Methodological Considerations for Linking Household and Healthcare Provider Data for Estimating Effective Coverage: A Systematic Review

Abstract

Effective coverage measures assess the proportion of a population that receive a health intervention with sufficient quality to achieve health benefit. Linking population-based surveys and health facility data is a promising means of generating effective coverage estimates, however, little guidance exists on methodological considerations for these analyses. We conducted a systematic review to assess existing knowledge related to 1) the suitability of data used in linking analyses, 2) the implications of the design of existing data sources commonly used in linking analyses, and 3) the impact of choice of method for combining datasets to obtain linked coverage estimates. The primary search was completed in Medline, with additional reviews of select sources. Of 3192 papers reviewed, 62 publications addressed issues related to linking household and provider datasets. Limited data suggest household surveys can be used to identify sources of care, but their validity in estimating a denominator of intervention need was variable. Methods for collecting provider data and constructing quality indices were variable and presented limitations. There was little empirical data supporting an association between structural, process, and outcome quality. Few studies addressed the influence of the design of common data sources on linking analyses, including imprecise household GIS data, provider sampling frame and sampling design, and estimate stability. There was a lack of concrete evidence around the impact of these factors on linked effective coverage estimates. The most consistent evidence suggested under certain conditions, combining data sets based on geographical proximity (ecological linking) produced similar estimates to linking based on the specific provider utilized (exact-match linking). Linking household and healthcare provider can leverage existing data sources to generate more informative estimates of intervention coverage and care. However, there is need for additional research to develop evidence-based, standardized best practices for these analyses.

Stability of healthcare quality measures for maternal and child services: Analysis of the continuous service provision assessment of health facilities in Senegal, 2012–2018

“…These uses often extend to years past the date of data collection. In particular, estimates of effective coverage may be calculated from health facility assessments and population data measured at different points in time; limited empirical evidence is available to assess the longevity of information from health facility assessments to support this practice [15]. Use of quality measures for description and benchmarking, on their own or as part of effective coverage measures, requires stability in the actual value of the measure from time of measurement to when inference is made; use for identification of better or worse performers relies on stability in classifications over time.…”

A rapid systematic review and evidence synthesis of effective coverage measures and cascades for childbirth, newborn and child health in low- and middle-income countries

“…Each of these areas of heterogeneity in definition and construction of QoC influenced the effective coverage estimates. Heterogeneity is not limited to the issues identified in this review: a recent review of methodological considerations for linking household and health facility data also identified a lack of standardisation in approaches to linking [ 69 ].…”

The effect of sampling health facilities on estimates of effective coverage: a simulation study

“…While numerous analyses have attempted to combine data from these sources, the methods for linking these data, constructing indicators, and interpreting results are highly variable (2). The most common and feasible approach is to ecologically link households with health care providers based on geographic proximity or administrative catchment (3).…”