Evidence map›Paper›PMID 33441139›Full record

ArticleBMC health services research2021

An approach to exploring associations between hospital structural measures and patient satisfaction by distance-based analysis.

Masumi Okuda, Akira Yasuda, Shusaku Tsumoto

Abstract read
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Article in BMC health services research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Masumi OkudaNursing Department, Matsue Red Cross Hospital, 83-1 Horo-machi, 690-8506, Matsue, Shimane, Japan. okuda_masumi@matsue.jrc.or.jp.ORCID http://orcid.org/0000-0002-1269-4105
Akira YasudaDepartment of Medical Informatics, School of Medicine, Shimane University, 89-1 Enya-cho, 693-8501, Izumo, Shimane, Japan.
Shusaku TsumotoDepartment of Medical Informatics, School of Medicine, Shimane University, 89-1 Enya-cho, 693-8501, Izumo, Shimane, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatient satisfaction studies have explored domains of patient satisfaction, the determinants of domains, and score differences of domains by patient/hospital structural measures but reports on the structure of patient satisfaction with respect to similarities among domains are scarce. This study is to explore by distance-based analysis whether similarities among patient-satisfaction domains are influenced by hospital structural measures, and to design a model evaluating relationships between the structure of patient satisfaction and hospital structural measures.

methodsThe Hospital Consumer Assessment of Healthcare Providers and Systems 2012 survey scores and their structural measures from the Hospital Compare website reported adjusted percentages of scale for each hospital. Contingency tables of nine measures and their ratings were designed based on hospital structural measures, followed by three different distance-based analyses - clustering, correspondence analysis, and ordinal multidimensional scaling - for robustness to identify homogenous groups with respect to similarities.

resultsOf 4,677 hospitals, 3,711 (79.3%) met the inclusion criteria and were analyzed. The measures were divided into three groups plus cleanliness. Certain combinations of these groups were shown to be dependent on hospital structural measures. High value ratings for communication and low value ratings for medication explanation, quietness and staff responsiveness were not influenced by hospital structural measures, but the varied-ratings domain group similarities, including items such as global evaluation and pain management, were affected by hospital structural measures.

conclusionsDistance-based analysis can reveal the hidden structure of patient satisfaction. This study suggests that hospital structural measures including hospital size, the ability to provide acute surgical treatment, and hospital interest in improving medical care quality are factors which may influence the structure of patient satisfaction.

Indexed as

HospitalsPatient SatisfactionCommunicationHealth Care SurveysHealth Facility SizeHumansQuality of Health CareClusteringData miningHCAHPSPatient satisfaction

Identifiers

PMID33441139
PMCPMC7805228

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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.