Cargando…
Socioeconomic inequalities in the quality of primary care under Brazil's national pay-for-performance programme: a longitudinal study of family health teams
BACKGROUND: Many governments have introduced pay-for-performance programmes to incentivise health providers to improve quality of care. Evidence on whether these programmes reduce or exacerbate disparities in health care is scarce. In this study, we aimed to assess socioeconomic inequalities in the...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7900523/ https://www.ncbi.nlm.nih.gov/pubmed/33607031 http://dx.doi.org/10.1016/S2214-109X(20)30480-0 |
Sumario: | BACKGROUND: Many governments have introduced pay-for-performance programmes to incentivise health providers to improve quality of care. Evidence on whether these programmes reduce or exacerbate disparities in health care is scarce. In this study, we aimed to assess socioeconomic inequalities in the performance of family health teams under Brazil's National Programme for Improving Primary Care Access and Quality (PMAQ). METHODS: For this longitudinal study, we analysed data on the quality of care delivered by family health teams participating in PMAQ over three rounds of implementation: round 1 (November, 2011, to March, 2013), round 2 (April, 2013, to September, 2015), and round 3 (October, 2015, to December, 2019). The primary outcome was the percentage of the maximum performance score obtainable by family health teams (the PMAQ score), based on several hundred (ranging from 598 to 914) indicators of health-care delivery. Using census data on household income of local areas, we examined the PMAQ score by income ventile. We used ordinary least squares regressions to examine the association between PMAQ scores and the income of each local area across implementation rounds, and we did an analysis of variance to assess geographical variation in PMAQ score. FINDINGS: Of the 40 361 family health teams that were registered as ever participating in PMAQ, we included 13 934 teams that participated in the three rounds of PMAQ in our analysis. These teams were located in 11 472 census areas and served approximately 48 million people. The mean PMAQ score was 61·0% (median 61·8, IQR 55·3–67·9) in round 1, 55·3% (median 56·0, IQR 47·6–63·4) in round 2, and 61·6% (median 62·7, IQR 54·4–69·9) in round 3. In round 1, we observed a positive socioeconomic gradient, with the mean PMAQ score ranging from 56·6% in the poorest group to 64·1% in the richest group. Between rounds 1 and 3, mean PMAQ performance increased by 7·1 percentage points for the poorest group and decreased by 0·8 percentage points for the richest group (p<0·0001), with the gap between richest and poorest narrowing from 7·5 percentage points (95% CI 6·5 to 8·5) to –0·4 percentage points over the same period (–1·6 to 0·8). INTERPRETATION: Existing income inequalities in the delivery of primary health care were eliminated during the three rounds of PMAQ, plausibly due to a design feature of PMAQ that adjusted financial payments for socioeconomic inequalities. However, there remains an important policy agenda in Brazil to address the large inequities in health. FUNDING: UK Medical Research Council, Newton Fund, and CONFAP (Conselho Nacional das Fundações Estaduais de Amparo à Pesquisa). |
---|