Smith Natalie Riva, Knocke Kathleen E, Hassmiller Lich Kristen
Department of Social and Behavioral Sciences, Harvard TH Chan School of Public Health, Harvard University, Boston, MA, 02115, USA.
Department of Health Policy and Management, Gillings School of Global Public Health, UNC Chapel Hill, Chapel Hill, USA.
Implement Sci Commun. 2022 Jul 30;3(1):83. doi: 10.1186/s43058-022-00330-1.
The process of implementing evidence-based interventions, programs, and policies is difficult and complex. Planning for implementation is critical and likely plays a key role in the long-term impact and sustainability of interventions in practice. However, implementation planning is also difficult. Implementors must choose what to implement and how best to implement it, and each choice has costs and consequences to consider. As a step towards supporting structured and organized implementation planning, we advocate for increased use of decision analysis.
When applied to implementation planning, decision analysis guides users to explicitly define the problem of interest, outline different plans (e.g., interventions/actions, implementation strategies, timelines), and assess the potential outcomes under each alternative in their context. We ground our discussion of decision analysis in the PROACTIVE framework, which guides teams through key steps in decision analyses. This framework includes three phases: (1) definition of the decision problems and overall objectives with purposeful stakeholder engagement, (2) identification and comparison of different alternatives, and (3) synthesis of information on each alternative, incorporating uncertainty. We present three examples to illustrate the breadth of relevant decision analysis approaches to implementation planning.
To further the use of decision analysis for implementation planning, we suggest areas for future research and practice: embrace model thinking; build the business case for decision analysis; identify when, how, and for whom decision analysis is more or less useful; improve reporting and transparency of cost data; and increase collaborative opportunities and training.
实施基于证据的干预措施、项目和政策的过程困难且复杂。实施规划至关重要，并且可能在实践中干预措施的长期影响和可持续性方面发挥关键作用。然而，实施规划也很困难。实施者必须选择实施什么以及如何以最佳方式实施，并且每个选择都有需要考虑的成本和后果。作为支持结构化和有组织的实施规划的一步，我们主张更多地使用决策分析。
当应用于实施规划时，决策分析指导用户明确界定感兴趣的问题，概述不同的计划（例如，干预措施/行动、实施策略、时间表），并在其背景下评估每个替代方案的潜在结果。我们基于主动（PROACTIVE）框架讨论决策分析，该框架指导团队完成决策分析的关键步骤。这个框架包括三个阶段：（1）通过有目的的利益相关者参与来界定决策问题和总体目标，（2）识别和比较不同的替代方案，以及（3）综合每个替代方案的信息，纳入不确定性因素。我们给出三个例子来说明实施规划中相关决策分析方法的广度。
为了进一步将决策分析用于实施规划，我们提出了未来研究和实践的领域：采用模型思维；为决策分析建立商业案例；确定决策分析在何时、如何以及对谁更有用或不太有用；提高成本数据的报告和透明度；以及增加合作机会和培训。
