Evidence map›Paper›PMID 32131817›Full record

SynthesisBMC health services research2020

Predicting the need for supportive services after discharged from hospital: a systematic review.

Daniel M Kobewka, Sunita Mulpuru, Michaël Chassé, Kednapa Thavorn, Luke T Lavallée, Shane W English, Benjamin Neilipovitz, Jonathan Neilipovitz, Alan J Forster, Daniel I McIsaac

Abstract readSystematic Review
In one paragraph

Synthesis in BMC health services research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Systematic review of prediction models for postacute care destination decision-making.Journal of the American Medical Informatics Association : JAMIA · 2021
    Pooled it
  2. Article
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  8. Predicting Length of Stay and Discharge Destination for Surgical Patients: A Cohort Study.International journal of environmental research and public health · 2020
    Article
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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.

Daniel M KobewkaDepartment of Medicine, Division of General Internal Medicine, The Ottawa Hospital, Civic Campus, 1053 Carling Avenue, Ottawa, Ontario, ON K1Y 4E9, Canada. dkobewka@toh.ca.ORCID http://orcid.org/0000-0002-1812-2335
Sunita MulpuruDepartment of Medicine, University of Ottawa, Ottawa, Ontario, Canada.
Michaël ChasséDepartment of Medicine (Critical Care), University of Montreal Hospital, Montreal, Quebec, Canada.
Kednapa ThavornClinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.
Luke T LavalléeDivision of Urology, Department of Surgery, University of Ottawa, Ottawa, Ontario, Canada.
Shane W EnglishDepartment of Medicine, University of Ottawa, Ottawa, Ontario, Canada.
Benjamin NeilipovitzClinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.
Jonathan NeilipovitzClinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.
Alan J ForsterDepartment of Medicine, Division of General Internal Medicine, The Ottawa Hospital, Civic Campus, 1053 Carling Avenue, Ottawa, Ontario, ON K1Y 4E9, Canada.
Daniel I McIsaacClinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSome patients admitted to acute care hospital require supportive services after discharge. The objective of our review was to identify models and variables that predict the need for supportive services after discharge from acute care hospital.

methodsWe performed a systematic review searching the MEDLINE, CINAHL, EMBASE, and COCHRANE databases from inception to May 1st 2017. We selected studies that derived and validated a prediction model for the need for supportive services after hospital discharge for patients admitted non-electively to a medical ward. We extracted cohort characteristics, model characteristics and variables screened and included in final predictive models. Risk of bias was assessed using the Quality in Prognostic Studies tool.

resultsOur search identified 3362 unique references. Full text review identified 6 models. Models had good discrimination in derivation (c-statistics > 0.75) and validation (c-statistics > 0.70) cohorts. There was high quality evidence that age, impaired physical function, disabilities in performing activities of daily living, absence of an informal care giver and frailty predict the need for supportive services after discharge. Stroke was the only unique diagnosis with at least moderate evidence of an independent effect on the outcome. No models were externally validated, and all were at moderate or higher risk of bias.

conclusionsDeficits in physical function and activities of daily living, age, absence of an informal care giver and frailty have the strongest evidence as determinants of the need for support services after hospital discharge.

trial registrationThis review was registered with PROSPERO #CRD42016037144.

Indexed as

Health Services Needs and DemandPatient DischargeHumansAssisted livingDischargeHome careResidential facilities

Identifiers

PMID32131817
PMCPMC7057581

What OpenQuestion 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 OpenQuestion graph.