Abstract
BackgroundVariability in processes of care and outcomes has been reported widely in high-income settings (at geographic, hospital, physician group and individual physician levels); however, such variability and the factors driving it are rarely examined in low-income settings.MethodsUsing data from a cross-sectional survey undertaken in 22 hospitals (60 case records from each hospital) across Kenya that aimed at evaluating the quality of routine hospital services, we sought to explore variability in four binary inpatient paediatric process indicators. These included three prescribing tasks and use of one diagnostic. To examine for sources of variability, we examined intra-class correlation coefficients (ICC) and their changes using multi-level mixed models with random intercepts for hospital and clinician levels and adjusting for patient and clinician level covariates.ResultsLevels of performance varied substantially across indicators and hospitals. The absolute values for ICCs also varied markedly ranging from a maximum of 0.48 to a minimum of 0.09 across the models for HIV testing and prescription of zinc, respectively. More variation was attributable at the hospital level than clinician level after allowing for nesting of clinicians within hospitals for prescription of quinine loading dose for malaria (ICC = 0.30), prescription of zinc for diarrhoea patients (ICC = 0.11) and HIV testing for all children (ICC = 0.43). However, for prescription of correct dose of crystalline penicillin, more of the variability was explained by the clinician level (ICC = 0.21). Adjusting for clinician and patient level covariates only altered, marginally, the ICCs observed in models for the zinc prescription indicator.ConclusionsPerformance varied greatly across place and indicator. The variability that could be explained suggests interventions to improve performance might be best targeted at hospital level factors for three indicators and clinician factors for one. Our data suggest that better understanding of performance and sources of variation might help tailor improvement interventions although further data across a larger set of indicators and sites would help substantiate these findings.
Highlights
Health systems are making efforts to control variation in care quality to raise overall standards and reduce geographic inequalities [1,2]
In the third model, we introduced patient level covariates to model 2 as fixed effects in three separate steps to explore the effect of case mix on the variability observed: a) Step 1 - Age and gender were added because they are not influenced by either hospital or clinician behaviour, b) Step 2 - Disease severity and co-morbidity were added because these may vary by hospital and their presence may influence clinician behaviour, c) Step 3 - All patient level covariates, disease severity, co-morbidity, age and gender, were added to explore the overall effect of patient level covariates
We present intra-class correlation coefficients (ICC) estimates representing total variability explained by the model; changes in ICC estimates observed after adding the clinician level demonstrate the additional variability explained by the clinician level after allowing nesting of clinicians within hospitals (the difference in ICC estimated in the models with and without clinicians)
Summary
Health systems are making efforts to control variation in care quality to raise overall standards and reduce geographic inequalities [1,2]. There are few data on quality of care but these suggest that quality of care varies greatly across place [3,4]. These wide variations and the factors driving them are, rarely examined in low-income settings. Variation in care has been associated with geographic regions or communities [5,6], hospitals or primary care units [7] and physicians [1]. Variability in processes of care and outcomes has been reported widely in high-income settings (at geographic, hospital, physician group and individual physician levels); such variability and the factors driving it are rarely examined in low-income settings
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