DOI: 10.17037/data.00002886
title: Supporting files for: Performance bonuses and the quality of primary health care delivered by family health teams in Brazil: A difference-in differences analysis

description: Data gathered as part of a study in which we exploited municipality variation in the design features of Brazil’s National Programme for Improving Primary Care Access and Quality (PMAQ) to examine whether performance bonuses given to family health team workers were associated with changes in the quality of care and whether the size of bonus mattered. The files include the analysis dataset, the accompanying codebook, and the do-file containing the code used to run the analysis. Some variables used in the analysis are not publicly available and are therefore not contained in the analysis dataset. The restricted data are: the PMAQ scores for each family health team (our measure of quality of care) and the responses from a survey of municipality managers about performance bonuses (our exposure variables). For these restricted data, we generate placeholder variables using a random number generator to allow the do-file to run. Requests for access to these data should directed at the Department for Family Health: telephone number +55 61 33159044 or email desf@saude.gov.br
description: Pay-for-performance programmes to incentivise health providers to improve quality of care have been widely implemented globally. Despite intuitive appeal, evidence on the effectiveness of P4P is mixed, potentially due to differences in how schemes are designed. We exploited municipality variation in the design features of Brazil’s National Programme for Improving Primary Care Access and Quality (PMAQ) to examine whether performance bonuses given to family health team workers were associated with changes in the quality of care and whether the size of bonus mattered. We used a difference-in-differences approach combined with matching. We compared changes over time in the quality of care delivered by family health teams between (bonus) municipalities that chose to use some or all of the PMAQ money to provide performance-related bonuses to team workers with (non-bonus) municipalities that invested the funds using traditional input-based budgets. The primary outcome was the PMAQ score, a quality of care index on a scale of 0 to 100, based on several hundred indicators (ranging from 598 to 660) of healthcare delivery. We did one-to-one matching of bonus municipalities to non-bonus municipalities based on baseline demographic and economic characteristics. On the matched sample, we used ordinary least squares regression to estimate the association of any bonus and size of bonus with the pre-post change over time (between November 2011 and October 2015) in the PMAQ score. We performed subgroup analyses with respect to the local area income of the family health team. We provide the analysis dataset, analysis code and the codebook that underpinned the study. The analysis dataset combines data from five different sources. First, we obtained the PMAQ score and performance category of all family health teams in each implementation round from the Ministry of Health. Second, to capture variation in the design of PMAQ, we used data from an online survey of municipality health managers, conducted as part of the external evaluation in the third round of implementation. This survey asked various questions on incentive design, including whether the municipality passed on PMAQ funds as bonuses to family health team workers and the size of the bonuses as a percentage of staff salaries. Third, we used the 2010 Brazilian Population Census to measure the average monthly income of households in each census area. We geographically linked each health facility to a census sector, allowing us to measure the local area income of each family health team. Fourth, we obtained data on the characteristics of health facilities to which family health teams were attached from a census of health facilities done by the Ministry of Health in 2011. Fifth, we used established sources to construct a dataset of municipality socioeconomic and demographic characteristics for the year 2010. Some of the data used in the study are owned by the Ministry of Health in Brazil and we do not have permission to share the data publicly. These variables are not available in the dataset. Instead, for these restricted data, we generate placeholder variables using a random number generator to allow the do file to run and for illustration.