Can benchmarking Australian hospitals for quality identify and improve high and low performers? Disseminating research findings for hospitals. (5th February 2020)

• Record Type: Journal Article
• Authors: Hibbert, Peter; Saeed, Faisal; Taylor, Natalie; Clay-Williams, Robyn; Winata, Teresa; Clay, Chrissy; Hussein, Wadaha; Braithwaite, Jeffrey
• Is Part Of: International journal for quality in health care. Volume 32(2020)Supplement 1
• Page Start: 84
• Page End: 88
• Publication Date: 2020-02-05
• Subjects: hospital quality management systems -- patient-level factors -- patient safety -- hospital performance -- quality improvement -- benchmarking; Medical care -- Quality control -- Periodicals; 362.1068
• DOI: 10.1093/intqhc/mzz109
• Languages: English
• ISSNs: 1353-4505

Abstract

Abstract: This paper examines the principles of benchmarking in healthcare and how benchmarking can contribute to practice improvement and improved health outcomes for patients. It uses the Deepening our Understanding of Quality in Australia (DUQuA) study published in this Supplement and DUQuA's predecessor in Europe, the Deepening our Understanding of Quality improvement in Europe (DUQuE) study, as models. Benchmarking is where the performances of institutions or individuals are compared using agreed indicators or standards. The rationale for benchmarking is that institutions will respond positively to being identified as a low outlier or desire to be or stay as a high performer, or both, and patients will be empowered to make choices to seek care at institutions that are high performers. Benchmarking often begins with a conceptual framework that is based on a logic model. Such a framework can drive the selection of indicators to measure performance, rather than their selection being based on what is easy to measure. A Donabedian range of indicators can be chosen, including structure, process and outcomes, created around multiple domains or specialties. Indicators based on continuous variables allow organizations to understand where their performance is within a population, and their interdependencies and associations can be understood. Benchmarking should optimally target providers, in order to drive them towards improvement. The DUQuA and DUQuE studies both incorporated some of these principles into their design, thereby creating a model of how to incorporate robust benchmarking into large-scale health services research.