Evidence map›Paper›PMID 40791831›Full record

ReviewMayo Clinic proceedings. Digital health2025

Virtual Health Care in Hospital-at-Home Models for Patients With Acute Infections: A Scoping Review.

Maria Normand Larsen, Tatjana Sandreva Dreisig, Maja Kjær Rasmussen, Anders N Ø Schultz, Thyge Lynghøj Nielsen, Thea K Fischer

Abstract readReview
In one paragraph

Review in Mayo Clinic proceedings. Digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Review
  4. Review
  5. Article
  6. Review
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.

Maria Normand LarsenDepartment of Clinical Research, Nordsjællands Hospital, Capital Region, Denmark.
Tatjana Sandreva DreisigDepartment of Clinical Research, Nordsjællands Hospital, Capital Region, Denmark.
Maja Kjær RasmussenCentre for Innovative Medical Technology, Odense University Hospital, Denmark.
Anders N Ø SchultzInternal Medicine Research Unit, University Hospital of Southern Denmark, Aabenraa, Denmark.
Thyge Lynghøj NielsenDepartment of Clinical Research, Nordsjællands Hospital, Capital Region, Denmark.
Thea K FischerDepartment of Clinical Research, Nordsjællands Hospital, Capital Region, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Given the imbalance between high care demand and strained hospital capacity, hospital-at-home (HaH) models offer a potential solution by providing hospital-level care in patients' homes. This scoping review maps the literature on hospital-led virtual health care within HaH models for acute infections, focusing on intervention characteristics and evaluation designs. Following Johanna Briggs Institute guidelines and PRISMA-ScR, we included studies on virtual and hybrid HaH models using telemedicine for remote monitoring and interventions. The literature searches were performed from October 3, 2022 to October 22, 2022, and updated on July 11, 2024 and identified 15,062 potentially relevant records. From these, 79 studies met the inclusion criteria, highlighting the diversity of HaH models and their evaluations. Hybrid models provided broader treatment options, but many studies lacked detailed intervention descriptions, complicating implementation and meta-analyses. Most studies evaluated patient outcomes, with limited attention to health care staff and relatives. Nearly 45,000 participants were assessed, but only 254 participated in randomized controlled trials, indicating a need for more high-level evidence. Relevant gaps remain, including model heterogeneity and inconsistent reporting.

Identifiers

PMID40791831
PMCPMC12337863

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.