Caroline Govathson, Lawrence C. Long, Colin A. Russell, Aneesa Moolla, Sophie Pascoe, Brooke E. Nichols

A modelling framework for translating discrete choice experiment results into cost‐effectiveness estimates: an application to designing tailored and scalable HIV and contraceptive services for adolescents in Gauteng, South Africa

  • Infectious Diseases
  • Public Health, Environmental and Occupational Health

AbstractIntroductionSouth African youth and adolescents face a high burden of (Sexually Transmitted Infections) STIs, HIV and unintended pregnancies, but uptake of services remains low. To address this, tailored and scalable interventions are urgently needed. We developed a framework to fill the gap and translate the impact of facility‐level attributes into a cost‐effectiveness analysis for increasing HIV/contraceptive service uptake in adolescents using a discrete choice experiment (DCE).MethodsWe used a DCE (n = 805) conducted in Gauteng, South Africa, which found that staff attitude, confidentiality, Wi‐Fi, subsidized food, afternoon hours and youth‐only services were preferred attributes of health services. Based on this, we simulated the uptake of services adapted for these preferences. We divided preferences into modifiable attributes that could readily be adapted (e.g. Wi‐Fi), and challenging to modify (more nuanced attributes that are more challenging to cost and evaluate): staff attitude and estimated the incremental change in the uptake of services using adapted services. Costs for modifiable preferences were estimated using data from two clinics in South Africa (2019 US$). We determined the incremental cost‐effectiveness ratio (ICER) for additional adolescents using services of 15 intervention combinations, and report the results of interventions on the cost‐effectiveness frontier.ResultsGreatest projected impact on uptake was from friendly and confidential services, both of which were considered challenging to modify (18.5% 95% CI: 13.0%−24.0%; 8.4% 95% CI: 3.0%−14.0%, respectively). Modifiable factors on their own resulted in only small increases in expected uptake. (Food: 2.3% 95% CI: 4.0%−9.00%; Wi‐Fi: 3.0% 95% CI: −4.0% to 10.0%; Youth‐only services: 0.3% 95% CI: −6.0% to 7.0%; Afternoon services: 0.8% 95% CI: −6.0% to 7.0%). The order of interventions on the cost‐effectiveness frontier are Wi‐Fi and youth‐only services (ICER US$7.01−US$9.78 per additional adolescent utilizing HIV and contraceptive services), Wi‐Fi, youth‐only services and food (ICER US$9.32−US$10.45), followed by Wi‐Fi, youth‐only services and extended afternoon hours (ICER US$14.46–US$43.63).ConclusionsCombining DCE results and costing analyses within a modelling framework provides an innovative way to inform decisions on effective resource utilization. Modifiable preferences, such as Wi‐Fi provision, youth‐only services and subsidized food, have the potential to cost‐effectively increase the proportion of adolescents accessing HIV and contraceptive services.

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