LAUSR

Correspondence to Ms Josephine Exley; josephine. exley@ lshtm. ac. uk © Author(s) (or their employer(s)) 2022. Reuse permitted under CC BY. Published by BMJ. Effective coverage measures combine need, use and quality of care into a single metric to estimate the benefit of a service or intervention. Effective coverage is defined as the proportion of the population in need of a service that resulted in a positive health outcome from that service. For reproductive, maternal, newborn, child health and nutrition (RMNCH+N) services and interventions, effective coverage can be defined using a cascade (see figure 1). Effective coverage is represented by the final step of the cascade, while the full cascade can be used to identify bottlenecks in implementation. Universal health coverage means that highquality interventions and services are available to all. Inequalities in the availability and quality of health services exist at all levels: between geographic regions, within geographic regions, and even within individual health facilities and families. To address inequalities effective coverage measures should be disaggregated by key sociodemographic and economic variables—such as wealth, age, ethnicity, gender, education, place of residence. The potential to investigate inequalities in effective coverage is dependent on the data used to construct each step in the cascade. Here, we illustrate two methodological constraints that limit measuring inequalities in effective coverage when using: (1) only populationbased data such as Demographic and Health Surveys (DHS) or Multiple Indicator Cluster Surveys (MICS) (eg, complementary feeding interventions) and (2) linked population and health facility data such as Service Provision Assessments (SPA) or Service Availability and Readiness Assessments (SARA) (eg, highquality childbirth care), summarised in figure 1. 1. POPULATION-LEVEL DATA ALONE DO NOT PROVIDE INFORMATION ON ALL QUALITY OF CARE STEPS OF THE CASCADE AND MAY HAVE LOW VALIDITY. A literature review of effective coverage measures revealed 14 studies that used only populationlevel data. A common example was treatment for malnutrition that typically reflected caregiver reports of whether nutritional interventions were received, whether children were ever given nutritional interventions, and whether the interventions were used appropriately in the household (see figure 1). Quality dimensions of health provider practise were not incorporated. Since information on sociodemographic and economic variables is typically captured in household surveys, it is possible to stratify SUMMARY BOX