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Comparing healthcare quality: A common framework for both ordinal and cardinal data with an application to primary care variation in England
Author(s) -
Allanson Paul,
Cookson Richard
Publication year - 2022
Publication title -
health economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.55
H-Index - 109
eISSN - 1099-1050
pISSN - 1057-9230
DOI - 10.1002/hec.4597
Subject(s) - ordinal data , ordinal regression , quality (philosophy) , variation (astronomy) , health care , econometrics , ordered logit , ethnic group , statistics , data quality , primary care , computer science , medicine , mathematics , family medicine , operations management , economics , sociology , metric (unit) , philosophy , physics , epistemology , astrophysics , anthropology , economic growth
The paper proposes a framework for comparing the quality of healthcare providers and assessing the variation in quality between them, which is directly applicable to both ordinal and cardinal quality data on a comparable basis. The resultant measures are sensitive to the full distribution of quality scores for each provider, not just the mean or the proportion meeting some binary quality threshold, thereby making full use of the multicategory response data increasingly available from patient experience surveys. The measures can also be standardized for factors such as age, sex, ethnicity, health and deprivation using a distribution regression model. We illustrate by measuring the quality of primary care services in England in 2019 using three different sources of publicly available, general practice‐level information: multicategory response patient experience data, ordinal inspection ratings and cardinal clinical achievement scores. We find considerable variation at both local and regional levels using all three data sources. However, the correlation between the comparative quality indices calculated using the alternative data sources is weak, suggesting that they capture different aspects of general practice quality.