Costing Curative Outpatient Care for the Poorest in Burkina Faso: Informing Universal Health Coverage and Leaving No One Behind

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Methods We conducted a micro-costing study in Burkina Faso to estimate the economic costs of providing curative outpatient healthcare services to the poorest at first-level healthcare facilities, considering a health system perspective. We measured the consumption of capital costs (building and equipment) using survey data from 32 primary health facilities and recurrent costs (drugs and consumables) from medical records of 1380 poor patients in Diébougou district. These individuals were specifically targeted and exempted from user fees through a community-based targeting approach. We obtained unit costs from official price lists, pharmacy registries, and expert interviews. Furthermore, we calculated the national budget for providing curative care services to the exempted poorest based on the average cost per first-level consultation. Results The estimated capital and recurrent costs of providing curative care services to the poorest ranged between USD 0.59 - USD 0.61 and USD 2.58 - USD 5.00, respectively. The total cost ranged between USD 3.17 - USD 5.61 per first-level consultation. Providing curative care to the bottom 20% of the population, assuming 0.25 healthcare contacts per person per year, would result in an annual expense ranging from USD 2.77M to USD 5.38M (0.74%-1.43% of the healthcare budget in 2019). With 2 healthcare contacts per person per year, costs increase to USD 22.19M to USD 43.05M (5.91%-11.45% of the healthcare budget). Conclusion Our study's cost data can inform policies aimed at expanding access to curative care for the poorest in Burkina Faso, contributing to the goals of universal health coverage and leaving no one behind. Further research is needed to enhance cost estimation and budgeting for higher-level care in the country. Figures Figure 1 1. Introduction Universal Health Coverage (UHC), a critical component of the United Nations' third Sustainable Development Goal, aims to provide equitable access to quality health services for everyone without financial hardship ( 1 ). Despite global efforts to expand access to healthcare, over 400 million poor and vulnerable people in low- and lower-middle-income countries (LMICs) ( 2 ) still face persistent and severe health disparities due to limited access to essential health services ( 3 ). To ensure that existing inequities are taken into account in the design of health policies, UHC embraces the Leaving No One Behind (LNOB) principle ( 4 ) prioritizing the expansion and improvement of effective service delivery models for the poorest. In LMICs, providing quality healthcare services to the poorest populations is challenging due to their remote locations, limited health literacy, and complex health needs ( 5 ). As a result, delivering healthcare services to this group may involve higher costs compared with the general population. Still, there is a lack of accurate costing studies addressing the specific needs of the poorest individuals ( 6 ). In turn, this lack of accurate cost information represents a real barrier to the design and implementation of programs aimed at enhancing access to care for this specific segment of the population, such as targeted publicly-funded health insurance schemes or free health care policies. Existing literature on the costs of healthcare services in LMICs mainly focuses on the general population, specific diseases, or other specific populations ( 7 – 10 ), leaving a significant research gap regarding the costs of services for the poorest individuals. Burkina Faso, a country committed to improving healthcare access for its poorest populations, has implemented various health financing reforms, including community or occupational based health insurance and user fee removal for pregnant women and children under the age of five ( 11 ). Notably, the Régime d'Assurance Maladie Universelle scheme (RAMU), stands out as a national health insurance program enacted into law on 5th September 2015 ( 12 ) to provide quality health services to all, with a particular emphasis on the poorest and most vulnerable populations. By aligning with the policy objectives of UHC and LNOB, Burkina Faso aims to eliminate financial barriers and enhance health outcomes for all its citizens. However, the aforementioned challenges persist in effectively targeting and extending coverage to all poor and informal workers ( 6 , 12 ), necessitating a closer examination of the economic costs associated with providing curative outpatient care to the poorest population in Burkina Faso at first-level healthcare facilities. Therefore, we conducted a comprehensive micro-costing study adopting a health system perspective to provide decision-makers with crucial cost data to inform the budgeting and implementation of policies to facilitate free access to care for the poorest. 2. Methods 2.1 Study setting Burkina Faso is located in West Africa and had a population of 21.51 million in 2021. The country is positioned among the world's poorest nations. Over 40% of its population lives in poverty, surviving on less than USD 1.90 a day ( 13 ). This study specifically examines the so called ‘ultra-poor’ ( 14 ), who are in an advanced state of poverty and lack basic necessities, such as food, shelter, and sanitation, as well as the financial and social resources necessary to access and pay for essential healthcare services ( 15 – 17 ). To enhance readability, the term 'ultra-poor' is interchangeably referred to as the 'poorest' throughout this manuscript. The unique setting for this study is the Diébougou health district, where the introduction of the Performance-based Financing (PBF) intervention, combined with a community-based targeting and exemption mechanism for the poorest in 2016, provided a valuable opportunity to distinguish medical records of the poorest from non-poor patients ( 18 ). The PBF initiative not only aimed to improve healthcare quality and accessibility, but also introduced mechanisms to identify and exempt the poorest from health care payments ( 18 ), the key population of this study. Within Burkina Faso, primary level healthcare services are provided at Centre de Santé et de Promotion Sociale (CSPS) and Centre Médical avec Antenne Chirurgicale (CMA), with each CSPS serving approximately 8,000–15,000 individuals and covering 5 to 23 villages. This study focuses on first-level services offered by CSPS, primarily located in the rural and peripheral areas of Burkina Faso ( 19 ). 2.2 Study design and overall approach To provide policy makers with relevant cost information, we adopted a health system perspective and employed two different approaches to address our study objectives. Firstly, we conducted a micro-costing study using a bottom-up approach to estimate the average cost of providing a curative outpatient consultation at the CSPS level (first-level of services) to the exempted poorest. The ability to distinguish medical records of the poorest from non-poor patients was enabled by the prior implementation of the PBF intervention in the Diébougou district in 2016. Secondly, we used the estimated cost per consultation to assess the budget impact of providing first-level curative outpatient care to the poorest across the country. The base year of the cost analysis is 2019, in order to align with the research project's deliverables. To account for inflation, we adjusted all costs incurred before 2019 using the national consumer price index (CPI) ( 20 ). We multiplied the cost incurred in 2016 by the ratio of the relevant CPI (CPI 2019 = 108.36 / CPI 2016 = 108.23). We obtained Burkina Faso's annual CPI from the International Monetary Fund, International Financial Statistics ( 21 ). We converted values from FCFA to USD using the average exchange rate for 2019 (1 USD = FCFA 585.91) ( 22 ). We used Microsoft Excel 2019 (Microsoft, Redmond, WA) to operationalize the model. 2.3 Identification of cost categories and measurement of resource consumption We identified two cost categories for the study: capital costs and recurrent costs. Capital costs included building and equipment costs, while recurrent costs included consultation fees, drugs, and human resources. Local experts were consulted to identify these cost categories. The quantity of rapid tests and the use of test strips was minimal and thus excluded. Resource consumption for recurrent costs and capital costs was measured using patient registries and a health facility survey, respectively. Patient registries from 15 CSPS in the Diébougou district were used from January to December 2016 in order to estimate the recurrent resources consumed by the poorest. Ten enumerators collected the paper-based information and transferred it to Excel. In total, 1380 patient records were used after excluding children below five years (who were covered by the national free health care policy for the pregnant women and children under five) and records with missing values. We conducted an additional data collection in August 2020 to obtain unit cost information for the drugs used in the medical records. We created a drug list matrix based on the entries in the records, and employing a trained enumerator to collect the unit cost information from pharmacy registries. For capital costs, we utilized a health facility survey conducted between March and May 2018 as part of another research project, which collected information on capital costs and variable overheads from 32 CSPS distributed across four regions (North, Hauts-Bassins, Est, and Centre South) by 20 trained enumerators. Paper-based responses were transferred to Excel. We extracted information on equipment for this study. 2.4 Valuation of costs We used a standardized approach to value costs by relating the unit cost of each resource to the quantity measured in the previous step. We obtained unit cost information from various sources. Recurrent costs were estimated from the fee structure of healthcare facilities for consultation services, while average drug prices among adults were derived from pharmacy registries. For human resource costs not covered by the consultation fees, we used the human capital approach, extracting salary information for nurses, midwives, and mobile health workers from data collected within the PBF end-line impact evaluation framework in the Diébougou district. The salaries of doctors and pharmacists were adopted from literature ( 23 ), based on the average gross monthly salary, with a working month consisting of 22 working days and eight hours/day. To estimate building costs, we interviewed Ministry of Health experts to determine the average cost of building a CSPS (104 million FCFA without equipment) and the useful lifespan of the CSPS (25 years). We derived the average size of a CSPS (500 sq m) from construction plans and used the square meters occupied for consultations (245 sq m) from the construction plan to allocate the building cost for consultation service (104 million FCFA * 245/500). For equipment, we estimated the unit costs and useful lifespan by triangulating information from two ministry structures: Direction des Infrastructures, de l'Equipement et de la Maintenance and Société de Gestion de l'Equipement et de la Maintenance Biomédicale - Management Company of Biomedical Equipment and Maintenance (SOGEMAB). Straight-line depreciation was applied by dividing the item's value by its useful lifespan. For equipment with a defined value below FCFA 15,000 (USD 25.50), we used the approach taken by Flessa & Marshall (2009) ( 24 ) and depreciated them within a year. 2.5 Cost data analysis To analyze the cost of a first-level curative outpatient consultation, we differentiated between capital and recurrent costs. Valuing these costs involved combining information on resource consumption with the unit prices described earlier ( 25 ). To account for indirect administrative expenses, we applied an average overhead rate of 20% to the total fixed and variable costs. This approach is consistent with the guidelines outlined in the International Standard Cost Model Manual ( 26 ). We estimated the average building and equipment costs per consultation by dividing the total building and equipment costs by the total number of consultations. The average cost per consultation was then calculated as the sum of the average recurrent costs for each cost item (human resource, consultation, drugs, and variable overheads) and the average capital cost. We conducted a two-way sensitivity analysis to account for the uncertainty surrounding the drug and overhead estimates. Specifically, we applied the mean drug expenditure of FCFA 657.68 plus one standard deviation (FCFA 545.36) and two standard deviations (FCFA 1,090.72). In addition, we increased the overhead rate for capital and recurrent costs from 20–25%. This approach allowed us to obtain a comprehensive understanding of the cost and to identify the key cost drivers. 2.6 Budget impact analysis (BIA) We conducted a BIA to estimate the financial impact of providing first-level curative healthcare services to poorest nationwide on the Burkinabe healthcare budget. For this analysis we focused only on recurrent costs. If the government of Burkina Faso were to provide first-level curative services for the poorest without charging user fees, they would need to plan a budget to cover the recurrent costs for the health facilities. To guide our analysis, we developed a model framework following the guidelines on BIA for healthcare interventions, depicted in (Fig. 1 ) . We used a cost-calculator model to estimate the annual costs, which multiplies the annual service volume by its average costs. This figure illustrates the conceptual framework developed for the BIA of providing first−level curative outpatient healthcare services to the poorest in Burkina Faso. The scenario names are shown in dark grey, and the green box indicates where each scenario differs from the base case. The white box indicates the economic endpoints. Utilization rates were estimated based on data from the poorest in Diébougou district, with an average of 0.25 healthcare contacts per person per year in the base case, as determined by the authors. This framework allowed us to assess the financial impact of different scenarios and identify those that would have the greatest impact on the healthcare budget. 2.7 Model Inputs The model used four inputs: Eligible Population The model population consisted of 6%, 9%, and 20% of the total population in Burkina Faso, assumed to be eligible for targeted user fee exemptions. The 6% threshold was used as a community threshold, and the 9% threshold illustrated the extremely poor according to the United Nations Development Programme ( 27 ). The 20% threshold reflected the concept of the "bottom 20% of the population," the poorest income quintile, as measured by income inequality. Time frame The time span of one year was adopted, in line with the period of the national healthcare budget of Burkina Faso. Uptake of the intervention The poorest in the Diébougou district had, on average, 0.25 healthcare contacts per person per year, based on the estimates derived from above. The context-specific utilization rate was doubled and quadrupled to reflect a likely increase in the intervention uptake in the absence of a specific global recommendation for the number of outpatient care contacts per person per year. Costs The base case and scenario analysis inputs originated from the cost assessment described above. 2.8 Model output The primary output of interest was the total annual recurrent cost. 2.9 Scenario analysis We conducted medium and high assumption scenarios reflecting alternative values for drugs and overheads, while also considering different thresholds of population coverage (6%, 9%, and 20% of the population) and different utilization rates among the targeted poorest (0.25, 0.50, and 2.00 healthcare contacts per capita per person per year) (Annex I and II). 2.10 Ethical considerations Ethical clearance was granted by the Comité National d’Éthique pour la Recherche en Santé in Burkina Faso (Decision No. 2019-01-004). No ethical clearance for this study was required in Germany since the study relied exclusively on secondary fully-anonymized data. 3. Findings The study estimated the average cost per first-level curative outpatient consultation for the poorest in Burkina Faso to be USD 3.17 ( Table 1 ). Recurrent costs constituted 81.39% of the total cost, with drugs and human resources being the two largest cost drivers at 35.33% and 21.77%, respectively. Capital costs accounted for the remaining 18.61% of the total cost. Scenario analyses assessed the impact of varying drug costs and overhead percentages on the total average cost. Scenario I, which increased the drug cost from USD 1.12 to USD 2.05 and the overhead percentage from 20–25%, increased the total average cost from USD 3.17 to USD 4.45. Scenario II, which increased the drug cost from USD 1.12 to USD 2.97 and the overhead percentage from 20–25%, further increased the total average cost from USD 3.17 to USD 5.61. Table 1 The average cost of providing one first-level curative outpatient consultation to the poorest in Burkina Faso. Base calculation Results Scenario analysis Time Horizon 1 YEAR I II Cost per consultation in USD I. Capital costs Building costs 0.26 USD 0.26 USD 0.26 USD Equipment costs 0.23 USD 0.23 USD 0.23 USD Fixed Overheads 20% 0.10 USD 0.12 USD 0.12 USD Total Capital Cost 0.59 USD 0.61 USD 0.61 USD II. Recurrent costs Cost per consultation in USD Consultation costs 0.34 USD 0.34 USD 0.34 USD Drug costs 1.12 USD 2.05 USD 2.97 USD Human resource costs 0.69 USD 0.69 USD 0.69 USD Variable overheads 20% 0.43 USD 0.76 USD 1.00 USD TOTAL Recurrent cost 2.58 USD 3.84 USD 5.00 USD GRAND TOTAL CAPITAL AND RECURRENT COST PER CONSULTATION 3.17 USD 4.45 USD 5.61 USD Table 2 shows the recurrent costs and budget impact of providing curative outpatient healthcare services to the poorest in Burkina Faso. Costs vary based on the population targeted and the expected number of curative contacts. For example, targeting 6% of the population with 0.25 curative contacts per capita would cost USD 832,225.81 annually, equivalent to 0.22% of the healthcare budget. Increasing the target population to 20% with 0.50 curative contacts would cost USD 5,548,172, representing 1.48% of the healthcare budget. Three scenarios are presented with different targeting thresholds and utilization rates, ranging from USD 832,225.81 to USD 22,192,688.35 representing 0.22–5.91% of the healthcare budget, respectively. Table 2 Cost and budget impact estimates applying different targeting thresholds and population coverage. Cost category Base case: Targeting threshold 6% of the population:1,290,611 % of the healthcare budget Medium assumption scenario: Targeting threshold 9% of the population: 1,935,916 % of the healthcare budget High assumption scenario Targeting threshold 20% of the population: 4,302,036 % of the healthcare budget Scenario 1 Utilization 0.25 Consultation costs USD 109,833.69 USD 164,750.54 USD 366,112.31 Drug costs USD 361,177.91 USD 541,766.87 USD 1,203,926.37 Human resources USD 222,509.91 USD 333,764.86 USD 741,699.70 Variable overheads 20% USD 138,704.30 USD 208,056.45 USD 462,347.67 TOTAL RECURRENT COST IN USD USD 832,225.81 0.22 USD 1,248,338.72 0.33 USD 2,774,086.04 0.74 Scenario 2: Utilization 0.50 Consultation costs USD 219,667.38 USD 329,501.07 USD 732,224.61 Drug costs USD 722,355.82 USD 1,083,533.73 USD 2,407,852.74 Human resources USD 445,019.82 USD 667,529.73 USD 1,483,399.39 Variable overheads 20% USD 277,408.60 USD 416,112.91 USD 924,695.35 TOTAL RECURRENT COST IN USD USD 1,664,451.63 0.44 USD 2,496,677.44 0.66 USD 5,548,172.09 1.48 Scenario 3: Utilization 2.00 Consultation costs USD 878,669.53 USD 1,318,004.30 USD 2,928,898.44 Drug costs USD 2,889,423.28 USD 4,334,134.93 USD 9,631,410.95 Human resources USD 1,780,079.27 USD 2,670,118.90 USD 5,933,597.56 Variable overheads 20% USD 1,109,634.42 USD 1,664,451.63 USD 3,698,781.39 TOTAL RECURRENT COST IN USD USD 6,657,806.50 1.77 USD 9,986,709.76 2.66 USD 22,192,688.35 5.91 4. Discussion 4.1 Insights into the cost of providing curative outpatient services at first-level healthcare facilities to the poorest and policy implications Our study estimates the average cost of providing curative outpatient services at first level healthcare facilities to Burkina Faso's poorest population, ranging from USD 3.17 to USD 5.61 per consultation. These cost estimates offer policymakers valuable insights, particularly when it comes to setting prices for healthcare services covered by free healthcare policies for the poorest supported by the government through the RAMU. Notably, the cost estimate, while specific to curative care, underscores the broader need for accurate financial planning within the healthcare system. It is this accurate financial planning that plays a vital role in ensuring adequate resources for the successful implementation of the free health care for the poor and achieving the global goal of strengthening health systems for UHC, as emphasized in the Declaration of Astana. Moreover, recognizing the importance of curative outpatient services at first-level facilities as part of primary healthcare (PHC) ( 28 ) further emphasizes the significance of our cost estimate. Such services represent the first point of care and are instrumental in the pursuit of comprehensive healthcare for all. Beyond the local context, the involvement of organizations such as the World Bank in discussions about implementing flat-rate purchases for free healthcare policies ( 29 , 30 ) underlines the practical relevance of our findings and illustrates how these findings can help shape healthcare policy and financial planning in the region. Our cost estimates align with earlier studies in Burkina Faso for the general population, underscoring a potential stability in healthcare costs even considering the considerable time elapsed since those studies were conducted ( 24 , 31 ). Notably, Flessa & Marschall (2009) estimated the average cost per consultation at USD 2.94 ( 24 ), while Mugisha et al. (2002) evaluated outpatient services for the rural population in Nouna at USD 3.08 ( 31 ), which is almost matching our lowest estimate of USD 3.17. The consistency of these figures over time prompts reflection on how inflation has seemingly had minimal impact on healthcare costs within Burkina Faso's healthcare system. However, a study in rural Ghana ( 32 ) revealed a notably higher median cost of USD 8.79 for outpatient department attendance, likely linked to economic disparities. Ghana's comparatively higher income level, relative to Burkina Faso, suggests a plausible influence on healthcare expenses. Drug costs accounted for 35.33% of the total cost, and human resources at 21.77%. Our estimate differs from prior studies, where drug costs were the second-largest driver ( 31 , 32 ), but it aligns with our initial expectations due to the complex morbidity profile of the poorest population seeking late-stage care requiring complex medication ( 33 ). To enhance access to quality healthcare, controlling drug costs and improving procurement processes are crucial ( 34 ). While not directly derived from our cost analysis, the role of community health workers emerges as a complementary strategy, especially relevant in the context of our findings. By providing first-level services, particularly in underserved rural areas ( 35 ), community health workers can alleviate the burden on healthcare facilities, indirectly affecting the cost structure by reducing the demand for more expensive, late-stage treatments. Their involvement can improve medication adherence among the poorest populations, potentially mitigating the need for complex and costly care. This indirect link suggests that incorporating community health workers into healthcare delivery models could enhance the overall cost-effectiveness and efficiency of care for these vulnerable groups. 4.2 Insights into the budget-impact and policy implications The findings indicate that across all hypothetical budget scenarios (I-II, as detailed in the Annex), providing free curative outpatient care at first-level healthcare facilities for up to 20% of the population would result in a healthcare budget impact between 0.22 and 11.45 percent. This suggests that providing these services to the bottom 20% of the population could be financially viable without imposing a substantial burden on the government's budget. While Burkina Faso allocated 46% of its government health spending to PHC in 2020 ( 36 ), a relatively high share compared with neighboring countries (such as Côte d'Ivoire 38%, Niger 36% and Benin 13% ( 36 )) the need for further investment and resource allocation efficiency is evident. This becomes particularly important when considering that 31% of PHC funding in Burkina Faso relies on out-of-pocket payments and 22% on external sources ( 36 ). Policymakers should explore fund reallocation and alternative financing sources ( 37 ), bearing in mind the challenges posed by the current economic and security context ( 12 ) as they work to progress toward UHC and ensure equitable healthcare access for the most vulnerable populations. Policymakers may also need to consider implementing RAMU gradually, increasing coverage step by step, as done in other countries with successful fee removal policies, such as Ghana, Colombia, Mexico, and Thailand ( 38 ). Furthermore, our study did not consider the cost of identifying the poorest, estimated at 5.73 USD per beneficiary ( 39 ), which can significantly impact the financial costs of the policy and should be factored in to ensure its sustainability and affordability. With the ongoing implementation of RAMU in Burkina Faso ( 6 ), the findings of our study hold significant relevance. Policymakers can use our cost estimates and budget impact analysis to guide budget planning, policy decisions, and the pricing of services. Addressing financial implications, cost drivers, and cost-effectiveness strategies will support the successful and sustainable implementation of RAMU and advance the goals of UHC and LNOB in Burkina Faso and similar resource constrained settings. 5. Methodological consideration Our study has limitations that must be considered. Firstly, the cost and budget estimates were derived from a single district with a limited number of health facilities, which may have led to an over or underestimation of resource consumption. Secondly, the treatment mix provided in our study may not fully reflect the quality standard of care offered by facilities to non-poor patients, as practitioners may have focused solely on treating the presented conditions without considering underlying co-morbidities. However, we have triangulated our data with another micro-costing study on health service use among children from the general population, yielding similar findings (unpublished). Moreover, even though providers were compensated for treating the poorest, the incentives provided by the PBF intervention may not have fully encouraged a comprehensive range of services. This discrepancy could have led to a situation where the services provided to the poorest were more limited in scope compared to what was available to other patient groups. To address this limitation, future studies could explore provider behavior through qualitative research. 6. Conclusion Providing curative care services to the poorest at first-level facilities is critical for achieving universal health coverage and leaving no one behind. Our study informs policies such as RAMU in Burkina Faso by providing cost information to plan and finance free curative care for the poor. More research is needed for better cost estimation and the budgeting of curative care services at a higher level of care in LMICs. Abbreviations BIA Budget Impact Analysis CMA Centre Médical avec Antenne Chirurgicale CPI Consumer Price Index CSPS Centre de Santé et de Promotion Sociale FCFA West African CFA franc LMICs Low- and lower-middle-income countries LNOB Leaving no one behind PBF Performance-based financing PHC Primary healthcare RAMU Régime d'Assurance Maladie Universelle scheme UHC Universal Health Coverage USD United States Dollar Declarations Ethics approval and consent to participate Ethical clearance was granted by the Comité National d’Éthique pour la Recherche en Santé in Burkina Faso (Decision No. 2019-01-004). No ethical clearance for this study was required in Germany since the study relied exclusively on secondary fully-anonymized data. Consent for publication Not applicable Availability of data and materials The datasets analyzed during the study are available from the corresponding author on request. Data sharing is subject to compliance with ethical guidelines and institutional policies. Competing interests All authors report no conflict of interest. Funding This research was funded by the European Union Delegation in Burkina Faso within the framework of a EuropeAid project devoted to Capacity Building for Analysis and Policy Research. The award number is EuropeAid/156333/DD/ACT/BF. Authors' contributions YB, MDA, EB conceptualized the study and designed the research methodology. YB analyzed the data and wrote the initial draft of the manuscript. VR provided guidance and expertise. SS collected the data. SS and JAK contributed to the interpretation of the results from the local perspective. HTN contributed secondary data. All authors provided critical input on the manuscript. MDA and HTN supervised the research process and provided guidance on data analysis. All authors critically reviewed the manuscript for important intellectual content. All authors read and approved the final version. 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Marschall P, Flessa S. Efficiency of primary care in rural Burkina Faso. A two-stage DEA analysis. Health economics review. 2011;1(1):1–15. Turner HC, Lauer JA, Tran BX, Teerawattananon Y, Jit M. Adjusting for Inflation and Currency Changes Within Health Economic Studies. Value in Health [Internet]. 2019 Sep 1 [cited 2021 Dec 16];22(9):1026–32. Available from: https://www.valueinhealthjournal.com/article/S1098-3015(19)32149-7/fulltext?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS1098301519321497%3Fshowall%3Dtrue World Bank. Consumer price index. Burkina Faso. Data [Internet]. 2021 [cited 2021 Dec 16]. Available from: https://data.worldbank.org/indicator/FP.CPI.TOTL?locations=BF World Bank. Official exchange rate (LCU per US$, period average) - Burkina Faso | Data [Internet]. 2019 [cited 2021 Dec 15]. Available from: https://data.worldbank.org/indicator/PA.NUS.FCRF?locations=BF Kafando Y, Ridde V. Les ressources financières des comités de gestion du Burkina Faso peuvent améliorer l’équité d’accès au système de santé. Cahiers d’études et de recherches francophones / Santé. 2010 Jul 1;20(3):153–61. Flessa S, Marschall P. Costing of primary care in developing countries: how much health can we buy for a few Dollars? In: Hofmann BR, editor. Health care costs: causes, effects and control [Internet]. New York, USA: Nova Science; 2009 [cited 2021 Aug 26]. Available from: https://www.die-gdi.de/externe-publikationen/article/costing-of-primary-care-in-developing-countries-how-much-health-can-we-buy-for-a-few-dollars/ Levin HM. Cost-effectiveness Analysis. In: Carnoy M, editor. International encyclopedia of economics of education. Pergamon Press; 1995. Network SCM. International standard cost model manual. Measuring and reducing administrative burdens for businesses. 2005; RAPPORT DU PNUD SUR PAURETE 1998 | Shop.un.org : Official Source for United Nations Books and More [Internet]. [cited 2023 Feb 3]. Available from: https://shop.un.org/books/rapport-du-pnud-sur-la-paurete-98-44822 Hanson K, Brikci N, Erlangga D, Alebachew A, Allegri MD, Balabanova D, et al. The Lancet Global Health Commission on financing primary health care: putting people at the centre. The Lancet Global Health. 2022 May 1;10(5):e715–72. Preker AS, Langenbrunner J. Spending wisely: buying health services for the poor. World Bank Publications; 2005. World Bank Group. High-Performance Health Financing for Universal Health Coverage: Driving Sustainable, Inclusive Growth in the 21st Century. World Bank; 2019. Mugisha F, Kouyate B, Dong H, Sauerborn R. Costing health care interventions at primary health facilities in Nouna, Burkina Faso. Afr J Health Sci. 2002 Jun;9(1–2):69–79. Dalaba MA, Welaga P, Matsubara C. Cost of delivering health care services at primary health facilities in Ghana. BMC Health Services Research. 2017 Nov 17;17(1):742. Beaugé Y, Ridde V, Bonnet E, Souleymane S, Kuunibe N, De Allegri M. Factors related to excessive out-of-pocket expenditures among the ultra-poor after discontinuity of PBF: a cross-sectional study in Burkina Faso. Health economics review. 2020;10(1):1–11. Gatome-Munyua A, Sieleunou I, Sory O, Cashin C. Why Is Strategic Purchasing Critical for Universal Health Coverage in Sub-Saharan Africa? Health Systems & Reform. 2022 Mar 1;8(2):e2051795. World Health Organization. What do we know about community health workers? A systematic review of existing reviews. 2020; Global Health Expenditure Database [Internet]. [cited 2023 Mar 18]. Available from: https://apps.who.int/nha/database/PHC_Country_profile/Index/en Kutzin J, Yip W, Cashin C. Alternative financing strategies for universal health coverage. In: World Scientific handbook of global health economics and public policy: volume 1: the economics of health and health systems. World Scientific; 2016. p. 267–309. Cotlear D, Nagpal S, Smith O, Tandon A, Cortez R. Going universal: how 24 developing countries are implementing universal health coverage from the bottom up. World Bank Publications; 2015. Beaugé Y, Koulidiati JL, Ridde V, Robyn PJ, De Allegri M. How much does community-based targeting of the ultra-poor in the health sector cost? Novel evidence from Burkina Faso. Health Economics Review. 2018 Sep 4;8(1):19. Additional Declarations No competing interests reported. Supplementary Files Annex.docx Cite Share Download PDF Status: Published Journal Publication published 28 Nov, 2024 Read the published version in BMC Health Services Research → Version 1 posted Editorial decision: Revision requested 16 Jul, 2024 Editor assigned by journal 14 Jul, 2024 Submission checks completed at journal 14 Jul, 2024 First submitted to journal 12 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4729625","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":327656600,"identity":"b761b308-a75c-4e99-9729-7f5443fa1523","order_by":0,"name":"Yvonne Beaugé","email":"data:image/png;base64,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","orcid":"","institution":"Heidelberg University Hospital and Medical Faculty","correspondingAuthor":true,"prefix":"","firstName":"Yvonne","middleName":"","lastName":"Beaugé","suffix":""},{"id":327656602,"identity":"cd7fabff-b119-4d30-aa21-a8f3dd29b0ad","order_by":1,"name":"Valéry Ridde","email":"","orcid":"","institution":"CEPED, IRD- Université Paris Cité, ERL INSERM SAGESUD","correspondingAuthor":false,"prefix":"","firstName":"Valéry","middleName":"","lastName":"Ridde","suffix":""},{"id":327656603,"identity":"7a4cc803-a4a3-4708-9f10-cb4d632fa2ec","order_by":2,"name":"Sidibé Souleymane","email":"","orcid":"","institution":"University Joseph Ki-Zerbo","correspondingAuthor":false,"prefix":"","firstName":"Sidibé","middleName":"","lastName":"Souleymane","suffix":""},{"id":327656604,"identity":"1dd7420a-2858-42d6-94a2-827d405671b9","order_by":3,"name":"Joël Arthur Kiendrébéogo","email":"","orcid":"","institution":"University Joseph Ki-Zerbo","correspondingAuthor":false,"prefix":"","firstName":"Joël","middleName":"Arthur","lastName":"Kiendrébéogo","suffix":""},{"id":327656606,"identity":"bb99a8c8-0c12-486c-b15c-4c45ca89b0da","order_by":4,"name":"Hoa Thi Nguyen","email":"","orcid":"","institution":"Heidelberg University Hospital and Medical Faculty","correspondingAuthor":false,"prefix":"","firstName":"Hoa","middleName":"Thi","lastName":"Nguyen","suffix":""},{"id":327656609,"identity":"904906a0-510c-4106-a3d9-2da61a854012","order_by":5,"name":"Emmanuel Bonnet","email":"","orcid":"","institution":"Unité Mixte Internationale (UMI) Résiliences","correspondingAuthor":false,"prefix":"","firstName":"Emmanuel","middleName":"","lastName":"Bonnet","suffix":""},{"id":327656610,"identity":"52c7c63c-90c7-4c48-89e9-ef85c036fef2","order_by":6,"name":"Manuela De Allegri","email":"","orcid":"","institution":"Heidelberg University Hospital and Medical Faculty","correspondingAuthor":false,"prefix":"","firstName":"Manuela","middleName":"","lastName":"De Allegri","suffix":""}],"badges":[],"createdAt":"2024-07-12 10:32:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4729625/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4729625/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12913-024-11854-8","type":"published","date":"2024-11-28T15:58:20+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":62541992,"identity":"2a3a3c90-eac3-4d17-bb09-099e2c3bbc1a","added_by":"auto","created_at":"2024-08-15 15:04:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":83667,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConceptual Framework for BIA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis figure illustrates the conceptual framework developed for the BIA of providing first-level curative outpatient healthcare services to the poorest in Burkina Faso. The scenario names are shown in dark grey, and the green box indicates where each scenario differs from the base case. The white box indicates the economic endpoints. Utilization rates were estimated based on data from the poorest in Diébougou district, with an average of 0.25 healthcare contacts per person per year in the base case, as determined by the authors. This framework allowed us to assess the financial impact of different scenarios and identify those that would have the greatest impact on the healthcare budget.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4729625/v1/a5b60334d999dfbfca9ab63a.png"},{"id":70389477,"identity":"56cb1607-009c-4ec6-aebf-3beb5ec425f3","added_by":"auto","created_at":"2024-12-02 17:28:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":983864,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4729625/v1/1fad929f-41bc-4103-98d0-fa703c08e71d.pdf"},{"id":62541990,"identity":"85c58438-eb84-4a57-9934-9b51cb994ba4","added_by":"auto","created_at":"2024-08-15 15:04:00","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":22822,"visible":true,"origin":"","legend":"","description":"","filename":"Annex.docx","url":"https://assets-eu.researchsquare.com/files/rs-4729625/v1/ac685667443ec1e1eee1c346.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Costing Curative Outpatient Care for the Poorest in Burkina Faso: Informing Universal Health Coverage and Leaving No One Behind","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eUniversal Health Coverage (UHC), a critical component of the United Nations' third Sustainable Development Goal, aims to provide equitable access to quality health services for everyone without financial hardship (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Despite global efforts to expand access to healthcare, over 400\u0026nbsp;million poor and vulnerable people in low- and lower-middle-income countries (LMICs) (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) still face persistent and severe health disparities due to limited access to essential health services (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). To ensure that existing inequities are taken into account in the design of health policies, UHC embraces the Leaving No One Behind (LNOB) principle (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) prioritizing the expansion and improvement of effective service delivery models for the poorest.\u003c/p\u003e \u003cp\u003eIn LMICs, providing quality healthcare services to the poorest populations is challenging due to their remote locations, limited health literacy, and complex health needs (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). As a result, delivering healthcare services to this group may involve higher costs compared with the general population. Still, there is a lack of accurate costing studies addressing the specific needs of the poorest individuals (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). In turn, this lack of accurate cost information represents a real barrier to the design and implementation of programs aimed at enhancing access to care for this specific segment of the population, such as targeted publicly-funded health insurance schemes or free health care policies. Existing literature on the costs of healthcare services in LMICs mainly focuses on the general population, specific diseases, or other specific populations (\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), leaving a significant research gap regarding the costs of services for the poorest individuals.\u003c/p\u003e \u003cp\u003eBurkina Faso, a country committed to improving healthcare access for its poorest populations, has implemented various health financing reforms, including community or occupational based health insurance and user fee removal for pregnant women and children under the age of five (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Notably, the R\u0026eacute;gime d'Assurance Maladie Universelle scheme (RAMU), stands out as a national health insurance program enacted into law on 5th September 2015 (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) to provide quality health services to all, with a particular emphasis on the poorest and most vulnerable populations. By aligning with the policy objectives of UHC and LNOB, Burkina Faso aims to eliminate financial barriers and enhance health outcomes for all its citizens.\u003c/p\u003e \u003cp\u003eHowever, the aforementioned challenges persist in effectively targeting and extending coverage to all poor and informal workers (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), necessitating a closer examination of the economic costs associated with providing curative outpatient care to the poorest population in Burkina Faso at first-level healthcare facilities. Therefore, we conducted a comprehensive micro-costing study adopting a health system perspective to provide decision-makers with crucial cost data to inform the budgeting and implementation of policies to facilitate free access to care for the poorest.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study setting\u003c/h2\u003e \u003cp\u003eBurkina Faso is located in West Africa and had a population of 21.51\u0026nbsp;million in 2021. The country is positioned among the world's poorest nations. Over 40% of its population lives in poverty, surviving on less than USD 1.90 a day (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). This study specifically examines the so called \u0026lsquo;ultra-poor\u0026rsquo; (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), who are in an advanced state of poverty and lack basic necessities, such as food, shelter, and sanitation, as well as the financial and social resources necessary to access and pay for essential healthcare services (\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). To enhance readability, the term 'ultra-poor' is interchangeably referred to as the 'poorest' throughout this manuscript. The unique setting for this study is the Di\u0026eacute;bougou health district, where the introduction of the Performance-based Financing (PBF) intervention, combined with a community-based targeting and exemption mechanism for the poorest in 2016, provided a valuable opportunity to distinguish medical records of the poorest from non-poor patients (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). The PBF initiative not only aimed to improve healthcare quality and accessibility, but also introduced mechanisms to identify and exempt the poorest from health care payments (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), the key population of this study. Within Burkina Faso, primary level healthcare services are provided at \u003cem\u003eCentre de Sant\u0026eacute; et de Promotion Sociale\u003c/em\u003e (CSPS) and \u003cem\u003eCentre M\u0026eacute;dical avec Antenne Chirurgicale\u003c/em\u003e (CMA), with each CSPS serving approximately 8,000\u0026ndash;15,000 individuals and covering 5 to 23 villages. This study focuses on first-level services offered by CSPS, primarily located in the rural and peripheral areas of Burkina Faso (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Study design and overall approach\u003c/h2\u003e \u003cp\u003eTo provide policy makers with relevant cost information, we adopted a health system perspective and employed two different approaches to address our study objectives. Firstly, we conducted a micro-costing study using a bottom-up approach to estimate the average cost of providing a curative outpatient consultation at the CSPS level (first-level of services) to the exempted poorest. The ability to distinguish medical records of the poorest from non-poor patients was enabled by the prior implementation of the PBF intervention in the Di\u0026eacute;bougou district in 2016.\u003c/p\u003e \u003cp\u003eSecondly, we used the estimated cost per consultation to assess the budget impact of providing first-level curative outpatient care to the poorest across the country.\u003c/p\u003e \u003cp\u003eThe base year of the cost analysis is 2019, in order to align with the research project's deliverables. To account for inflation, we adjusted all costs incurred before 2019 using the national consumer price index (CPI) (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). We multiplied the cost incurred in 2016 by the ratio of the relevant CPI (CPI 2019\u0026thinsp;=\u0026thinsp;108.36 / CPI 2016\u0026thinsp;=\u0026thinsp;108.23). We obtained Burkina Faso's annual CPI from the International Monetary Fund, International Financial Statistics (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). We converted values from FCFA to USD using the average exchange rate for 2019 (1 USD\u0026thinsp;=\u0026thinsp;FCFA 585.91) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). We used Microsoft Excel 2019 (Microsoft, Redmond, WA) to operationalize the model.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Identification of cost categories and measurement of resource consumption\u003c/h2\u003e \u003cp\u003eWe identified two cost categories for the study: capital costs and recurrent costs. Capital costs included building and equipment costs, while recurrent costs included consultation fees, drugs, and human resources. Local experts were consulted to identify these cost categories. The quantity of rapid tests and the use of test strips was minimal and thus excluded. Resource consumption for recurrent costs and capital costs was measured using patient registries and a health facility survey, respectively.\u003c/p\u003e \u003cp\u003ePatient registries from 15 CSPS in the Di\u0026eacute;bougou district were used from January to December 2016 in order to estimate the recurrent resources consumed by the poorest. Ten enumerators collected the paper-based information and transferred it to Excel. In total, 1380 patient records were used after excluding children below five years (who were covered by the national free health care policy for the pregnant women and children under five) and records with missing values. We conducted an additional data collection in August 2020 to obtain unit cost information for the drugs used in the medical records. We created a drug list matrix based on the entries in the records, and employing a trained enumerator to collect the unit cost information from pharmacy registries.\u003c/p\u003e \u003cp\u003eFor capital costs, we utilized a health facility survey conducted between March and May 2018 as part of another research project, which collected information on capital costs and variable overheads from 32 CSPS distributed across four regions (North, Hauts-Bassins, Est, and Centre South) by 20 trained enumerators. Paper-based responses were transferred to Excel. We extracted information on equipment for this study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Valuation of costs\u003c/h2\u003e \u003cp\u003eWe used a standardized approach to value costs by relating the unit cost of each resource to the quantity measured in the previous step. We obtained unit cost information from various sources. Recurrent costs were estimated from the fee structure of healthcare facilities for consultation services, while average drug prices among adults were derived from pharmacy registries. For human resource costs not covered by the consultation fees, we used the human capital approach, extracting salary information for nurses, midwives, and mobile health workers from data collected within the PBF end-line impact evaluation framework in the Di\u0026eacute;bougou district. The salaries of doctors and pharmacists were adopted from literature (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), based on the average gross monthly salary, with a working month consisting of 22 working days and eight hours/day.\u003c/p\u003e \u003cp\u003eTo estimate building costs, we interviewed Ministry of Health experts to determine the average cost of building a CSPS (104\u0026nbsp;million FCFA without equipment) and the useful lifespan of the CSPS (25 years). We derived the average size of a CSPS (500 sq m) from construction plans and used the square meters occupied for consultations (245 sq m) from the construction plan to allocate the building cost for consultation service (104\u0026nbsp;million FCFA * 245/500). For equipment, we estimated the unit costs and useful lifespan by triangulating information from two ministry structures: \u003cem\u003eDirection des Infrastructures, de l'Equipement\u003c/em\u003e et de la Maintenance and \u003cem\u003eSoci\u0026eacute;t\u0026eacute; de Gestion de l'Equipement et de la Maintenance Biom\u0026eacute;dicale\u003c/em\u003e - Management Company of Biomedical Equipment and Maintenance (SOGEMAB). Straight-line depreciation was applied by dividing the item's value by its useful lifespan. For equipment with a defined value below FCFA 15,000 (USD 25.50), we used the approach taken by Flessa \u0026amp; Marshall (2009) (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) and depreciated them within a year.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Cost data analysis\u003c/h2\u003e \u003cp\u003eTo analyze the cost of a first-level curative outpatient consultation, we differentiated between capital and recurrent costs. Valuing these costs involved combining information on resource consumption with the unit prices described earlier (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). To account for indirect administrative expenses, we applied an average overhead rate of 20% to the total fixed and variable costs. This approach is consistent with the guidelines outlined in the International Standard Cost Model Manual (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe estimated the average building and equipment costs per consultation by dividing the total building and equipment costs by the total number of consultations. The average cost per consultation was then calculated as the sum of the average recurrent costs for each cost item (human resource, consultation, drugs, and variable overheads) and the average capital cost.\u003c/p\u003e \u003cp\u003eWe conducted a two-way sensitivity analysis to account for the uncertainty surrounding the drug and overhead estimates. Specifically, we applied the mean drug expenditure of FCFA 657.68 plus one standard deviation (FCFA 545.36) and two standard deviations (FCFA 1,090.72). In addition, we increased the overhead rate for capital and recurrent costs from 20\u0026ndash;25%.\u003c/p\u003e \u003cp\u003eThis approach allowed us to obtain a comprehensive understanding of the cost and to identify the key cost drivers.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Budget impact analysis (BIA)\u003c/h2\u003e \u003cp\u003eWe conducted a BIA to estimate the financial impact of providing first-level curative healthcare services to poorest nationwide on the Burkinabe healthcare budget. For this analysis we focused only on recurrent costs.\u003c/p\u003e \u003cp\u003eIf the government of Burkina Faso were to provide first-level curative services for the poorest without charging user fees, they would need to plan a budget to cover the recurrent costs for the health facilities.\u003c/p\u003e \u003cp\u003eTo guide our analysis, we developed a model framework following the guidelines on BIA for healthcare interventions, depicted in (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. We used a cost-calculator model to estimate the annual costs, which multiplies the annual service volume by its average costs.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e This figure illustrates the conceptual framework developed for the BIA of providing first\u0026minus;level curative outpatient healthcare services to the poorest in Burkina Faso. The scenario names are shown in dark grey, and the green box indicates where each scenario differs from the base case. The white box indicates the economic endpoints. Utilization rates were estimated based on data from the poorest in Di\u0026eacute;bougou district, with an average of 0.25 healthcare contacts per person per year in the base case, as determined by the authors. This framework allowed us to assess the financial impact of different scenarios and identify those that would have the greatest impact on the healthcare budget.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Model Inputs\u003c/h2\u003e \u003cp\u003eThe model used four inputs:\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEligible Population\u003c/strong\u003e \u003cp\u003eThe model population consisted of 6%, 9%, and 20% of the total population in Burkina Faso, assumed to be eligible for targeted user fee exemptions. The 6% threshold was used as a community threshold, and the 9% threshold illustrated the extremely poor according to the United Nations Development Programme (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). The 20% threshold reflected the concept of the \"bottom 20% of the population,\" the poorest income quintile, as measured by income inequality.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eTime frame\u003c/strong\u003e \u003cp\u003eThe time span of one year was adopted, in line with the period of the national healthcare budget of Burkina Faso.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eUptake of the intervention\u003c/strong\u003e \u003cp\u003eThe poorest in the Di\u0026eacute;bougou district had, on average, 0.25 healthcare contacts per person per year, based on the estimates derived from above. The context-specific utilization rate was doubled and quadrupled to reflect a likely increase in the intervention uptake in the absence of a specific global recommendation for the number of outpatient care contacts per person per year.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCosts\u003c/strong\u003e \u003cp\u003eThe base case and scenario analysis inputs originated from the cost assessment described above.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 Model output\u003c/h2\u003e \u003cp\u003eThe primary output of interest was the total annual recurrent cost.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.9 Scenario analysis\u003c/h2\u003e \u003cp\u003eWe conducted medium and high assumption scenarios reflecting alternative values for drugs and overheads, while also considering different thresholds of population coverage (6%, 9%, and 20% of the population) and different utilization rates among the targeted poorest (0.25, 0.50, and 2.00 healthcare contacts per capita per person per year) (Annex I and II).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.10 Ethical considerations\u003c/h2\u003e \u003cp\u003eEthical clearance was granted by the \u003cem\u003eComit\u0026eacute; National d\u0026rsquo;\u0026Eacute;thique pour la Recherche en Sant\u0026eacute;\u003c/em\u003e in Burkina Faso (Decision No. 2019-01-004). No ethical clearance for this study was required in Germany since the study relied exclusively on secondary fully-anonymized data.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Findings","content":"\u003cp\u003eThe study estimated the average cost per first-level curative outpatient consultation for the poorest in Burkina Faso to be USD 3.17 \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e Recurrent costs constituted 81.39% of the total cost, with drugs and human resources being the two largest cost drivers at 35.33% and 21.77%, respectively. Capital costs accounted for the remaining 18.61% of the total cost.\u003c/p\u003e \u003cp\u003eScenario analyses assessed the impact of varying drug costs and overhead percentages on the total average cost. Scenario I, which increased the drug cost from USD 1.12 to USD 2.05 and the overhead percentage from 20\u0026ndash;25%, increased the total average cost from USD 3.17 to USD 4.45. Scenario II, which increased the drug cost from USD 1.12 to USD 2.97 and the overhead percentage from 20\u0026ndash;25%, further increased the total average cost from USD 3.17 to USD 5.61.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe average cost of providing one first-level curative outpatient consultation to the poorest in Burkina Faso.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBase calculation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eResults Scenario analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTime Horizon 1 YEAR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eCost per consultation in USD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eI. Capital costs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuilding costs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.26 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.26 USD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEquipment costs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.23 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.23 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.23 USD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFixed Overheads 20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.10 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.12 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12 USD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eTotal Capital Cost\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.59 USD\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.61 USD\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.61 USD\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eII. Recurrent costs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eCost per consultation in USD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConsultation costs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.34 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.34 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.34 USD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrug costs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.12 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.05 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.97 USD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman resource costs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.69 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.69 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.69 USD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable overheads 20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.43 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.76 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 USD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTOTAL Recurrent cost\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e2.58 USD\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e3.84 USD\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e5.00 USD\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003eGRAND TOTAL CAPITAL AND\u003c/span\u003e\u003c/p\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003eRECURRENT COST PER CONSULTATION\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003e3.17 USD\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003e4.45 USD\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003e5.61 USD\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the recurrent costs and budget impact of providing curative outpatient healthcare services to the poorest in Burkina Faso. Costs vary based on the population targeted and the expected number of curative contacts. For example, targeting 6% of the population with 0.25 curative contacts per capita would cost USD 832,225.81 annually, equivalent to 0.22% of the healthcare budget. Increasing the target population to 20% with 0.50 curative contacts would cost USD 5,548,172, representing 1.48% of the healthcare budget. Three scenarios are presented with different targeting thresholds and utilization rates, ranging from USD 832,225.81 to USD 22,192,688.35 representing 0.22\u0026ndash;5.91% of the healthcare budget, respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCost and budget impact estimates applying different targeting thresholds and population coverage.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCost category\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBase case: Targeting threshold 6% of the population:1,290,611\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e% of the healthcare budget\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMedium assumption scenario: Targeting threshold 9% of the population: 1,935,916\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e% of the healthcare budget\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHigh assumption scenario Targeting threshold 20% of the population: 4,302,036\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e% of the healthcare budget\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScenario 1 Utilization 0.25\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConsultation costs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSD 109,833.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSD 164,750.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUSD 366,112.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDrug costs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSD 361,177.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSD 541,766.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUSD 1,203,926.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHuman resources\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSD 222,509.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSD 333,764.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUSD 741,699.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVariable overheads 20%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSD 138,704.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSD 208,056.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUSD 462,347.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003eTOTAL RECURRENT COST IN USD\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003eUSD 832,225.81\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003e0.22\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003eUSD 1,248,338.72\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003e0.33\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003eUSD 2,774,086.04\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003e0.74\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eScenario 2: Utilization 0.50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConsultation costs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSD 219,667.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSD 329,501.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUSD 732,224.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDrug costs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSD 722,355.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSD 1,083,533.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUSD 2,407,852.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHuman resources\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSD 445,019.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSD 667,529.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUSD 1,483,399.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVariable overheads 20%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSD 277,408.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSD 416,112.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUSD 924,695.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003eTOTAL RECURRENT COST IN USD\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003eUSD 1,664,451.63\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003e0.44\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003eUSD 2,496,677.44\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003e0.66\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003eUSD 5,548,172.09\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003e1.48\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eScenario 3: Utilization 2.00\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConsultation costs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSD 878,669.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSD 1,318,004.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUSD 2,928,898.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDrug costs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSD 2,889,423.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSD 4,334,134.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUSD 9,631,410.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHuman resources\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSD 1,780,079.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSD 2,670,118.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUSD 5,933,597.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVariable overheads 20%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSD 1,109,634.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSD 1,664,451.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUSD 3,698,781.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003eTOTAL RECURRENT COST IN USD\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003eUSD 6,657,806.50\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003e1.77\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003eUSD 9,986,709.76\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003e2.66\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003eUSD 22,192,688.35\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"BoldDoubleUnderline\" class=\"BoldDoubleUnderline\" name=\"Emphasis\"\u003e5.91\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e "},{"header":"4. Discussion","content":"\u003cp\u003e \u003cb\u003e4.1 Insights into the cost of providing curative outpatient services at first-level healthcare facilities to the poorest and policy implications\u003c/b\u003e \u003c/p\u003e \u003cp\u003eOur study estimates the average cost of providing curative outpatient services at first level healthcare facilities to Burkina Faso's poorest population, ranging from USD 3.17 to USD 5.61 per consultation. These cost estimates offer policymakers valuable insights, particularly when it comes to setting prices for healthcare services covered by free healthcare policies for the poorest supported by the government through the RAMU. Notably, the cost estimate, while specific to curative care, underscores the broader need for accurate financial planning within the healthcare system. It is this accurate financial planning that plays a vital role in ensuring adequate resources for the successful implementation of the free health care for the poor and achieving the global goal of strengthening health systems for UHC, as emphasized in the Declaration of Astana.\u003c/p\u003e \u003cp\u003eMoreover, recognizing the importance of curative outpatient services at first-level facilities as part of primary healthcare (PHC) (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) further emphasizes the significance of our cost estimate. Such services represent the first point of care and are instrumental in the pursuit of comprehensive healthcare for all. Beyond the local context, the involvement of organizations such as the World Bank in discussions about implementing flat-rate purchases for free healthcare policies (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) underlines the practical relevance of our findings and illustrates how these findings can help shape healthcare policy and financial planning in the region.\u003c/p\u003e \u003cp\u003eOur cost estimates align with earlier studies in Burkina Faso for the general population, underscoring a potential stability in healthcare costs even considering the considerable time elapsed since those studies were conducted (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Notably, Flessa \u0026amp; Marschall (2009) estimated the average cost per consultation at USD 2.94 (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e), while Mugisha et al. (2002) evaluated outpatient services for the rural population in Nouna at USD 3.08 (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), which is almost matching our lowest estimate of USD 3.17. The consistency of these figures over time prompts reflection on how inflation has seemingly had minimal impact on healthcare costs within Burkina Faso's healthcare system. However, a study in rural Ghana (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) revealed a notably higher median cost of USD 8.79 for outpatient department attendance, likely linked to economic disparities. Ghana's comparatively higher income level, relative to Burkina Faso, suggests a plausible influence on healthcare expenses.\u003c/p\u003e \u003cp\u003eDrug costs accounted for 35.33% of the total cost, and human resources at 21.77%. Our estimate differs from prior studies, where drug costs were the second-largest driver (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), but it aligns with our initial expectations due to the complex morbidity profile of the poorest population seeking late-stage care requiring complex medication (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). To enhance access to quality healthcare, controlling drug costs and improving procurement processes are crucial (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). While not directly derived from our cost analysis, the role of community health workers emerges as a complementary strategy, especially relevant in the context of our findings. By providing first-level services, particularly in underserved rural areas (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e), community health workers can alleviate the burden on healthcare facilities, indirectly affecting the cost structure by reducing the demand for more expensive, late-stage treatments. Their involvement can improve medication adherence among the poorest populations, potentially mitigating the need for complex and costly care. This indirect link suggests that incorporating community health workers into healthcare delivery models could enhance the overall cost-effectiveness and efficiency of care for these vulnerable groups.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Insights into the budget-impact and policy implications\u003c/h2\u003e \u003cp\u003eThe findings indicate that across all hypothetical budget scenarios (I-II, as detailed in the Annex), providing free curative outpatient care at first-level healthcare facilities for up to 20% of the population would result in a healthcare budget impact between 0.22 and 11.45 percent. This suggests that providing these services to the bottom 20% of the population could be financially viable without imposing a substantial burden on the government's budget.\u003c/p\u003e \u003cp\u003eWhile Burkina Faso allocated 46% of its government health spending to PHC in 2020 (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e), a relatively high share compared with neighboring countries (such as C\u0026ocirc;te d'Ivoire 38%, Niger 36% and Benin 13% (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e)) the need for further investment and resource allocation efficiency is evident. This becomes particularly important when considering that 31% of PHC funding in Burkina Faso relies on out-of-pocket payments and 22% on external sources (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Policymakers should explore fund reallocation and alternative financing sources (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e), bearing in mind the challenges posed by the current economic and security context (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) as they work to progress toward UHC and ensure equitable healthcare access for the most vulnerable populations.\u003c/p\u003e \u003cp\u003ePolicymakers may also need to consider implementing RAMU gradually, increasing coverage step by step, as done in other countries with successful fee removal policies, such as Ghana, Colombia, Mexico, and Thailand (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Furthermore, our study did not consider the cost of identifying the poorest, estimated at 5.73 USD per beneficiary (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e), which can significantly impact the financial costs of the policy and should be factored in to ensure its sustainability and affordability.\u003c/p\u003e \u003cp\u003eWith the ongoing implementation of RAMU in Burkina Faso (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), the findings of our study hold significant relevance. Policymakers can use our cost estimates and budget impact analysis to guide budget planning, policy decisions, and the pricing of services. Addressing financial implications, cost drivers, and cost-effectiveness strategies will support the successful and sustainable implementation of RAMU and advance the goals of UHC and LNOB in Burkina Faso and similar resource constrained settings.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Methodological consideration","content":"\u003cp\u003eOur study has limitations that must be considered. Firstly, the cost and budget estimates were derived from a single district with a limited number of health facilities, which may have led to an over or underestimation of resource consumption. Secondly, the treatment mix provided in our study may not fully reflect the quality standard of care offered by facilities to non-poor patients, as practitioners may have focused solely on treating the presented conditions without considering underlying co-morbidities. However, we have triangulated our data with another micro-costing study on health service use among children from the general population, yielding similar findings (unpublished). Moreover, even though providers were compensated for treating the poorest, the incentives provided by the PBF intervention may not have fully encouraged a comprehensive range of services. This discrepancy could have led to a situation where the services provided to the poorest were more limited in scope compared to what was available to other patient groups. To address this limitation, future studies could explore provider behavior through qualitative research.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eProviding curative care services to the poorest at first-level facilities is critical for achieving universal health coverage and leaving no one behind. Our study informs policies such as RAMU in Burkina Faso by providing cost information to plan and finance free curative care for the poor. More research is needed for better cost estimation and the budgeting of curative care services at a higher level of care in LMICs.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eBIA\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eBudget Impact Analysis\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eCMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eCentre M\u0026eacute;dical avec Antenne Chirurgicale\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eCPI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eConsumer Price Index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eCSPS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eCentre de Sant\u0026eacute; et de Promotion Sociale\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eFCFA\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eWest African CFA franc\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eLMICs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eLow- and lower-middle-income countries\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eLNOB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eLeaving no one behind\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003ePBF\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003ePerformance-based financing\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003ePHC\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003ePrimary\u0026nbsp;healthcare\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eRAMU\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eR\u0026eacute;gime d\u0026apos;Assurance Maladie Universelle scheme\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eUHC\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eUniversal Health Coverage\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eUSD\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eUnited States Dollar\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical clearance was granted by the Comit\u0026eacute; National d\u0026rsquo;\u0026Eacute;thique pour la Recherche en Sant\u0026eacute; in Burkina Faso (Decision No. 2019-01-004). No ethical clearance for this study was required in Germany since the study relied exclusively on secondary fully-anonymized data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets analyzed during the study are available from the corresponding author on request. Data sharing is subject to compliance with ethical guidelines and institutional policies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors report no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the European Union Delegation in Burkina Faso within the framework of a EuropeAid project devoted to Capacity Building for Analysis and Policy Research. The award number is EuropeAid/156333/DD/ACT/BF.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYB, MDA, EB conceptualized the study and designed the research methodology. YB analyzed the data and wrote the initial draft of the manuscript. VR provided guidance and expertise. SS collected the data. SS and JAK contributed to the interpretation of the results from the local perspective. HTN contributed secondary data. All authors provided critical input on the manuscript. MDA and HTN supervised the research process and provided guidance on data analysis. All authors critically reviewed the manuscript for important intellectual content. All authors read and approved the final version.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank Salvador Shabbir for proofreading the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; information\u003c/strong\u003e (optional): Not applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eUnited Nations. Goal 3 | Department of Economic and Social Affairs [Internet]. 2023 [cited 2023 Oct 12]. Available from: https://sdgs.un.org/goals/goal3\u003c/li\u003e\n\u003cli\u003eBukhman G, Mocumbi A. Universal health coverage for the poorest billion: justice and equity considerations \u0026ndash; Authors\u0026rsquo; reply. The Lancet. 2021 Feb 6;397(10273):474. \u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Declaration of Astana [Internet]. Geneva; 2018. 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Why Is Strategic Purchasing Critical for Universal Health Coverage in Sub-Saharan Africa? Health Systems \u0026amp; Reform. 2022 Mar 1;8(2):e2051795. \u003c/li\u003e\n\u003cli\u003eWorld Health Organization. What do we know about community health workers? A systematic review of existing reviews. 2020; \u003c/li\u003e\n\u003cli\u003eGlobal Health Expenditure Database [Internet]. [cited 2023 Mar 18]. Available from: https://apps.who.int/nha/database/PHC_Country_profile/Index/en\u003c/li\u003e\n\u003cli\u003eKutzin J, Yip W, Cashin C. Alternative financing strategies for universal health coverage. In: World Scientific handbook of global health economics and public policy: volume 1: the economics of health and health systems. World Scientific; 2016. p. 267\u0026ndash;309. \u003c/li\u003e\n\u003cli\u003eCotlear D, Nagpal S, Smith O, Tandon A, Cortez R. Going universal: how 24 developing countries are implementing universal health coverage from the bottom up. World Bank Publications; 2015. \u003c/li\u003e\n\u003cli\u003eBeaug\u0026eacute; Y, Koulidiati JL, Ridde V, Robyn PJ, De Allegri M. How much does community-based targeting of the ultra-poor in the health sector cost? Novel evidence from Burkina Faso. Health Economics Review. 2018 Sep 4;8(1):19. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4729625/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4729625/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo provide decision-makers with cost information about policies aimed at facilitating free access to curative outpatient care for the poorest as part of efforts towards achieving universal health coverage and leaving no one behind.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a micro-costing study in Burkina Faso to estimate the economic costs of providing curative outpatient healthcare services to the poorest at first-level healthcare facilities, considering a health system perspective. We measured the consumption of capital costs (building and equipment) using survey data from 32 primary health facilities and recurrent costs (drugs and consumables) from medical records of 1380 poor patients in Di\u0026eacute;bougou district. These individuals were specifically targeted and exempted from user fees through a community-based targeting approach. We obtained unit costs from official price lists, pharmacy registries, and expert interviews. Furthermore, we calculated the national budget for providing curative care services to the exempted poorest based on the average cost per first-level consultation.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe estimated capital and recurrent costs of providing curative care services to the poorest ranged between USD 0.59 - USD 0.61 and USD 2.58 - USD 5.00, respectively. The total cost ranged between USD 3.17 - USD 5.61 per first-level consultation. Providing curative care to the bottom 20% of the population, assuming 0.25 healthcare contacts per person per year, would result in an annual expense ranging from USD 2.77M to USD 5.38M (0.74%-1.43% of the healthcare budget in 2019). With 2 healthcare contacts per person per year, costs increase to USD 22.19M to USD 43.05M (5.91%-11.45% of the healthcare budget).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOur study's cost data can inform policies aimed at expanding access to curative care for the poorest in Burkina Faso, contributing to the goals of universal health coverage and leaving no one behind. Further research is needed to enhance cost estimation and budgeting for higher-level care in the country.\u003c/p\u003e","manuscriptTitle":"Costing Curative Outpatient Care for the Poorest in Burkina Faso: Informing Universal Health Coverage and Leaving No One Behind","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-15 15:03:55","doi":"10.21203/rs.3.rs-4729625/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-16T11:30:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-15T02:54:07+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-15T02:53:15+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2024-07-12T10:30:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bd33acb5-474b-4a90-a0ca-3431ca954fd2","owner":[],"postedDate":"August 15th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-02T17:24:09+00:00","versionOfRecord":{"articleIdentity":"rs-4729625","link":"https://doi.org/10.1186/s12913-024-11854-8","journal":{"identity":"bmc-health-services-research","isVorOnly":false,"title":"BMC Health Services Research"},"publishedOn":"2024-11-28 15:58:20","publishedOnDateReadable":"November 28th, 2024"},"versionCreatedAt":"2024-08-15 15:03:55","video":"","vorDoi":"10.1186/s12913-024-11854-8","vorDoiUrl":"https://doi.org/10.1186/s12913-024-11854-8","workflowStages":[]},"version":"v1","identity":"rs-4729625","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4729625","identity":"rs-4729625","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}