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University of Cambridge

The design of composite indicators of healthcare quality: a multi-method analysis

Abstract

dc:description.abstract

High profile composite indicators seeking to summarise aspects of the quality of healthcare organisations often have important impacts: they may be reputationally consequential for healthcare organisations, may affect prioritisation for inspection or action by regulators, and may be responsible for effecting changes in the way services are delivered. Use of composite indicators, which include examples such as the Hospital Compare Star Ratings in the US and the Quality and Outcomes Framework in the UK, is proliferating in healthcare. But to date there is limited understand of how such indicators should be designed and reported. This thesis seeks to address this gap, characterising relevant challenges in the design of composite indicators and exploring their reporting might be improved. My examination of composite indicators is formed from two principal components. The first comprises two quantitative studies, which are conceptually linked. These studies investigate the sensitivity of the ratings and rankings of hospitals to the exact technical methods by which composite indicators are produced. I show that composite indicators can be highly sensitive to technical decisions, and that different composite indicators are affected differently by these, rarely examined, technical issues. The second component is a qualitative interview study, for which I interviewed experts in performance measurement about the process of developing a composite indicator. This study highlighted two crucial aspects of the development of composite indicators. First, the purpose of a composite indicator needs to drive every aspect of technical decisions relating to their specification. Second, the development process should be iterative: developers must be willing and able to revise the purpose of the indicator and restart the development process if it subsequently becomes apparent that the composite indicator does not match the purpose for which it is being developed. The results of the quantitative and qualitative studies in this thesis revealed a number of challenges for the design of composite indicators, but also helped to identify possible ways for improving their design. The qualitative study catalogues important decision points which could be used as a framework for design choices for composite indicators. In combination with the results of the quantitative studies, which inter alia show the usefulness of applications of Monte Carlo sensitivity analysis as part of the development and evaluation of composites, this catalogue of decisions holds promise for identifying and addressing problems with composite indicator in the design stage and for offering critiques of existing indicators. Together these considerations point toward designing-in an iterative approach to processes used in the development of composite indicators, in which sensitivity analysis is used to assess the implications of each design decision. Finally, my results lay the groundwork for future development of a reporting guideline for the development and reporting of composite indicators of healthcare quality.

Degree

thesis:*
Name dc:type.qualificationname
Doctor of Philosophy (PhD)
Level dc:type.qualificationlevel
Doctoral
Grantor dc:publisher.institution
University of Cambridge
Year dc:date.issued
2021

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Barclay, Matthew
Advisors dc:contributor.advisor
  • Dixon-Woods, Mary
  • Lyratzopoulos, Georgios

Subjects

dc:subject × 4

Rights

dc:rights
Language dc:language
eng

Identifiers

dc:identifier.*
Author Identifier
0000-0003-1148-1922
OAI identifier oai:identifier
oai:www.repository.cam.ac.uk:1810/328778

Chain of custody

source
Harvested from
Cambridge University
Base URL
api.repository.cam.ac.uk/server/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Barclay, Matthew. The design of composite indicators of healthcare quality: a multi-method analysis. Doctoral thesis, University of Cambridge, 2021. https://doi.org/10.17863/CAM.76223