DOI: 10.17037/data.00000780
title: Matrika Household Survey in India

description: Data produced as part of a study to evaluate the impact of the Matrika social franchising model – a multi-faceted intervention that established a network of private providers and strengthened the skills of both public and private sector clinicians – and determine whether it has improved the quality and coverage of health services along the continuum of care for maternal, newborn and reproductive health in Uttar Pradesh, India.  The datasets cover two rounds of a household survey, performed in January 2015 and May 2016, of women who had recently given birth.
description: Data were collected during household interviews using CAPI (computer assisted personal interviewing) by staff of Sambodhi Research and Communications. The household survey was administered to women as a repeated cross-section in January 2015 (round 1) and May 2016 (round 2). Women were selected from the same clusters in each round. Eligible respondents included all women who gave birth in the previous 24 months (round 1) or 18 months (round 2), including those who had a stillbirth or whose child died since birth. Eligible women were identified through a census of households, conducted one month before the household survey round. Every member of the household was listed and then, for women aged 15 to 49 years, a series of questions probed whether she gave birth to a baby that was born alive, born dead or lost before birth. Using this sampling frame, eligible women in each cluster were randomly selected for interview. The household survey tool included the following modules: (1) household listing, (2) general healthcare interactions, (3) household characteristics, (4) wellbeing of husband, (5) pregnancy history, (6) family planning and antenatal care, (7) delivery and postnatal care, (8) child health, (9) interactions with community health workers, (10) information and perceptions of healthcare, and (11) wellbeing, mental health and physical health.

The study involved the selection of three types of clusters: 1) ‘intervention’ clusters with a Sky provider; 2) ‘internal comparison’ clusters with no social franchisee in the three intervention districts; 3) ‘external comparison’ clusters in three neighbouring districts where the social franchise model was not operating. Study clusters were selected one year after the first social franchisee was contracted using the following procedures. First, every Sky health provider was linked to its census area. At the time of selection there were 393 private providers in the network. This process identified 216 possible intervention clusters from which 60 clusters were selected at random. Second, internal comparison clusters were selected by matching without replacement the intervention clusters to 60 comparison areas within the same three districts. We performed exact matching on district and urban residences, and then within each strata, selected pairs of clusters with the smallest distance based on a Mahalanobis metric that was computed using census data on village characteristics (total population, % under 6 years, % females under 6 years, % female literate females, % scheduled tribe, % scheduled caste, % cultivator, and % “other” workers). To limit problems of contamination, comparison clusters adjacent to intervention areas could not be selected. Finally, the same matching procedure was performed to select 60 external comparison clusters from neighbouring districts.