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

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  • Author(s): Okuda M;Okuda M; Yasuda A; Yasuda A; Tsumoto S; Tsumoto S
  • Source:
    BMC health services research [BMC Health Serv Res] 2021 Jan 13; Vol. 21 (1), pp. 63. Date of Electronic Publication: 2021 Jan 13.
  • Publication Type:
    Journal Article
  • Language:
    English
  • Additional Information
    • Source:
      Publisher: BioMed Central Country of Publication: England NLM ID: 101088677 Publication Model: Electronic Cited Medium: Internet ISSN: 1472-6963 (Electronic) Linking ISSN: 14726963 NLM ISO Abbreviation: BMC Health Serv Res Subsets: MEDLINE
    • Publication Information:
      Original Publication: London : BioMed Central, [2001-
    • Subject Terms:
    • Abstract:
      Background: Patient 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.
      Methods: The 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.
      Results: Of 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.
      Conclusions: Distance-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.
    • References:
      J Hosp Med. 2015 Aug;10(8):503-9. (PMID: 25940305)
      Med Care Res Rev. 2010 Feb;67(1):27-37. (PMID: 19638641)
      JAMA Surg. 2013 Apr;148(4):362-7. (PMID: 23715968)
      J Pain Symptom Manage. 2002 Mar;23(3):211-20. (PMID: 11888719)
      Am J Manag Care. 2011 Jan;17(1):41-8. (PMID: 21348567)
      Health Med Care Serv Rev. 1978 Jan-Feb;1(1):1, 3-15. (PMID: 10297474)
      Health Serv Res. 2005 Dec;40(6 Pt 2):2057-77. (PMID: 16316438)
      Arch Intern Med. 2006 Sep 25;166(17):1855-62. (PMID: 17000942)
      Med Care. 1983 Mar;21(3):294-322. (PMID: 6834907)
      Health Care Manage Rev. 2012 Jan-Mar;37(1):23-30. (PMID: 21918464)
      QRB Qual Rev Bull. 1989 Jun;15(6):172-9. (PMID: 2502747)
      Soc Sci Med. 1982;16(5):583-9. (PMID: 7100991)
      Med Care. 1975 Aug;13(8):669-82. (PMID: 1152557)
      PLoS One. 2013;8(4):e61097. (PMID: 23577195)
      Med Care Res Rev. 2014 Oct;71(5):522-54. (PMID: 25027409)
      Med Care. 1978 Mar;16(3):202-13. (PMID: 633970)
      Health Technol Assess. 2002;6(32):1-244. (PMID: 12925269)
      Scand J Caring Sci. 2013 Dec;27(4):785-91. (PMID: 23181421)
      QRB Qual Rev Bull. 1987 Apr;13(4):122-30. (PMID: 3108744)
      Health Serv Res. 2005 Dec;40(6 Pt 2):2078-95. (PMID: 16316439)
      Med Care. 1979 May;17(5):461-79. (PMID: 431154)
      Healthc Inform Res. 2012 Sep;18(3):178-85. (PMID: 23115740)
      QRB Qual Rev Bull. 1992 Feb;18(2):53-9. (PMID: 1574321)
      Health Serv Res. 2005 Dec;40(6 Pt 2):2018-36. (PMID: 16316436)
      J Pain Symptom Manage. 2010 Jan;39(1):100-15. (PMID: 19879107)
      Res Social Adm Pharm. 2017 Jul - Aug;13(4):849-856. (PMID: 27913084)
      N Engl J Med. 2008 Oct 30;359(18):1921-31. (PMID: 18971493)
      Health Serv Res. 2005 Dec;40(6 Pt 2):1977-95. (PMID: 16316434)
      Health Serv Res. 2010 Aug;45(4):1024-40. (PMID: 20528990)
      Med Care. 1970 Sep-Oct;8(5):429-36. (PMID: 4920640)
      BMC Health Serv Res. 2013 Feb 21;13:73. (PMID: 23433450)
      Lancet. 1999 Oct 16;354(9187):1321-6. (PMID: 10533859)
      J Clin Nurs. 2009 Dec;18(23):3333-41. (PMID: 19735337)
    • Contributed Indexing:
      Keywords: Clustering; Data mining; HCAHPS; Patient satisfaction
    • Publication Date:
      Date Created: 20210114 Date Completed: 20210514 Latest Revision: 20210514
    • Publication Date:
      20240105
    • Accession Number:
      PMC7805228
    • Accession Number:
      10.1186/s12913-020-06050-3
    • Accession Number:
      33441139