clinics (UPK), University of Basel, Basel, Switzerland.
Christian G HuberUniversity Psychiatric Clinics (UPK), University of Basel, Basel, Switzerland.
Julian MoellerUniversity Psychiatric Clinics (UPK), University of Basel, Basel, Switzerland. julian.moeller@upk.ch.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study investigated socio-demographic, psychiatric, and psychological characteristics of patients with high versus low utilization of psychiatric inpatient services. Our objective was to better understand the utilization pattern and to contribute to improving psychiatric care.

methodsOne-hundred and twenty inpatients of the University Psychiatric Clinics (UPK) Basel, Switzerland, participated in this cross-sectional study. All patients were interviewed using different clinical scales. As target variables we investigated the number of days of psychiatric inpatient treatment within a 30-month period.

resultsDespite including multiple relevant patient variables and using elaborate statistical models (classic univariate und multiple regression, LASSO regression, and non-linear random forest models), the selected variables explained only a small percentage of variance in the number of days of psychiatric inpatient treatment with cross-validated R

conclusionsHigh utilization behavior remains a complex phenomenon, which can only partly be explained by psychiatric, psychological, or social/demographic characteristics. Self-reported unmet patient needs seems to be a promising variable which may be targeted by further research in order to potentially reduce unnecessary hospitalizations or develop better tailored psychiatric treatments.

Indexed as

InpatientsMachine LearningMental DisordersAdultAgedCross-Sectional StudiesFemaleHospitalizationHospitals, PsychiatricHumansMaleMental Health ServicesMiddle AgedPatient Acceptance of Health CareSwitzerlandHigh utilizationPsychiatric inpatient servicesRe-hospitalisationRevolving doorSevere mental illness

Identifiers

PMID39716097
PMCPMC11667975

What Socratic holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.