Ranson M Kent, Sinha Tara, Morris Saul S, Mills Anne J
Health Policy Unit, London School of Hygiene and Tropical Medicine, UK.
Can J Public Health. 2006 Jan-Feb;97(1):72-5. doi: 10.1007/BF03405220.
This paper addresses the logistical challenges of implementing public health interventions in the setting of cluster randomized trials (CRTs), drawing on the experience of carrying out a CRT within a community-based health insurance (CBHI) scheme in rural India. Our CRT is seeking to improve the equity impact--i.e., reduce the differential in claims submission for hospitalization between poor and less poor--of this CBHI in rural areas. Five main challenges are identified and discussed: 1) assigning control clusters, 2) blinding, 3) implementing interventions simultaneously, 4) minimizing leakage, and 5) piggy-backing on a changing scheme. These challenges are not likely to be unique to low-income settings, although the fifth challenge is particularly likely when working with relatively small and resource-constrained programs. While compromises to methodological best-practice may reduce internal validity, they make the intervention more 'real', and potentially more applicable, to other programs and settings. Further, careful documentation of compromises allows them to be considered in the final analysis.
本文借鉴在印度农村社区医疗保险(CBHI)计划中开展整群随机试验(CRT)的经验,探讨了在整群随机试验背景下实施公共卫生干预措施所面临的后勤挑战。我们的整群随机试验旨在提高该农村社区医疗保险在公平性方面的影响,即减少贫困和非贫困人群在住院理赔方面的差异。本文识别并讨论了五个主要挑战:1)分配对照群组;2)设盲;3)同时实施干预措施;4)尽量减少渗漏;5)依托不断变化的计划。尽管第五个挑战在处理规模相对较小且资源有限的项目时尤为突出,但这些挑战并非低收入环境所独有。虽然对方法学最佳实践的折衷可能会降低内部效度,但它们会使干预措施对其他项目和环境更“真实”,也可能更具适用性。此外,对这些折衷进行仔细记录有助于在最终分析中加以考虑。