User fee exemptions and excessive household spending for normal delivery in Burkina Faso: The need for careful implementation

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Study Justification:
This study aims to assess the impact of user fee exemptions on the total cost of giving birth in health centers in Burkina Faso. The study is motivated by the need to lower the country’s high maternal mortality and morbidity rates by reducing the financial barriers to accessing obstetric services and neonatal care. The study compares the costs of giving birth in health centers with partial fee exemptions to those with full fee exemptions, in order to evaluate the impact on additional out-of-pocket expenses.
Highlights:
– The study found that the elimination of fees for facility-based births benefits the poorest households the most.
– Women giving birth in health centers with full fee exemptions had significantly lower excessive medical expenses compared to those with partial fee exemptions.
– The study highlights the need for the government to remove all direct fees for obstetric and neonatal care to further reduce financial barriers to accessing healthcare services.
– The implementation process of fee exemptions must have a thorough monitoring system to reduce implementation gaps.
Recommendations:
– The government should remove all direct fees for obstetric and neonatal care to ensure that financial barriers do not prevent women from accessing healthcare services.
– A thorough monitoring system should be implemented to ensure the effective implementation of fee exemptions and reduce implementation gaps.
Key Role Players:
– Government of Burkina Faso: Responsible for implementing and monitoring the removal of direct fees for obstetric and neonatal care.
– Ministry of Health: Responsible for overseeing the implementation of fee exemptions and monitoring the impact on healthcare access and financial barriers.
– Non-Governmental Organizations (NGOs): NGOs like HELP can play a role in advocating for fee exemptions and supporting the implementation process.
Cost Items for Planning Recommendations:
– Monitoring system: Budget for developing and implementing a monitoring system to track the implementation of fee exemptions and assess their impact.
– Public awareness campaigns: Budget for raising awareness among the public about the removal of direct fees for obstetric and neonatal care.
– Training and capacity building: Budget for training healthcare providers and staff on the new fee exemption policies and procedures.
– Data collection and analysis: Budget for collecting and analyzing data on healthcare utilization, costs, and financial barriers to assess the effectiveness of fee exemptions.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is fairly strong, but there are some areas for improvement. The study design is a case-control study, which is a robust method for comparing groups. The sample size is also relatively large, with a total of 870 women. The study compares the total cost of giving birth in health centers with full fee exemption versus those with partial fee exemption. The results show that women in the full exemption health districts had lower excessive medical expenses compared to women in the partial exemption district. The conclusion suggests that eliminating fees for facility-based births benefits the poorest households. However, there are some limitations to consider. The abstract does not provide information on the representativeness of the sample or the generalizability of the findings. Additionally, the abstract does not mention any statistical analyses performed to support the results. To improve the evidence, future studies could include a more diverse and representative sample, conduct statistical analyses to support the findings, and provide information on the generalizability of the results.

Background: In 2006, the Parliament of Burkina Faso passed a policy to reduce the direct costs of obstetric services and neonatal care in the countrys health centres, aiming to lower the countrys high national maternal mortality and morbidity rates. Implementation was via a partial exemption covering 80% of the costs. In 2008 the German NGO HELP launched a pilot project in two health districts to eliminate the remaining 20% of user fees. Regardless of any exemptions, women giving birth in Burkina Fasos health centres face additional expenses that often represent an additional barrier to accessing health services. We compared the total cost of giving birth in health centres offering partial exemption versus those with full exemption to assess the impact on additional out-of-pocket fees. Methods. A case-control study was performed to compare medical expenses. Case subjects were women who gave birth in 12 health centres located in the Dori and Sebba districts, where HELP provided full fee exemption for obstetric services and neonatal care. Controls were from six health centres in the neighbouring Djibo district where a partial fee exemption was in place. A random sample of approximately 50 women per health centre was selected for a total of 870 women. Results: There was an implementation gap regarding the full exemption for obstetric services and neonatal care. Only 1.1% of the sample from Sebba but 17.5% of the group from Dori had excessive spending on birth related costs, indicating that women who delivered in Sebba were much less exposed to excessive medical expenses than women from Dori. Additional out-of-pocket fees in the full exemption health districts took into account household ability to pay, with poorer women generally paying less. Conclusions: We found that the elimination of fees for facility-based births benefits especially the poorest households. The existence of excessive spending related to direct costs of giving birth is of concern, making it urgent for the government to remove all direct fees for obstetric and neonatal care. However, the policy of completely abolishing user fees is insufficient; the implementation process must have a thorough monitoring system to reduce implementation gaps. © 2012 Ben Ameur et al.; licensee BioMed Central Ltd.

In this study, researchers are analysing the results of a natural experiment. A natural experiment is an empirical study in which the experimental conditions are determined by nature or by other factors out of the control of the evaluators [11]. The study took place in the Sahel Region of Burkina Faso about 300 km from the capital Ouagadougou, which has specific geographical and cultural characteristics. This region has four districts: Dori, Sebba, Djibo and Gorom-Gorom. The first two represent the only districts where the NGO intervened during the study; the evaluators had no control in selecting these districts for the pilot project. In order to select a third district for comparison with Dori and Sebba we examined the level of facility-based delivery (expressed as a percentage of all institutional deliveries) in Gorom-Gorom and Djibo. According to Annuaire statistique 2009 (Ministère de la santé – Secrétariat général, Direction générale de l’information et des statistiques sanitaires), 22% of institutional deliveries in Gorom-Gorom had skilled care, while this proportion was 52.4% in Djibo. Djibo was chosen as the comparison district because its percentage of skilled care was much closer to the proportions observed in the Dori and Sebba districts. Dori and Sebba served as the case districts with a full user fee exemption provided by a pilot project of the NGO HELP, and Djibo as the control district with the government-mandated partial user fee exemption. The table below describes the main characteristics of the three districts (Table ​(Table1).1). Districts characteristics (source: Plans d’Action 2010 des Districts Sanitaires de la Région du Sahel) (*) The official cost of delivery corresponds to « acts, medicines and consumables, and observation » (Ministère de la santé, 2006a). (**) Annuaire statistique 2008, 2009, 2010, 2011 Ministère de la santé – Secrétariat général, Direction générale de l’information et des statistiques sanitaires. NGO= Non government organization. CSPS= Centre de santé et de protection sociale, i.e. “first line health centre”. F CFA= Franc de la Communauté Financière Africaine. « facility-based delivery » refers to facility-based childbirths assisted by professionals. According to the Annuaire Statistique where the indicator comes from, it is called in French: Accouchements assistés par du personnel de santé. In every district, six health centres were selected for a total of 18 health centres (30% of the total centres). This selection sample was based on two previous studies in the region that reflected situational diversity [12][13]. Only two exceptions were made because of access constraints due to the rainy season at the time of data collection. For these two cases, two other CSPS with similar characteristics were chosen. The selection sample includes only women who gave birth in health centres and had no complications, as the study focused on expenses related to an institutional birth. In the full exemption districts (Dori and Sebba), the study population was women who gave birth in health centres two months prior to the start of the study. In the partial exemption district (Djibo), the study population was women who gave birth in health facilities in the six months prior to the start of the study. This longer recall period was needed to gather a large enough sample size because the number of women using facility-based services in that district was very low. At the CSPS level, the sampling was done using maternal registers available in each health centre. A random sample of approximately 50 women per health centre was selected from the registers. The survey size was limited to 50 per health centre due to the limited financial resources available for the study. In Dori and Sebba it was possible to achieve this target. However, in Djibo, the low rate of facility-based births (2010) together with an exceptional number of emigrants made it more difficult to reach our targeted sample size. Thus, the final sample in this district was 270 women rather than 300. The total sample was 870 women who gave birth in 18 health centres. Twenty-one women were excluded from the original sample as they were found to have given birth at home or before reaching the health centre (see Table ​Table22). Sampling (1) Source: maternal registers available in health centres Period of delivery: *March 2010- May 2010; **December 2009- May 2010. Survey instruments were developed based on a similar survey conducted in another district of Burkina Faso in 2006 by IMMPACT researchers and in 2010 by VR and AB in Ouargaye [14]. The instruments measure medical household expenditures related to institutional birth at the point of use. The medical expenditures include: user fees, drugs and consumables, laboratory fees, and cleaning products. Traditional poverty measurements based on consumption or incomes were particularly difficult in the sample district settings. Instead, household characteristics and asset ownership are widely used as indicators of wealth [15]. Consequently, a series of questions related to the specific characteristics of rural households in Burkina Faso was used to gauge household economic status. Questionnaires and consent forms were developed in French and then translated into the local language, Peulh, following the double-translation method. The instruments were pretested in the Dori district in a CSPS not included in the sample. The pre-test assessed the validity of the data-collection instruments and procedures, as well as the sampling procedures. This process identified content and logistical issues that led to revising some of the questions and the data collection process. Sahel Regional Authorities approved the survey. Fieldwork was conducted over a five-week period starting in May 2010 by six trained local interviewers fluent in Peulh and French. Each interviewer interviewed +/− 50 women over a ten-day period. The household survey questionnaires were administered to all study participants. Respondents gave verbal consent to the interview and were assured of data confidentiality. Two research coordinators carefully supervised data collection during the entire fieldwork. Data was input and validation was performed with the double entry method using Epi Data software, and the data set was then converted to SPSS 17 and STATA 11 for analysis. Analysis of variance (ANOVA) was performed to compute means of medical expenses and compare them between districts and other explanatory variables (education, distance, etc.). A poverty proxy was developed using household data indicators. Through Principal Components Analysis (PCA), households/women were assigned to poverty quintiles [16]. This allows a classification of households from the poorest (rated as 1) to the least poor (rated as 5) in order to show socio-economic differences. As we did not have information about household consumption and/or income, it is not possible to measure catastrophic expenditures related to births health centres. Instead, we relied upon the concept of “high delivery health care spending per household”, equivalent to “excessive spending per household”. It was estimated by analyzing the expenditures dispersion within the two samples (full exemption vs partial exemption group). By using the statistical outlier method (or Tukey method) it was possible to identify the value threshold. Supposing Q1 and Q3 are respectively the first and third quartiles of the distribution of delivery health expenditure of the sample, then a high-spending or outlier household within the group is one for which the value of delivery health expenditure is greater than Q3+k*(Q3-Q1), where k is a constant (varied from 0.5, 1 or 1.5). Having three values for k, rather than one, allows more flexibility in defining the outlier households at different expenditure cut-off points and permits testing the sensitivity of the results. In fact, the smaller k is, the stricter is the approach [17]. The Ministry of Health of Burkina Faso examined and approved the ethics component of this research project and authorized the study. Ethical approval was given prior to data collection.

Based on the information provided, here are some potential innovations that could be recommended to improve access to maternal health:

1. Expand user fee exemptions: The study found that eliminating user fees for facility-based births benefited the poorest households. To further improve access, the government could consider expanding the exemption to cover all direct fees for obstetric and neonatal care.

2. Strengthen monitoring systems: The study highlighted an implementation gap in the full fee exemption districts. To ensure effective implementation, it is important to have a thorough monitoring system in place. This could involve regular assessments of the exemption program, tracking the number of women benefiting from the exemption, and addressing any implementation challenges.

3. Improve availability of skilled care: The study mentioned that the percentage of facility-based deliveries with skilled care varied across districts. To improve access to maternal health, efforts should be made to increase the availability of skilled healthcare providers in all districts, ensuring that women have access to quality care during childbirth.

4. Address additional out-of-pocket expenses: The study found that women still faced additional expenses when giving birth in health centers, even with fee exemptions. To improve access, it is important to address these additional out-of-pocket expenses, which can act as barriers to accessing healthcare. This could involve providing financial support or subsidies to cover the cost of drugs, consumables, and other related expenses.

5. Increase awareness and education: To improve access to maternal health, it is important to increase awareness and education among women and communities. This could involve conducting awareness campaigns to inform women about the benefits of facility-based births, the availability of fee exemptions, and the importance of seeking timely and appropriate healthcare during pregnancy and childbirth.

These recommendations aim to address the barriers identified in the study and improve access to maternal health services in Burkina Faso.
AI Innovations Description
The recommendation from this study to improve access to maternal health is to remove all direct fees for obstetric and neonatal care. The study found that the elimination of fees for facility-based births benefited the poorest households the most. However, it also highlighted the need for a thorough monitoring system to reduce implementation gaps and ensure that the policy of fee exemption is effectively implemented. By removing all direct fees and closely monitoring the implementation process, access to maternal health services can be improved, particularly for the most vulnerable populations.
AI Innovations Methodology
Based on the information provided, here are some potential recommendations to improve access to maternal health:

1. Strengthen implementation of user fee exemptions: The study found that the elimination of fees for facility-based births benefited the poorest households. To further improve access, it is recommended to fully implement the policy of completely abolishing user fees for obstetric and neonatal care. This can be done by ensuring thorough monitoring and evaluation systems are in place to reduce implementation gaps.

2. Increase availability of skilled care: The study mentioned that the percentage of facility-based deliveries with skilled care varied across districts. To improve access to maternal health, it is important to increase the availability of skilled care in all districts. This can be achieved by training and deploying more skilled healthcare professionals, particularly in areas with low access to healthcare services.

3. Address additional out-of-pocket expenses: The study highlighted that women giving birth in health centers in Burkina Faso face additional expenses that act as barriers to accessing health services. It is recommended to address these additional out-of-pocket expenses by providing financial support or subsidies to cover the costs of obstetric services and neonatal care. This can help reduce the financial burden on women and their families.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Define the indicators: Identify key indicators to measure access to maternal health, such as the percentage of facility-based deliveries, maternal mortality rate, and out-of-pocket expenses for maternal health services.

2. Collect baseline data: Gather data on the current status of access to maternal health services, including the indicators identified in step 1. This can be done through surveys, interviews, and analysis of existing data sources.

3. Develop a simulation model: Create a simulation model that incorporates the recommendations mentioned above. This model should consider factors such as population demographics, healthcare infrastructure, and financial resources available for implementation.

4. Input data and run simulations: Input the baseline data into the simulation model and run multiple simulations to assess the potential impact of the recommendations on access to maternal health. This can involve varying parameters such as the coverage of user fee exemptions, availability of skilled care, and financial support for additional expenses.

5. Analyze results: Analyze the results of the simulations to determine the potential impact of the recommendations on access to maternal health. This can include assessing changes in the indicators identified in step 1 and identifying any trade-offs or unintended consequences.

6. Refine and iterate: Based on the analysis of the simulation results, refine the recommendations and simulation model as needed. Repeat the simulation process to further assess the potential impact and make adjustments as necessary.

By following this methodology, policymakers and stakeholders can gain insights into the potential effects of different recommendations on improving access to maternal health. This can inform decision-making and help prioritize interventions to achieve better maternal health outcomes.

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