Planning a Community Approach to Diabetes Care in Low-and Middle-Income Countries Using Optimization

• 成果类型: Article; Early Access
• 署名作者: Adams, Katherine B.; Boutilier, Justin J.; Deo, Sarang; Mintz, Yonatan
• 署名单位: University of Texas System; University of Texas at San Antonio; University of Ottawa; Indian School of Business (ISB); University of Wisconsin System; University of Wisconsin Madison
• 刊物名称: OPERATIONS RESEARCH
• ISSN/ISSBN: 0030-364X
• DOI: 10.1287/opre.2023.0248
• 发表日期: 2026-05-08
• 关键词: diabetes; optimization; dynamic programming; global health; HEALTH; BEHAVIOR; metaanalysis; relaxations; management; PROGRAMS; glucose

摘要

Diabetes is a global health priority, especially in low-and middle-income countries, where over 50% of premature deaths are attributed to high blood glucose. Community health worker (CHW) programs can provide affordable and culturally tailored solutions for early detection and management of diabetes. We introduce an optimization framework to determine personalized CHW visits that maximize glycemic control at a community level. Our framework explicitly models the trade-off between screening new patients and providing management visits to individuals who are enrolled in treatment. We account for patients' motivational states, which affect their decisions to enroll or drop out of treatment and therefore, the effectiveness of the intervention. By estimating patients' health and motivational states, our model builds visit plans accounting for patients' tradeoffs when deciding to enroll in treatment, leading to reduced dropout rates and improved resource allocation. We apply our approach to generate CHW visit plans using operational data from urban slums in India. We find that our approach can reduce fasting blood glucose by up to 25% with the same capacity as the best baseline method. Our experiments also demonstrate that our approach performs well with imperfect information.