Evidence map›Paper›PMID 39534459›Full record

ReviewmHealth2024

Barriers to hospital-at-home acceptance: a systematic review of reasons for patient refusal.

Cesar A Gomez-Cabello, Sahar Borna, Sophia M Pressman, Syed Ali Haider, Antonio J Forte, Jennifer B Cowart, Michael J Maniaci

Abstract readReview
In one paragraph

Review in mHealth, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Observational
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

7 authors.

Cesar A Gomez-CabelloDivision of Plastic Surgery, Mayo Clinic, Jacksonville, FL, USA.ORCID https://orcid.org/0009-0008-0603-3192
Sahar BornaDivision of Plastic Surgery, Mayo Clinic, Jacksonville, FL, USA.ORCID https://orcid.org/0000-0002-7845-7356
Sophia M PressmanDivision of Plastic Surgery, Mayo Clinic, Jacksonville, FL, USA.ORCID https://orcid.org/0009-0000-0398-8024
Syed Ali HaiderDivision of Plastic Surgery, Mayo Clinic, Jacksonville, FL, USA.ORCID https://orcid.org/0009-0007-5621-2861
Antonio J ForteDivision of Plastic Surgery, Mayo Clinic, Jacksonville, FL, USA.ORCID https://orcid.org/0000-0003-2004-7538
Jennifer B CowartDivision of Hospital Internal Medicine, Mayo Clinic, Jacksonville, FL, USA.ORCID https://orcid.org/0000-0002-7127-7432
Michael J ManiaciDivision of Hospital Internal Medicine, Mayo Clinic, Jacksonville, FL, USA.ORCID https://orcid.org/0000-0002-2731-1787

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hospital-at-home (H@H) models have gained recognition as a safe and potentially cost-effective solution for the current rising global healthcare needs. However, despite these models' potential, their adoption has been limited partly due to patients refusing care at home. This systematic review analyses the reasons behind their refusal. Methods: We searched five databases: Embase, Google Scholar, PubMed, Scopus, and Web of Science, limiting our search to papers from 2005 to 2024. Our search focused on papers reporting patient-provided reasons for declining treatment in a H@H setting without language or country restrictions. In addition to reasons for refusal, we extracted patient demographics and predictors for refusal to ensure a broad understanding of the factors influencing patient decisions. The quality of the studies included was evaluated using the Mixed Methods Appraisal Tool (MMAT) version 2018. Results: From the 1,067 articles identified, seven met our inclusion criteria. The papers reported reasons from 418 patients participating in diverse H@H models from the United States, United Kingdom, Spain, and Singapore, primarily focusing on acute home-based care. The most common reasons for declination included concerns about model effectiveness, safety at home, preference for in-hospital care, physician advice, family burden, and visitor concerns. Additionally, common significant demographic factors associated with decliners were the enrollment site, partnership or marital status, risk of adverse outcomes, and previous healthcare utilization. Conclusions: Understanding patients' motivations for declining H@H is crucial for its successful implementation. Targeted communication strategies and collaboration between healthcare providers are paramount to ensure that patients understand the benefits and safety of H@H models. Future research should explore effective communication and engagement techniques to address patient apprehensions and broaden H@H adoption.

Indexed as

home-based hospitalHospital-at-home (H@H)patient declinationpatient perceptionspatient preferences

Identifiers

PMID39534459
PMCPMC11557161

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.