Evidence map›Paper›PMID 34468324›Full record

SynthesisJournal of medical Internet research2021

The Effect of Telehealth on Hospital Services Use: Systematic Review and Meta-analysis.

Guido M Peters, Laura Kooij, Anke Lenferink, Wim H van Harten, Carine J M Doggen

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 5 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

36 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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  7. Telehealth service use in people with cancer compared to people without cancer: analysis of Patient Experience Surveys in Australia.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
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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

5 authors.

Guido M PetersDepartment of Clinical Research, Rijnstate Hospital, Arnhem, Netherlands.ORCID 0000-0002-9035-4982
Laura KooijDepartment of Health Technology and Services Research, Technical Medical Centre, University of Twente, Enschede, Netherlands.ORCID 0000-0002-9047-3295
Anke LenferinkDepartment of Health Technology and Services Research, Technical Medical Centre, University of Twente, Enschede, Netherlands.ORCID 0000-0002-2276-5691
Wim H van HartenDepartment of Health Technology and Services Research, Technical Medical Centre, University of Twente, Enschede, Netherlands.ORCID 0000-0001-9580-0489
Carine J M DoggenDepartment of Clinical Research, Rijnstate Hospital, Arnhem, Netherlands.ORCID 0000-0003-4766-4333

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTelehealth interventions, that is, health care provided over a distance using information and communication technology, are suggested as a solution to rising health care costs by reducing hospital service use. However, the extent to which this is possible is unclear.

objectiveThe aim of this study is to evaluate the effect of telehealth on the use of hospital services, that is, (duration of) hospitalizations, and to compare the effects between telehealth types and health conditions.

methodsWe searched PubMed, Scopus, and the Cochrane Library from inception until April 2019. Peer-reviewed randomized controlled trials (RCTs) reporting the effect of telehealth interventions on hospital service use compared with usual care were included. Risk of bias was assessed using the Cochrane Risk of Bias 2 tool and quality of evidence according to the Grading of Recommendations Assessment, Development and Evaluation guidelines.

resultsWe included 127 RCTs in the meta-analysis. Of these RCTs, 82.7% (105/127) had a low risk of bias or some concerns overall. High-quality evidence shows that telehealth reduces the risk of all-cause or condition-related hospitalization by 18 (95% CI 0-30) and 37 (95% CI 20-60) per 1000 patients, respectively. We found high-quality evidence that telehealth leads to reductions in the mean all-cause and condition-related hospitalizations, with 50 and 110 fewer hospitalizations per 1000 patients, respectively. Overall, the all-cause hospital days decreased by 1.07 (95% CI -1.76 to -0.39) days per patient. For hospitalized patients, the mean hospital stay for condition-related hospitalizations decreased by 0.89 (95% CI -1.42 to -0.36) days. The effects were similar between telehealth types and health conditions. A trend was observed for studies with longer follow-up periods yielding larger effects.

conclusionsSmall to moderate reductions in hospital service use can be achieved using telehealth. It should be noted that, despite the large number of included studies, uncertainties around the magnitude of effects remain, and not all effects are statistically significant.

Indexed as

TelemedicineBiasHospitalizationHospitalsHumansLength of StayeHealthhealth services usehospitalizationmeta-analysissystematic reviewtelehealth

Identifiers

PMID34468324
PMCPMC8444037

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.