Evidence map›Paper›PMID 38706154›Full record

ArticleHealth policy and planning2024

Understanding the municipal-level design and adaptation of pay-for-performance schemes across two states of Brazil.

Nasser Fardousi, Garibaldi Dantas Gurgel Junior, Helena Shimizu, Keila Silene de Brito E Silva, Everton Da Silva, Mariana Olivia Santana Dos Santos, Adriana Falangola Benjamin Bezerra, Luciano Gomes, Timothy Powell-Jackson, Juliana Sampaio and 1 more

Abstract read
In one paragraph

Article in Health policy and planning, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Nasser FardousiDepartment of Global Health and Development, London School of Hygiene & Tropical Medicine, London WC1H 9SH, UK.ORCID 0000-0002-0306-8612
Garibaldi Dantas Gurgel JuniorOswaldo Cruz Foundation-Fiocruz, Pernambuco 50740-465, Brazil.
Helena ShimizuUniversity of Brasilia, Brasília 70910-900, Brazil.
Keila Silene de Brito E SilvaCentro Acadêmico de Vitória, Federal University of Pernambuco, Recife, Pernambuco 55608-680, Brazil.
Everton Da SilvaUniversity of Brasilia, Brasília 70910-900, Brazil.ORCID 0000-0001-8747-4185
Mariana Olivia Santana Dos SantosOswaldo Cruz Foundation-Fiocruz, Pernambuco 50740-465, Brazil.
Adriana Falangola Benjamin BezerraCentre for Medical Sciences, Federal University of Pernambuco, Recife, Pernambuco 50670-901, Brazil.
Luciano GomesDepartment of Health Promotion, Federal University of Paraíba, João Pessoa, Paraíba 58051-900, Brazil.
Timothy Powell-JacksonDepartment of Global Health and Development, London School of Hygiene & Tropical Medicine, London WC1H 9SH, UK.
Juliana SampaioDepartment of Health Promotion, Federal University of Paraíba, João Pessoa, Paraíba 58051-900, Brazil.
Josephine BorghiDepartment of Global Health and Development, London School of Hygiene & Tropical Medicine, London WC1H 9SH, UK.

Funding

Fundação de Amparo à Pesquisa do Distrito Federal (FAPDF), Fundação de Amparo à Ciência e Tecnologia do Estado de PernambucoFundação de Apoio à Pesquisa do Estado da ParaíbaMedical Research Council (MRC) MR/R022828/1The Brazilian National Council for the States Funding Agencies (CONFAP)The Newton Fund
6 · The paper itself

Abstract

The design of complex health systems interventions, such as pay for performance (P4P), can be critical to determining such programmes' success. In P4P programmes, the design of financial incentives is crucial in shaping how these programmes work. However, the design of such schemes is usually homogenous across providers within a given scheme. Consequently, there is a limited understanding of the strengths and weaknesses of P4P design elements from the implementers' perspective. This study takes advantage of the unique context of Brazil, where municipalities adapted the federal incentive design, resulting in variations in incentive design across municipalities. The study aims to understand why municipalities in Brazil chose certain P4P design features, the associated challenges and the local adaptations made to address problems in scheme design. This study was a multiple case study design relying on qualitative data from 20 municipalities from two states in Northeastern Brazil. We conducted two key informant interviews with municipal-level stakeholders and focus group discussions with primary care providers. We also reviewed municipal Primary Care Access and Quality laws in each municipality. We found substantial variation in the design choices made by municipalities regarding 'who was incentivized', the 'payment size' and 'frequency'. Design choices affected relationships within municipalities and within teams. Challenges were chiefly associated with fairness relating to 'who received the incentive', 'what is incentivized' and the 'incentive size'. Adaptations were made to improve fairness, mostly in response to pressure from the healthcare workers. The significant variation in design choices across municipalities and providers' response to them highlights the importance of considering local context in the design and implementation of P4P schemes and ensuring flexibility to accommodate local preferences and emerging needs. Attention is needed to ensure that the choice of 'who is incentivized' and the 'size of incentives' are inclusive and fair and the allocation and 'use of funds' are transparent.

Indexed as

Primary Health CareReimbursement, IncentiveBrazilCitiesFocus GroupsHealth Services AccessibilityHumansInterviews as TopicLocal GovernmentMotivationQualitative ResearchQuality of Health CareadaptationBrazilimplementationincentive design featuresPay-for-performancePMAQprimary care

Identifiers

PMID38706154
PMCPMC11308603

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.