Association between sick child facility readiness and quality of care at the individual and facility level in five low- and middle-income countries.

backgroundRaising the quality of health services is key to continued progress in improving child health, however, data on service quality are limited and difficult to interpret. The relationship between facility readiness and the quality of care is complex.

methodsUsing publicly available data sets from five low- and middle-income countries (LMICs), we assessed the relationship between structural factors and the clinical quality of care for managing sick children. We developed indices for readiness and quality accounting for available indicators, expert opinion, and alignment with integrated management of childhood illness (IMCI) guidelines. In each country, we assessed the association between readiness and quality, with and without adjusting for other factors. We considered associations overall, by domain, and by provider type, explored non-linear associations, and compared associations at the individual and facility-level.

resultsThe analysis included data from 3,149 health facilities and 11,159 sick child observations. In four of the five countries included in the analysis, we observed for every 10%-point increase in readiness, quality increased by about 1% point after adjusting for facility type and managing authority. There was little evidence of a non-linear relationship or a threshold effect altering the relationship between readiness and quality of care. Beyond readiness, younger child age, higher cost of care, and having a respiratory, digestive, or febrile diagnosis were most often associated with a higher quality of care. Higher "human resources" readiness domain scores were most consistently associated with better quality of care, while the quality of care domain of "treatment" was the least influenced by readiness. Facility-level associations did not vary greatly from individual-level associations.

conclusionsThe weak correlation observed suggests readiness plays an important role in quality but as currently measured cannot be used to characterize clinical quality of care. Data for assessing quality of health services are limited, presenting challenges for understanding impediments, assessing interventions, and gauging changes in the quality of care over time. We need better data to assess the quality of care being delivered in LMICs to understand what factors drive quality, with the goal of improving the management of sick children.