Evidence map›Paper›PMID 41814292›Full record

Observational studyBMC health services research2026

30-day healthcare utilisation after discharge from four General Internal Medicine departments in Switzerland: a prospective observational cohort study.

Gregor John, Loïc Payrard, Jörg Leuppi, Marco Mancinetti, Daniel Genné, Jacques Donzé

Abstract readObservational Study
In one paragraph

Observational study in BMC health services research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Gregor JohnDepartment of Internal Medicine, Neuchâtel Hospital Network, Rue de la Maladière 45, Neuchâtel, CH-2000 , Switzerland. gregor.john@rhne.ch.
Loïc PayrardDepartment of Medicine, Neuchâtel Hospital Network, Neuchâtel, Switzerland.
Jörg LeuppiFaculty of Medicine, University of Basel, Basel, Switzerland.
Marco MancinettiDepartment of Medicine, Fribourg Cantonal Hospital, Fribourg, Switzerland.
Daniel GennéFaculty of Medicine, University of Geneva, Rue Michel-Servet 1, Geneva, Switzerland.
Jacques DonzéDepartment of Medicine, Neuchâtel Hospital Network, Neuchâtel, Switzerland.

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung PP00P3_170656
6 · The paper itself

Abstract

aimTo assess healthcare utilisation within 30 days of discharge, identify predictors of this utilisation, and examine its association with mortality.

methodsAdults discharged from four Swiss medicine departments were prospectively followed. The 30-day Healthcare Utilisation (HUTIL) index was calculated with consultations with primary care physicians (PCPs), specialists or at emergency departments (EDs), home visits by nurses and hospital readmissions and compared to the Swiss national values. The one-year age- and sex-adjusted risks of dying for each three-point increase in the HUTIL index were calculated using a Cox regression model.

resultsOf 934 patients included, 78% attended medical consultations, 25% received home-care nurse visits, 12% were readmitted to hospital and 9% consulted at an ED within 30 days of discharge. The median number of healthcare services used per patient (2; IQR 25–75%: 1–13) and HUTIL index scores (3.0; IQR 25–75%: 1.0–8.0) were significantly higher than Switzerland’s 30-day national values of 0.7 (p < 0.001) and 1.6 (p < 0.001), respectively. High HOSPITAL scores, age, hospital lengths of stay, and number of comorbidities were all associated with healthcare utilisation. Compared to patients with HUTIL index scores of 0–2.9, patients with scores of 3–5.9 (adjusted hazard ratio [aHR] 2.7; 95%CI: 1.1–6.7), 6–8.9 (aHR 5.5; 95%CI: 2.8–10.6), and more than 8.9 (aHR 9.6; 95%CI: 5.2–17.9), all had higher risks of dying within one year.

conclusionHospital discharge is followed by periods of high healthcare services utilisation. HUTIL index scores correlate with patients’ prognoses.

Indexed as

Internal MedicinePatient Acceptance of Health CarePatient DischargeAgedAged, 80 and overEmergency Room VisitsFemaleHumansMaleMiddle AgedPatient ReadmissionProspective StudiesSwitzerlandHealthcare servicesHealthcare utilisationHospital dischargeHospital readmissionHOSPITAL scoreHUTIL indexInternal MedicineMortalityMultimorbidity

Identifiers

PMID41814292
PMCPMC13093932

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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 OpenQuestion graph.