Introduction
The transition in 2015 from the Millennium Development Goals (MDG) to the Sustainable Development Goals (SDG) solidified a shift in global health from service-specific targets to broader health system goals.1 2 SDG goal 3 explicitly calls for the achievement of universal health coverage, with quality of healthcare services as an integral component.2 This evolution reflects the growing recognition that provision of a range of quality services is central to health systems delivering benefits to the population they serve.3 4
Expanding the focus beyond access to quality has led to an increased interest in measuring effective coverage, defined as the fraction of potential health gain actually delivered through the health system to the population in need.5 The WHO and World Bank have identified measuring and improving effective coverage as critical to achieving universal health coverage.6 Health systems deliver optimum health gains when those in need both access services and receive high-quality care. One approach to estimating effective coverage is the product of utilisation and service quality conditional on need for the service.7 It is a flexible construct that can be applied to specific elements of a given clinical service, the entirety of a service or a combination of essential health system services.8
We focus here on three essential services within primary care: antenatal care (ANC), family planning and care for sick children under 5. Successful delivery of each service is essential to achieving the SDG targets on maternal, neonatal and under-5 mortality,9 but research to date has identified substantial variation in the clinical quality of these services in low-income and middle-income countries.10 While these services are far from the entirety of primary care, their widespread provision and the existence of comparable crossnational measurement of their utilisation and quality make them useful tracer services for the measurement of effective primary care. Researchers and policymakers have called for better measures of primary care performance in particular to monitor health system strengthening efforts.11 As demonstrated by disproportionate progress towards MDG targets relative to other health system indicators,12 crossnational measurement may be an important tool in encouraging improved performance.
While crude coverage can typically be estimated from household survey data, assessing effective coverage depends on valid and appropriate measures of quality,7 which require clear conceptualisation and sufficient data to achieve. Quality measures are commonly organised into three domains: structure, process and outcomes.13 Each domain provides distinct insights into health service delivery: the basic input and capacity necessary to provide care, the actual clinical content of care, and the patient outcome thereafter based on both the quality of care and factors unrelated to the health system. Following Tanahashi’s original health service coverage framework,14 research describing coverage combined with measures of structural quality frequently refers to accessible coverage, a precursor to effective coverage.15 We review prior research related to effective coverage of ANC, family planning and care for sick children.
Of the three services, ANC has been the subject of most research, with a range of effective coverage studies from subnational assessment to crosscountry comparisons.15–23 These studies uniformly measure effective coverage based on receipt of essential services such as blood pressure measurement or blood testing during ANC. For example, studies in Mexico have found that most states reach between half and 80% of women with appropriate ANC,18 with greater effective coverage for women with insurance,22 while studies in several low-income countries have found that fewer than 15% of women received a minimum set of essential services during pregnancy.19 21 23
Research on effective coverage of family planning and sick-child care is much less extensive, with a focus on structural measures such as facility readiness.16 Even these measures suggest considerable quality shortfalls: a recent study in Kenya found a drop of 28% in family planning coverage when considering facility readiness. Studies of sick-child care have identified gaps in both access and quality, with effective coverage of acute respiratory illness estimated as only 41% in Kenya and 60% in Mexico.8 16 An innovative study of malaria in sub-Saharan Africa combined maternal report of treatment source with studies of treatment type to calculate expected cure rates; the findings suggest an average effective coverage of only 40%, ranging from 7% in Somalia to 71% in Botswana.24 Across all services and settings, the findings point to dramatic gaps in population health coverage once quality of care is accounted for.
Out of this body of evidence, two studies discuss the creation of aggregate measures. Nguhiu et al 16 present the average of effective coverage for maternal and child health services in Kenya, weighted by population need for the service. They find that aggregate effective coverage is increasing in Kenya, with some suggestion that inequalities between wealthy and poor populations are decreasing. Lozano et al 8 explored multiple weighting methods to calculate a metric of health system effective coverage and, finding high concordance across methods, presented the simple average as the most understandable metric. This composite metric usefully identifies the geographical areas of the country most in need of health system improvement.
The findings from the rapidly expanding literature on effective coverage in maternal and child health services demonstrate the need to consider quality in assessing the true population receipt of health services. However, little existing research considers more than a single clinical service or country, limiting generalisability. In this work, we combine nationally representative facility and population survey data from eight countries to evaluate effective coverage of three primary care services at the subnational level. We use quality measures based on directly observed clinical care from facility surveys to adjust coverage measures from population surveys. We compare effective coverage across services, calculate a composite effective coverage metric, and identify gaps in effective coverage both within and between low-income and middle-income countries.