Center for Health Systems Research, National Institute of Public Health, Cuernavaca, Mexico.
University of California Berkeley, Berkeley, CA, United States of America.
PLoS One. 2021 Apr 22;16(4):e0249076. doi: 10.1371/journal.pone.0249076. eCollection 2021.
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.
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.
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.
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.
优化资金决策的一个关键因素涉及实施替代项目组件和配置的成本和效率影响。项目规划者、政策制定者和资金提供者都需要相关的战略数据和分析，以帮助他们规划和实施有效和高效的项目。与政策和学术领域广泛接受的观念相反，每服务平均成本（所谓的“单位成本”）在不同的实施环境和设施中差异很大。这项工作的目的有两个：1）估计撒哈拉以南国家不同服务提供平台（SDP）的 VMMC 单位成本变化，2）制定并验证一种将单位成本外推到尚无数据的环境的策略。
我们通过文献回顾确定了高质量的 VMMC 成本研究。联系作者以请求他们提供研究结果所依据的设施层面数据集（原始数据）。我们将不同的数据标准化为一个综合数据库，其中包括 8 个国家的 228 个设施。我们估计了多元模型，以评估 VMMC 单位成本与规模之间的相关性，同时考虑到 SDP（我们将其定义为设施类型、所有权、城市性和国家的所有可能组合）对单位成本变化的影响。我们将 SDP 定义为这四个特征的任何组合。最后，我们外推了 13 个国家所有 SDP 的 VMMC 单位成本，包括我们数据集中没有的国家。
平均单位成本为 73 美元（IQR：28.3，100.7）。南非显示了最高的国内成本变化，以及最高的平均单位成本（135 美元）。乌干达和纳米比亚的国内成本变化最小，乌干达的 VMMC 单位成本最低（22 美元）。我们的结果表明存在规模经济的证据。私人所有和医院是单位成本较高的重要决定因素。通过确定关键成本驱动因素，包括国家和设施层面的特征，以及规模的影响，我们开发了经济计量模型，以估计各种临床和地理环境下的 VMMC 服务的单位成本曲线。
虽然我们的研究没有产生新的经验数据，但我们的结果将 14 个 VMMC 重点国家的 128 个 SDP 的单位成本估计数增加了十倍。据我们所知，这是迄今为止对 VMMC 单位成本最全面的分析。此外，我们提供了一个概念验证，证明了在没有经验数据的情况下生成预测性成本估计的能力。
