Article

Should measures of patient experience in primary care be adjusted for case mix? Evidence from the English General Practice Patient Survey

Cambridge Centre for Health Services Research, University of Cambridge, Cambridge, UK.
BMJ quality & safety (Impact Factor: 3.99). 05/2012; 21(8):634-40. DOI: 10.1136/bmjqs-2011-000737
Source: PubMed

ABSTRACT

Uncertainties exist about when and how best to adjust performance measures for case mix. Our aims are to quantify the impact of case-mix adjustment on practice-level scores in a national survey of patient experience, to identify why and when it may be useful to adjust for case mix, and to discuss unresolved policy issues regarding the use of case-mix adjustment in performance measurement in health care.
Secondary analysis of the 2009 English General Practice Patient Survey. Responses from 2 163 456 patients registered with 8267 primary care practices. Linear mixed effects models were used with practice included as a random effect and five case-mix variables (gender, age, race/ethnicity, deprivation, and self-reported health) as fixed effects.
Primary outcome was the impact of case-mix adjustment on practice-level means (adjusted minus unadjusted) and changes in practice percentile ranks for questions measuring patient experience in three domains of primary care: access; interpersonal care; anticipatory care planning, and overall satisfaction with primary care services.
Depending on the survey measure selected, case-mix adjustment changed the rank of between 0.4% and 29.8% of practices by more than 10 percentile points. Adjusting for case-mix resulted in large increases in score for a small number of practices and small decreases in score for a larger number of practices. Practices with younger patients, more ethnic minority patients and patients living in more socio-economically deprived areas were more likely to gain from case-mix adjustment. Age and race/ethnicity were the most influential adjustors.
While its effect is modest for most practices, case-mix adjustment corrects significant underestimation of scores for a small proportion of practices serving vulnerable patients and may reduce the risk that providers would 'cream-skim' by not enrolling patients from vulnerable socio-demographic groups.

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Available from: Georgios Lyratzopoulos
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    • "Relating case mix to funding strategies introduced a systematic bias of reporting more comorbidities, known as " upcoding " , for greater gains in several national health systems[12]. Such biases can change the relationship between patient profile and outcome across hospitals and would potentially lead to inaccurate or unfair provider comparisons and allocation of incentives[2,4,13141516. Different sources of information, employed by studies to verify consistency in hospital datasets , resulted in varying levels of agreement. "
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    • "Morbidity scores, designed to summarize comorbidity for individual patients, by summing scores for selected diseases, are widely used in research and service monitoring to adjust for baseline differences in patient groups or service providers [2]. In primary and ambulatory care, robust adjustment for case mix is important for valid interpretation of both observational research and routine health services outcome data [3]. A range of morbidity scores have been used, of which the Charlson index is the most well known [4]. "
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