Linking household and facility data for better coverage measures in reproductive, maternal, newborn, and child health care: systematic review.
BACKGROUND
Currently many measures of intervention coverage obtained from household surveys do not measure actual health intervention/service delivery, resulting in a need for linking reports of care-seeking with assessments of the service environment in order to improve measurements. This systematic review aims to identify evidence of different methods used to link household surveys and service provision assessments, with a focus on reproductive, maternal, newborn and child health care, in low- and middle-income countries.


METHODS
Using pre-defined search terms, articles published in peer-reviewed journals and the grey literature after 1990 were identified, their reference lists scanned and linking methods synthesized.


RESULTS
A total of 59 articles and conference presentations were carefully reviewed and categorized into two groups based on the linking method used: 1) indirect/ecological linking that included studies in which health care-seeking behavior was linked to all or the nearest facilities or providers of certain types within a geographical area, and 2) direct linking/exact matching where individuals were linked with the exact provider or facility where they sought care. The former approach was employed in 51 of 59 included studies, and was particularly common among studies that were based on independent sources of household and facility data that were nationally representative. Only eight of the 59 reviewed studies employed direct linking methods, which were typically done at the sub-national level (eg, district level) and often in rural areas, where the number of providers was more limited compared to urban areas.


CONCLUSIONS
Different linking methods have been reported in the literature, each category has its own set of advantages and limitations, in terms of both methodology and practicality for scale-up. Future studies that link household and provider/facility data should also take into account factors such as sources of data, the timing of surveys, the temporality of data points, the type of services and interventions, and the scale of the study in order to produce valid and reliable results.
Department of Global Community Health and Behavioral Sciences, Tulane University School of Public Health and Tropical Medicine, Tulane, LA, USA.
Mai
M
Do
Department of Global Health Management and Policy, Tulane University School of Public Health and Tropical Medicine, Tulane, LA, USA.
Angela
A
Micah
Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, Scotland, UK.
Luciana
L
Brondi
Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, Scotland, UK.
Harry
H
Campbell
Faculty of Infectious and Tropical Disease, London School of Hygiene and Tropical Medicine, London, UK.
Tanya
T
Marchant
Center for Applied Malaria Research and Evaluation, Department of Tropical Medicine, Tulane University School of Tropical Medicine, Tulane, LA, USA.
Thomas
T
Eisele
Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Melinda
M
Munos
D003695:Delivery of Health Care; D005191:Family Characteristics; D005260:Female; D006268:Health Facilities; D006282:Health Personnel; D006296:Health Services; D006302:Health Services Research / Q000379:methods*; D006801:Humans; D008297:Male; D000068101:Maternal-Child Health Services; D010342:Patient Acceptance of Health Care