Complex health problems require multi-strategy, multi-target interventions. We present a method that uses machine learning techniques to choose optimal interventions from a set of possible interventions within a case study aiming to increase General Practitioner (GP) discussions of physical activity (PA) with their patients. Interventions were developed based on a causal loop diagram with 26 GPs across 13 clinics in Geelong, Australia. GPs prioritised eight from more than 80 potential interventions to increase GP discussion of PA with patients. Following a 2-week baseline, a multi-arm bandit algorithm was used to assign optimal strategies to GP clinics with the target outcome being GP PA discussion rates. The algorithm was updated weekly and the process iterated until the more promising strategies emerged (a duration of seven weeks). The top three performing strategies were continued for 3 weeks to improve the power of the hypothesis test of effectiveness for each strategy compared to baseline. GPs recorded a total of 11,176 conversations about PA. GPs identified 15 factors affecting GP PA discussion rates with patients including GP skills and awareness, fragmentation of care and fear of adverse outcomes. The two most effective strategies were correctly identified within seven weeks of the algorithm-based assignment of strategies. These were clinic reception staff providing PA information to patients at check in and PA screening questionnaires completed in the waiting room. This study demonstrates an efficient way to test and identify optimal strategies from multiple possible solutions.

复杂的健康问题需要多策略、多目标的干预措施。我们提出了一种方法，使用机器学习技术从案例研究中的一组可能的干预措施中选择最佳干预措施，旨在增加全科医生 (GP) 与患者对身体活动 (PA) 的讨论。干预措施是根据澳大利亚吉朗 13 家诊所的 26 名全科医生的因果循环图制定的。全科医生从 80 多种潜在干预措施中优先考虑 8 种，以增加全科医生与患者对 PA 的讨论。在两周基线后，使用多臂老虎机算法为全科医生诊所分配最佳策略，目标结果是全科医生 PA 讨论率。该算法每周更新一次，并且迭代该过程，直到出现更有希望的策略（持续七周）。表现最好的三个策略持续 3 周，以提高每个策略相对于基线的有效性假设检验的能力。全科医生总共记录了 11,176 条有关 PA 的对话。全科医生确定了影响全科医生与患者进行 PA 讨论率的 15 个因素，包括全科医生的技能和意识、护理的分散性以及对不良结果的恐惧。在基于算法的策略分配后七周内，正确识别了两种最有效的策略。这些是诊所接待人员，在办理入住时向患者提供 PA 信息，并在候诊室填写 PA 筛查问卷。这项研究展示了一种从多种可能的解决方案中测试和识别最佳策略的有效方法。