Does payment for performance increase performance inequalities across health providers? A case study of Tanzania

Do health care quality improvement policies work for all? Distributional effects by baseline quality in South Africa

Health care quality improvement (QI) initiatives are being implemented by a number of low- and middle-income countries. However, there is concern that these policies may not reduce, or may even worsen, inequities in access to high-quality care. Few studies have examined the distributional impact of QI programmes. We study the Ideal Clinic Realization and Maintenance program implemented in health facilities in South Africa, assessing whether the effects of the program are sensitive to previous quality performance. Implementing difference-in-difference-in-difference and changes-in-changes approaches we estimate the effect of the program on quality across the distribution of past facility quality performance. We find that the largest gains are realized by facilities with higher baseline quality, meaning this policy may have led to a worsening of pre-existing inequity in health care quality. Our study highlights that the full consequences of QI programmes cannot be gauged solely from examination of the mean impact.

Who is paid in pay-for-performance? Inequalities in the distribution of financial bonuses amongst health centres in Zimbabwe

Although pay-for-performance (P4P) schemes have been implemented across low- and middle-income countries (LMICs), little is known about their distributional consequences. A key concern is that financial bonuses are primarily captured by providers who are already better able to perform (for example, those in wealthier areas), P4P could exacerbate existing inequalities within the health system. We examine inequalities in the distribution of pay-outs in Zimbabwe's national P4P scheme (2014-2016) using quantitative data on bonus payments and facility characteristics and findings from a thematic policy review and 28 semi-structured interviews with stakeholders at all system levels. We found that in Zimbabwe, facilities with better baseline access to guidelines, more staff, higher consultation volumes and wealthier and less remote target populations earned significantly higher P4P bonuses throughout the programme. For instance, facilities that were 1 SD above the mean in terms of access to guidelines, earned 90 USD more per quarter than those that were 1 SD below the mean. Differences in bonus pay-outs for facilities that were 1 SD above and below the mean in terms of the number of staff and consultation volumes are even more pronounced at 348 USD and 445 USD per quarter. Similarly, facilities with villages in the poorest wealth quintile in their vicinity earned less than all others-and 752 USD less per quarter than those serving villages in the richest quintile. Qualitative data confirm these findings. Respondents identified facility baseline structural quality, leadership, catchment population size and remoteness as affecting performance in the scheme. Unequal distribution of P4P pay-outs was identified as having negative consequences on staff retention, absenteeism and motivation. Based on our findings and previous work, we provide some guidance to policymakers on how to design more equitable P4P schemes.

Impact of global budget combined with pay-for-performance on the quality of care in county hospitals: a difference-in-differences study design with a propaensity-score-matched control group using data from Guizhou province, China

BACKGROUND

Provider payment system has a profound impact on health system performance. In 2016, a number of counties in rural Guizhou, China, implemented global budget (GB) for county hospitals with quality control measures. The aim of this study is to measure the impact of GB combined with pay-for-performance on the quality of care of inpatients in county-level hospitals in China.

METHODS

Inpatient cases of four diseases, including pneumonia, chronic asthma, acute myocardial infarction and stroke, from 16 county-level hospitals in Guizhou province that implemented GB in 2016 were selected as the intervention group, and similar inpatient cases from 10 county-level hospitals that still implemented fee-for-services were used as the control group. Propensity matching score (PSM) was used for data matching to control for age factors, and difference-in-differences (DID) models were constructed using the matched samples to perform regression analysis on quality of care for the four diseases.

RESULTS

After the implementation of GB, rate of sputum culture in patients with pneumonia, rate of aspirin at discharge, rate of discharge with β-blocker and rate of smoking cessation advice in patients with acute myocardial infarction increased. Rate of oxygenation index assessment in patient with chronic asthma decreased 20.3%. There are no significant changes in other indicators of process quality.

CONCLUSIONS

The inclusion of pay-for-performance in the global budget payment system will help to reduce the quality risks associated with the reform of the payment system and improve the quality of care. Future reform should also consider the inclusion of the pay-for-performance mechanism.

Long-term effects of payment for performance on maternal and child health outcomes: evidence from Tanzania

BACKGROUND

The success of payment for performance (P4P) schemes relies on their ability to generate sustainable changes in the behaviour of healthcare providers. This paper examines short-term and longer-term effects of P4P in Tanzania and the reasons for these changes.

METHODS

We conducted a controlled before and after study and an embedded process evaluation. Three rounds of facility, patient and household survey data (at baseline, after 13 months and at 36 months) measured programme effects in seven intervention districts and four comparison districts. We used linear difference-in-difference regression analysis to determine programme effects, and differential effects over time. Four rounds of qualitative data examined evolution in programme design, implementation and mechanisms of change.

RESULTS

Programme effects on the rate of institutional deliveries and antimalarial treatment during antenatal care reduced overtime, with stock out rates of antimalarials increasing over time to baseline levels. P4P led to sustained improvements in kindness during deliveries, with a wider set of improvements in patient experience of care in the longer term. A change in programme management and funding delayed incentive payments affecting performance on some indicators. The verification system became more integrated within routine systems over time, reducing the time burden on managers and health workers. Ongoing financial autonomy and supervision sustained motivational effects in those aspects of care giving not reliant on funding.

CONCLUSION

Our study adds to limited and mixed evidence documenting how P4P effects evolve over time. Our findings highlight the importance of undertaking ongoing assessment of effects over time.

Perceptions of nurses and physicians on pay-for-performance in hospital: a systematic review of qualitative studies

AIMS

To systematically examine perceptions of nurses and physicians on pay-for-performance in hospital.

BACKGROUND

Pay-for-performance projects have proliferated over the past two decades, most systematic reviews of which solely focused on its effectiveness in primary healthcare and the physicians' or nurses' attitudes. However, systematic reviews of qualitative approaches for better examining perceptions of both nurses and physicians in hospital are lacking.

EVALUATION

Electronic databases were systematic searched with date from its inception to December 31, 2020. Meta-aggregation synthesis methodology and the conceptual framework of the Theory of Planned Behavior were used to summarize findings.

KEY ISSUES

A total of nine studies were included. Three major synthesized themes were identified: (1) perceptions of the motivation effects and positive outcomes (2) perceptions about the design defects and negative effects (3) perceptions of the obstacles in the implementation process.

CONCLUSION

To maximize the intended positive effects, nurses' and physicians' perceptions should be considered and incorporated into the project design and implementation stage.

IMPLICATIONS FOR NURSING MANAGEMENT AND RESEARCH

The paper gives enlightenment to nurse managers on improving and advancing the cause of nurses when planning for or evaluating their institutions' policies on pay-for-performance in the future research.

Poor quality for the poor? A study of inequalities in service readiness and provider knowledge in Indonesian primary health care facilities

BACKGROUND

For many low and middle-income countries poor quality health care is now responsible for a greater number of deaths than insufficient access to care. This has in turn raised concerns around the distribution of quality of care in LMICs: do the poor have access to lower quality health care compared to the rich? The aim of this study is to investigate the extent of inequalities in the availability of quality health services across the Indonesian health system with a particular focus on differences between care delivered in the public and private sectors.

METHODS

Using the Indonesian Family Life Survey (wave 5, 2015), 15,877 households in 312 communities were linked with a representative sample of both public and private health facilities available in the same communities. Quality of health facilities was assessed using both a facility service readiness score and a knowledge score constructed using clinical vignettes. Ordinary least squares regression models were used to investigate the determinants of quality in public and private health facilities.

RESULTS

In both sectors, inequalities in both quality scores existed between major islands. In public facilities, inequalities in readiness scores persisted between rural and urban areas, and to a lesser extent between rich and poor communities.

CONCLUSION

In order to reach the ambitious stated goal of reaching Universal Health Coverage in Indonesia, priority should be given to redressing current inequalities in the quality of care.

Understanding the maternal and child health system response to payment for performance in Tanzania using a causal loop diagram approach

Payment for performance (P4P) has been employed in low and middle-income (LMIC) countries to improve quality and coverage of maternal and child health (MCH) services. However, there is a lack of consensus on how P4P affects health systems. There is a need to evaluate P4P effects on health systems using methods suitable for evaluating complex systems. We developed a causal loop diagram (CLD) to further understand the pathways to impact of P4P on delivery and uptake of MCH services in Tanzania. The CLD was developed and validated using qualitative data from a process evaluation of a P4P scheme in Tanzania, with additional stakeholder dialogue sought to strengthen confidence in the diagram. The CLD maps the interacting mechanisms involved in provider achievement of targets, reporting of health information, and population care seeking, and identifies those mechanisms affected by P4P. For example, the availability of drugs and medical commodities impacts not only provider achievement of P4P targets but also demand of services and is impacted by P4P through the availability of additional facility resources and the incentivisation of district managers to reduce drug stock outs. The CLD also identifies mechanisms key to facility achievement of targets but are not within the scope of the programme; the activities of health facility governing committees and community health workers, for example, are key to demand stimulation and effective resource use at the facility level but both groups were omitted from the incentive system. P4P design considerations generated from this work include appropriately incentivising the availability of drugs and staffing in facilities and those responsible for demand creation in communities. Further research using CLDs to study heath systems in LMIC is urgently needed to further our understanding of how systems respond to interventions and how to strengthen systems to deliver better coverage and quality of care.

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Holistic analysis key to avoiding suboptimal P4P performance.

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Availability of drugs is influenced by P4P and affects success of P4P.

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Need to incentivise groups outside facility that support service coverage.

Paying for performance to improve the delivery of health interventions in low- and middle-income countries

BACKGROUND

There is growing interest in paying for performance (P4P) as a means to align the incentives of healthcare providers with public health goals. Rigorous evidence on the effectiveness of these strategies in improving health care and health in low- and middle-income countries (LMICs) is lacking; this is an update of the 2012 review on this topic.

OBJECTIVES

To assess the effects of paying for performance on the provision of health care and health outcomes in low- and middle-income countries.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, and 10 other databases between April and June 2018. We also searched two trial registries, websites, online resources of international agencies, organizations and universities, and contacted experts in the field. Studies identified from rerunning searches in 2020 are under 'Studies awaiting classification.'

SELECTION CRITERIA

We included randomized or non-randomized trials, controlled before-after studies, or interrupted time series studies conducted in LMICs (as defined by the World Bank in 2018). P4P refers to the transfer of money or material goods conditional on taking a measurable action or achieving a predetermined performance target. To be included, a study had to report at least one of the following outcomes: patient health outcomes, changes in targeted measures of provider performance (such as the delivery of healthcare services), unintended effects, or changes in resource use.

DATA COLLECTION AND ANALYSIS

We extracted data as per original review protocol and narratively synthesised findings. We used standard methodological procedures expected by Cochrane. Given diversity and variability in intervention types, patient populations, analyses and outcome reporting, we deemed meta-analysis inappropriate. We noted the range of effects associated with P4P against each outcome of interest. Based on intervention descriptions provided in documents, we classified design schemes and explored variation in effect by scheme design.

MAIN RESULTS

We included 59 studies: controlled before-after studies (19), non-randomized (16) or cluster randomized trials (14);  and interrupted time-series studies (9). One study included both an interrupted time series and a controlled before-after study. Studies focused on a wide range of P4P interventions, including target payments and payment for outputs as modified by quality (or quality and equity assessments). Only one study assessed results-based aid. Many schemes were funded by national governments (23 studies) with the World Bank funding most externally funded schemes (11 studies). Targeted services varied; however, most interventions focused on reproductive, maternal and child health indicators. Participants were predominantly located in public or in a mix of public, non-governmental and faith-based facilities (54 studies). P4P was assessed predominantly at health facility level, though districts and other levels were also involved. Most studies assessed the effects of P4P against a status quo control (49 studies); however, some studies assessed effects against comparator interventions (predominantly enhanced financing intended to match P4P funds (17 studies)). Four studies reported intervention effects against both comparator and status quo. Controlled before-after studies were at higher risk of bias than other study designs. However, some randomised trials were also downgraded due to risk of bias. The interrupted time-series studies provided insufficient information on other concurrent changes in the study context. P4P compared to a status quo control For health services that are specifically targeted, P4P may slightly improve health outcomes (low certainty evidence), but few studies assessed this. P4P may also improve service quality overall (low certainty evidence); and probably increases the availability of health workers, medicines and well-functioning infrastructure and equipment (moderate certainty evidence). P4P may have mixed effects on the delivery and use of services (low certainty evidence) and may have few or no distorting unintended effects on outcomes that were not targeted (low-certainty evidence), but few studies assessed these. For secondary outcomes, P4P may make little or no difference to provider absenteeism, motivation or satisfaction (low certainty evidence); but may improve patient satisfaction and acceptability (low certainty evidence); and may positively affect facility managerial autonomy (low certainty evidence). P4P probably makes little to no difference to management quality or facility governance (low certainty evidence). Impacts on equity were mixed (low certainty evidence). For health services that are untargeted, P4P probably improves some health outcomes (moderate certainty evidence); may improve the delivery, use and quality of some health services but may make little or no difference to others (low certainty evidence); and may have few or no distorting unintended effects (low certainty evidence). The effects of P4P on the availability of medicines and other resources are uncertain (very low certainty evidence). P4P compared to other strategies For health outcomes and services that are specifically targeted, P4P may make little or no difference to health outcomes (low certainty evidence), but few studies assessed this. P4P may improve service quality (low certainty evidence); and may have mixed effects on the delivery and use of health services and on the availability of equipment and medicines (low certainty evidence). For health outcomes and services that are untargeted, P4P may make little or no difference to health outcomes and to the delivery and use of health services (low certainty evidence). The effects of P4P on service quality, resource availability and unintended effects are uncertain (very low certainty evidence). Findings of subgroup analyses Results-based aid, and schemes using payment per output adjusted for service quality, appeared to yield the greatest positive effects on outcomes. However, only one study evaluated results-based aid, so the effects may be spurious. Overall, schemes adjusting both for quality of service and rewarding equitable delivery of services appeared to perform best in relation to service utilization outcomes.

AUTHORS' CONCLUSIONS

The evidence base on the impacts of P4P schemes has grown considerably, with study quality gradually increasing. P4P schemes may have mixed effects on outcomes of interest, and there is high heterogeneity in the types of schemes implemented and evaluations conducted. P4P is not a uniform intervention, but rather a range of approaches. Its effects depend on the interaction of several variables, including the design of the intervention (e.g., who receives payments ), the amount of additional funding,  ancillary components (such as technical support) and contextual factors (including organizational context).

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 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).

A realist review to assess for whom, under what conditions and how pay for performance programmes work in low- and middle-income countries

Pay for performance (P4P) programmes are popular health system-focused interventions aiming to improve health outcomes in low-and middle-income countries (LMICs). This realist review aims to understand how, why and under what circumstance P4P works in LMICs.We systematically searched peer-reviewed and grey literature databases, and examined the mechanisms underpinning P4P effects on: utilisation of services, patient satisfaction, provider productivity and broader health system, and contextual factors moderating these. This evidence was then used to construct a causal loop diagram.We included 112 records (19 grey literature; 93 peer-reviewed articles) assessing P4P schemes in 36 countries. Although we found mixed evidence of P4P's effects on identified outcomes, common pathways to improved outcomes include: community outreach; adherence to clinical guidelines, patient-provider interactions, patient trust, facility improvements, access to drugs and equipment, facility autonomy, and lower user fees. Contextual factors shaping the system response to P4P include: degree of facility autonomy, efficiency of banking, role of user charges in financing public services; staffing levels; staff training and motivation, quality of facility infrastructure and community social norms. Programme design features supporting or impeding health system effects of P4P included: scope of incentivised indicators, fairness and reach of incentives, timely payments and a supportive, robust verification system that does not overburden staff. Facility bonuses are a key element of P4P, but rely on provider autonomy for maximum effect. If health system inputs are vastly underperforming pre-P4P, they are unlikely to improve only due to P4P. This is the first realist review describing how and why P4P initiatives work (or fail) in different LMIC contexts by exploring the underlying mechanisms and contextual and programme design moderators. Future studies should systematically examine health system pathways to outcomes for P4P and other health system strengthening initiatives, and offer more understanding of how programme design shapes mechanisms and effects.

Pay-for-performance reduces bypassing of health facilities: Evidence from Tanzania

Many patients and expectant mothers in low-income countries bypass local health facilities in search of better-quality services. This study examines the impact of a payment-for-performance (P4P) scheme on bypassing practices among expectant women in Tanzania. We expect the P4P intervention to reduce incidences of bypassing by improving the quality of services in local health facilities, thereby reducing the incentive to migrate. We used a difference-in-difference regression model to assess the impact of P4P on bypassing after one year and after three years. In addition, we implemented a machine learning approach to identify factors that predict bypassing. Overall, 38% of women bypassed their local health service provider to deliver in another facility. Our analysis shows that the P4P scheme significantly reduced bypassing. On average, P4P reduced bypassing in the study area by 17% (8 percentage points) over three years. We also identified two main predictors of bypassing - facility type and the distance to the closest hospital. Women are more likely to bypass if their local facility is a dispensary instead of a hospital or a health center. Women are less likely to bypass if they live close to a hospital.

Pay for Performance: A Reflection on How a Global Perspective Could Enhance Policy and Research

Pay-for-performance (P4P) is the provision of financial incentives to healthcare providers based on pre-specified performance targets. P4P has been used as a policy tool to improve healthcare provision globally. However, researchers tend to cluster into those working on high or low- and middle-income countries (LMICs), with still limited knowledge exchange, potentially constraining opportunities for learning from across income settings. We reflect here on some commonalities and differences in the design of P4P schemes, research questions, methods and data across income settings. We highlight how a global perspective on knowledge synthesis could lead to innovations and further knowledge advancement.

Understanding efficiency and the effect of pay-for-performance across health facilities in Tanzania

BACKGROUND

Ensuring efficient use and allocation of limited resources is crucial to achieving the UHC goal. Performance-based financing that provides financial incentives for health providers reaching predefined targets would be expected to enhance technical efficiency across facilities by promoting an output-oriented payment system. However, there is no study which has systematically assessed efficiency scores across facilities before and after the introduction of pay-for-performance (P4P). This paper seeks to fill this knowledge gap.

METHODS

We used data of P4P evaluation related to healthcare inputs (staff, equipment, medicines) and outputs (outpatient consultations and institutional deliveries) from 75 health facilities implementing P4P in Pwani region, and 75 from comparison districts in Tanzania. We measured technical efficiency using Data Envelopment Analysis and obtained efficiency scores across facilities before and after P4P scheme. We analysed which factors influence technical efficiency by regressing the efficiency scores over a number of contextual factors. We also tested the impact of P4P on efficiency through a difference-in-differences regression analysis.

RESULTS

The overall technical efficiency scores ranged between 0.40 and 0.65 for hospitals and health centres, and around 0.20 for dispensaries. Only 21% of hospitals and health centres were efficient when outpatient consultations and deliveries were considered as output, and <3% out of all facilities were efficient when outpatient consultations only were considered as outputs. Higher efficiency scores were significantly associated with the level of care (hospital and health centre) and wealthier catchment populations. Despite no evidence of P4P effect on efficiency on average, P4P might have improved efficiency marginally among public facilities.

CONCLUSION

Most facilities were not operating at their full capacity indicating potential for improving resource usage. A better understanding of the production process at the facility level and of how different healthcare financing reforms affects efficiency is needed. Effective reforms should improve inputs, outputs but also efficiency.

At what cost is performance-based financing implemented? Novel evidence from Malawi

Our study estimated the full economic cost of implementing performance-based financing [PBF, the Support for Service Delivery Integration Performance-Based Incentives (SSDI-PBI) programme], as a means of first introducing strategic purchasing in a low-income setting, Malawi. Our analysis distinguished design from implementation costs and traces costs across personnel and non-personnel cost categories over the 2012-15 period. The full cost of the SSDI-PBI programme amounted to USD 3 402 187, equivalent to USD 6.46 per targeted beneficiary. The design phase accounted for about one-third (USD 1 161 332) of the total costs, while the incentives (USD 1 140 436) represented about one-third of the total cost of the intervention and about half the cost of the implementation phase. With a cost of USD 1 605 178, personnel costs represented the dominant cost category. Our study indicated that the introduction of PBF entailed consumption of a substantial amount of resources, hence representing an important opportunity cost for the health system.