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Measuring patient-centred system performance: a scoping review of patient-centred care quality indicators
  1. Maria-Jose Santana1,2,
  2. Sadia Ahmed2,
  3. Diane Lorenzetti1,3,
  4. Rachel J Jolley1,
  5. Kimberly Manalili1,
  6. Sandra Zelinsky1,
  7. Hude Quan1,
  8. Mingshan Lu1,4
  1. 1 Community Health Sciences, University of Calgary, Calgary, Alberta, Canada
  2. 2 Department of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
  3. 3 Health Sciences Library, University of Calgary, Calgary, Alberta, Canada
  4. 4 Department of Economics, University of Calgary, Calgary, Alberta, Canada
  1. Correspondence to Dr Maria-Jose Santana; mjsantan{at}ucalgary.ca

Abstract

Objectives The shift to the patient-centred care (PCC) model as a healthcare delivery paradigm calls for systematic measurement and evaluation. In an attempt to develop patient-centred quality indicators (PC-QIs), this study aimed to identify quality indicators that can be used to measure PCC.

Methods Design: scoping review. Data Sources: studies were identified through searching seven electronic databases and the grey literature. Search terms included quality improvement, quality indicators, healthcare quality and PCC. Eligibility Criteria: articles were included if they mentioned development and/or implementation of PC-QIs. Data Extraction and Synthesis: extracted data included study characteristics (country, year of publication and type of study/article), patients’ inclusion in the development of indicators and type of patient populations and point of care if applicable (eg, in-patient, out-patient and primary care).

Results A total 184 full-text peer-reviewed articles were assessed for eligibility for inclusion; of these, 9 articles were included in this review. From the non–peer-reviewed literature, eight documents met the criteria for inclusion in this study. This review revealed the heterogeneity describing and defining the nature of PC-QIs. Most PC-QIs were presented as PCC measures and identified as guidelines, surveys or recommendations, and therefore cannot be classified as actual PC-QIs. Out of 502 ways to measure PCC, only 25 were considered to be actual PC-QIs. None of the identified articles implemented the quality indicators in care settings.

Conclusion The identification of PC-QIs is a key first step in laying the groundwork to develop evidence-based PC-QIs. Research is needed to continue the development and implementation of PC-QIs for healthcare quality improvement.

  • patient-centred care
  • quality indicators
  • healthcare quality
  • quality improvement

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

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Footnotes

  • Patient consent for publication Not required.

  • Contributors M-JS conceived the study, and all authors identified key literature to be included in the review. M-JS led the drafting of the manuscript and key discussion points with support from DL, RJJ, SA, ML and KM. SA managed the design of the tables (with feedback from all authors), and management of references. All authors provided important intellectual contribution and guidance throughout the development of the manuscript. HQ, DL, SZ and ML provided guidance on the presentation of the findings and guidance on final revisions. All of the authors contributed to critical review and revisions to the manuscript, agreeing on the final version.

  • Funding M-JS secured funding from the M.S.I Foundation (Grant #886) based in Alberta, Canada. ML acknowledges the support from the Alberta’s Strategy for Patient Oriented Research (SPOR).

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement No additional data available.

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