Schaffer Elisabeth M, Gonzalez Juan Marcos, Wheeler Stephanie B, Kwarisiima Dalsone, Chamie Gabriel, Thirumurthy Harsha
Data Science to Patient Value, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO, USA.
Department of Health Policy and Management, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Appl Health Econ Health Policy. 2020 Jun;18(3):413-432. doi: 10.1007/s40258-019-00549-5.
HIV testing is essential to access HIV treatment and care and plays a critical role in preventing transmission. Despite this, testing coverage is low among men in sub-Saharan Africa. Community-based testing has demonstrated potential to expand male testing coverage, yet scant evidence reveals how community-based services can be designed to optimize testing uptake. We conducted a discrete choice experiment (DCE) to elicit preferences and predict uptake of community-based testing by men in Uganda.
Hypothetical choices between alternative community-based testing services and the option to opt-out of testing were presented to a random, population-based sample of 203 adult male residents. The testing alternatives varied by service delivery model (community health campaign, counselor-administered home-based testing, distribution of HIV self-test kits at local pharmacies), availability of multi-disease testing, access to antiretroviral therapy (ART), and provision of a US$0.85 incentive. We estimated preferences using a random parameters logit model and explored whether preferences varied by participant characteristics through subgroup analyses. We simulated uptake when a single and when two community-based testing services are made available, using reference values of observed uptake to calibrate predictions.
The share of the adult male population predicted to test for HIV ranged from 0.15 to 0.91 when a single community-based testing service is made available and from 0.50 to 0.96 when two community-based services are provided concurrently. ART access was the strongest driver of choices (relative importance [RI] = 3.01, 95% confidence interval [CI]: 1.74-4.29), followed by the service delivery model (RI = 1.27, 95% CI 0.72-1.82) and availability of multi-disease testing (RI = 1.27, 95% CI 0.09-2.45). A US$0.85 incentive had the least yet still significant influence on choices (RI = 0.77, 95% CI 0.06-1.49). Men who perceived their risk of having HIV to be relatively elevated had higher predicted uptake of HIV self-test kits at local pharmacies, as did young adult men compared to men aged ≥ 30 years. Men who earned ≤ the daily median income had higher predicted uptake of all community-based testing services versus men who earned above the daily median income.
Substantial opportunity exists to optimize the delivery of HIV testing to expand uptake by men; using an innovative DCE, we deliver timely, actionable guidance for promoting community-based testing by men in Uganda. We advance the stated preference literature methodologically by describing how we constructed and evaluated a pragmatic experimental design, used interaction terms to conduct subgroup analyses, and harnessed participant-specific preference estimates to predict and calibrate testing uptake.
艾滋病毒检测对于获得艾滋病毒治疗和护理至关重要,在预防传播方面发挥着关键作用。尽管如此,撒哈拉以南非洲男性的检测覆盖率较低。基于社区的检测已显示出扩大男性检测覆盖率的潜力,但很少有证据表明如何设计基于社区的服务以优化检测接受率。我们进行了一项离散选择实验(DCE),以了解乌干达男性对基于社区的检测的偏好并预测其接受情况。
向203名成年男性居民的随机、基于人群的样本提供了基于社区的替代检测服务与选择不进行检测之间的假设选择。检测替代方案因服务提供模式(社区健康运动、咨询师上门检测、在当地药店分发艾滋病毒自我检测试剂盒)、多疾病检测的可用性、抗逆转录病毒疗法(ART)的可及性以及提供0.85美元激励措施而有所不同。我们使用随机参数logit模型估计偏好,并通过亚组分析探讨偏好是否因参与者特征而异。我们使用观察到的接受率参考值来校准预测,模拟了提供单一和两种基于社区的检测服务时的接受情况。
当提供单一的基于社区的检测服务时,预计进行艾滋病毒检测的成年男性人口比例在0.15至0.91之间,当同时提供两种基于社区的服务时,这一比例在0.50至0.96之间。获得ART是选择的最强驱动因素(相对重要性[RI]=3.01,95%置信区间[CI]:1.74 - 4.29),其次是服务提供模式(RI = 1.27,95% CI 0.72 - 1.82)和多疾病检测的可用性(RI = 1.27,95% CI 0.09 - 2.45)。0.85美元的激励措施对选择的影响最小,但仍具有显著影响(RI = 0.77,95% CI 0.06 - 1.49)。认为自己感染艾滋病毒风险相对较高的男性,在当地药店对艾滋病毒自我检测试剂盒的预测接受率较高,与30岁及以上男性相比,年轻成年男性也是如此。日收入≤中位数的男性对所有基于社区的检测服务的预测接受率高于日收入高于中位数的男性。
存在优化艾滋病毒检测服务以扩大男性接受率的重大机会;通过创新的DCE,我们为促进乌干达男性基于社区的检测提供了及时、可操作的指导。我们在方法上推进了陈述偏好文献,描述了我们如何构建和评估一个实用的实验设计、使用交互项进行亚组分析以及利用参与者特定的偏好估计来预测和校准检测接受率。