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Abstract
Background Efforts to mitigate unwarranted variation in the quality of care require insight into the ‘level’ (eg, patient, physician, ward, hospital) at which observed variation exists. This systematic literature review aims to synthesise the results of studies that quantify the extent to which hospitals contribute to variation in quality indicator scores.
Methods Embase, Medline, Web of Science, Cochrane and Google Scholar were systematically searched from 2010 to November 2023. We included studies that reported a measure of between-hospital variation in quality indicator scores relative to total variation, typically expressed as a variance partition coefficient (VPC). The results were analysed by disease category and quality indicator type.
Results In total, 8373 studies were reviewed, of which 44 met the inclusion criteria. Casemix adjusted variation was studied for multiple disease categories using 144 indicators, divided over 5 types: intermediate clinical outcomes (n=81), final clinical outcomes (n=35), processes (n=10), patient-reported experiences (n=15) and patient-reported outcomes (n=3). In addition to an analysis of between-hospital variation, eight studies also reported physician-level variation (n=54 estimates). In general, variation that could be attributed to hospitals was limited (median VPC=3%, IQR=1%–9%). Between-hospital variation was highest for process indicators (17.4%, 10.8%–33.5%) and lowest for final clinical outcomes (1.4%, 0.6%–4.2%) and patient-reported outcomes (1.0%, 0.9%–1.5%). No clear pattern could be identified in the degree of between-hospital variation by disease category. Furthermore, the studies exhibited limited attention to the reliability of observed differences in indicator scores.
Conclusion Hospital-level variation in quality indicator scores is generally small relative to residual variation. However, meaningful variation between hospitals does exist for multiple indicators, especially for care processes which can be directly influenced by hospital policy. Quality improvement strategies are likely to generate more impact if preceded by level-specific and indicator-specific analyses of variation, and when absolute variation is also considered.
PROSPERO registration number CRD42022315850.
- Healthcare quality improvement
- Quality improvement methodologies
- Health policy
- Performance measures
Data availability statement
All data relevant to the study are included in the article or uploaded as online supplemental information.
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Data availability statement
All data relevant to the study are included in the article or uploaded as online supplemental information.
Footnotes
Contributors All authors contributed to the manuscript. All authors contributed to the overall conceptualisation and study design of the systematic review. MvdL and NS conducted the screening, data extraction and data analysis. All authors contributed to writing the manuscript, and all authors have agreed on the final version of the manuscript. FE is the guarantor of the study.
Funding This work was funded by Erasmus Initiative Smarter Choices for Better Health (no award/grant number).
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
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