Evidence map›Paper›PMID 36978003›Full record

ArticleBMC geriatrics2023

Determining the factors influencing the selection of post-acute care models by patients and their families: a qualitative content analysis.

Ya-Hui Hsu, Tsong-Hai Lee, Kuo-Piao Chung, Yu-Chi Tung

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Article in BMC geriatrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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

4 citing papers in PubMed.

  1. Article
  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

4 authors.

Ya-Hui HsuInstitute of Health Policy and Management, College of Public Health, National Taiwan University, Taipei, Taiwan.
Tsong-Hai LeeStroke Center, Department of Neurology, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan.
Kuo-Piao ChungInstitute of Health Policy and Management, College of Public Health, National Taiwan University, Taipei, Taiwan.
Yu-Chi TungInstitute of Health Policy and Management, College of Public Health, National Taiwan University, Taipei, Taiwan. yuchitung@ntu.edu.tw.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study conducted in-depth interviews to explore the factors that influence the choice of a post-acute care (PAC) model (inpatient rehabilitation hospital, skilled nursing facility, home health, and outpatient rehabilitation) among stroke patients and their families.

methodsWe conducted semi-structured, in-depth interviews of 21 stroke patients and their families at four hospitals in Taiwan. Content analysis was used in this qualitative study.

resultsResults revealed five main factors that influence respondents' choice of PAC: (1) medical professionals' suggestions, (2) health care accessibility, (3) continuity and coordination of care, (4) willingness and prior experience of patients and their relatives and friends, and (5) economic factors.

conclusionsThis study identifies five main factors that affect the choice of PAC models among stroke patients and their families. We suggest that policymakers establish comprehensive health care resources based on the needs of patients and families. Health care providers shall provide professional recommendations and adequate information to support decision-making, which aligns with the preferences and values of patients and their families. From this research, we hope to improve the accessibility of PAC services in order to enhance the quality of care for stroke patients.

Indexed as

StrokeStroke RehabilitationHealth PersonnelHospitalsHumansQualitative ResearchSubacute CareTaiwanFunctional disabilityPatient-centred carePost-acute care modelRehabilitationStroke

Identifiers

PMID36978003
PMCPMC10045930

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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.