Moving away from the "unit cost". Predicting country-specific average cost curves of VMMC services accounting for variations in service delivery platforms in sub-Saharan Africa.

BACKGROUND: One critical element to optimize funding decisions involves the cost and efficiency implications of implementing alternative program components and configurations. Program planners, policy makers and funders alike are in need of relevant, strategic data and analyses to help them plan and implement effective and efficient programs. Contrary to widely accepted conceptions in both policy and academic arenas, average costs per service (so-called "unit costs") vary considerably across implementation settings and facilities. The objective of this work is twofold: 1) to estimate the variation of VMMC unit costs across service delivery platforms (SDP) in Sub-Saharan countries, and 2) to develop and validate a strategy to extrapolate unit costs to settings for which no data exists. METHODS: We identified high-quality VMMC cost studies through a literature review. Authors were contacted to request the facility-level datasets (primary data) underlying their results. We standardized the disparate datasets into an aggregated database which included 228 facilities in eight countries. We estimated multivariate models to assess the correlation between VMMC unit costs and scale, while simultaneously accounting for the influence of the SDP (which we defined as all possible combinations of type of facility, ownership, urbanicity, and country), on the unit cost variation. We defined SDP as any combination of such four characteristics. Finally, we extrapolated VMMC unit costs for all SDPs in 13 countries, including those not contained in our dataset. RESULTS: The average unit cost was 73 USD (IQR: 28.3, 100.7). South Africa showed the highest within-country cost variation, as well as the highest mean unit cost (135 USD). Uganda and Namibia had minimal within-country cost variation, and Uganda had the lowest mean VMMC unit cost (22 USD). Our results showed evidence consistent with economies of scale. Private ownership and Hospitals were significant determinants of higher unit costs. By identifying key cost drivers, including country- and facility-level characteristics, as well as the effects of scale we developed econometric models to estimate unit cost curves for VMMC services in a variety of clinical and geographical settings. CONCLUSION: While our study did not produce new empirical data, our results did increase by a tenfold the availability of unit costs estimates for 128 SDPs in 14 priority countries for VMMC. It is to our knowledge, the most comprehensive analysis of VMMC unit costs to date. Furthermore, we provide a proof of concept of the ability to generate predictive cost estimates for settings where empirical data does not exist.

Variation in primary health care services after implementation of quality improvement policy in Brazil.

BACKGROUND: Brazil is the most populous country with a public, universal and free health care system. The National Program for Access and Quality Improvement in Primary Care (PMAQ) was created to improve the quality of primary health care (PHC). OBJECTIVE: To evaluated whether progress generally has been made within Brazil's PHC since PMAQ implementation, and if changes occurred uniformly in the country, while also identifying municipal characteristics that may have influenced the improvement. METHODS: This is an observational study using data from PMAQ external evaluation (2012 and 2014), a 1200-item survey used to evaluate Brazilian PHC quality. After confirming the groupings of items using factor analysis, we created 23 composed indexes (CIs) related to infrastructure and work process. RESULTS: On average, the large majority of CIs showed improvements between 2012 and 2014. Region and city size moderated changes in the PHC indices differently. Overall, there were better improvements in infrastructure in the Northeast compared with other country regions, and in smaller cities (10 000-20 000 people). Infrastructure indices appear to have improved equitably across the country. Work process improvements varied with city size and region. CONCLUSION: Despite similar support of PMAQ across the country, improvements are not predictable nor homogeneous. Non-uniform improvements were seen in Brazil's PHC. Though we do not directly evaluate the effectiveness of the PMAQ (financial reward) method, these initial findings suggest that it is a potentially useful tool to improve health systems, but additional support may be needed in regions that lag behind in quality improvements.

Meta-analysis of average costs of HIV testing and counselling and voluntary medical male circumcision across thirteen countries.

Objective: Explore facility-level average costs per client of HIV testing and counselling (HTC) and voluntary medical male circumcision (VMMC) services in 13 countries.Methods: Through a literature search we identified studies that reported facility-level costs of HTC or VMMC programmes. We requested the primary data from authors and standardised the disparate data sources to make them comparable. We then conducted descriptive statistics and a meta-analysis to assess the cost variation among facilities. All costs were converted to 2017 US dollars ($).Results: We gathered data from 14 studies across 13 countries and 772 facilities (552 HTC, 220 VMMC). The weighted average unit cost per client served was $15 (95% CI 12, 18) for HTC and $59 (95% CI 45, 74) for VMMC. On average, 38% of the mean unit cost for HTC corresponded to recurrent costs, 56% to personnel costs, and 6% to capital costs. For VMMC, 41% of the average unit cost corresponded to recurrent costs, 55% to personnel costs, and 4% to capital costs. We observed unit cost variation within and between countries, and lower costs in higher scale categories in all interventions.

A meta-analysis approach for estimating average unit costs for ART using pooled facility-level primary data from African countries.

Objective: To estimate facility-level average cost for ART services and explore unit cost variations using pooled facility-level cost estimates from four HIV empirical cost studies conducted in five African countries .Methods: Through a literature search we identified studies reporting facility-level costs for ART programmes. We requested the underlying data and standardised the disparate data sources to make them comparable. Subsequently, we estimated the annual cost per patient served and assessed the cost variation among facilities and other service delivery characteristics using descriptive statistics and meta-analysis. All costs were converted to 2017 US dollars ($). Results: We obtained and standardised data from four studies across five African countries and 139 facilities. The weighted average cost per patient on ART was $251 (95% CI: 193-308). On average, 46% of the mean unit cost correspond to antiretroviral (ARVs) costs, 31% to personnel costs, 20% other recurrent costs, and 2% to capital costs. We observed a lot of variation in unit cost and scale levels between countries. We also observed a negative relationship between ART unit cost and the number of patients served in a year.Conclusion: Our approach allowed us to explore unit cost variation across contexts by pooling ART costs from multiple sources. Our research provides an example of how to estimate costs based on heterogeneous sources reconciling methodological differences across studies and contributes by giving an example on how to estimate costs based on heterogeneous sources of data. Also, our study provides additional information on costs for funders, policy-makers, and decision-makers in the process of designing or scaling-up HIV interventions.