Department of Psychiatry, Columbia University Irving Medical Center, New York, NY; HIV Center for Clinical and Behavioral Studies, New York State Psychiatric Institute and Columbia University, New York; Department of Sociomedical Sciences, Columbia University Mailman School of Public Health, New York, NY.
Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD.
Ann Epidemiol. 2023 Sep;85:45-50. doi: 10.1016/j.annepidem.2023.03.008. Epub 2023 Apr 2.
We propose the observational-implementation hybrid approach-the incorporation of implementation science methods and measures into observational studies to collect information that would allow researchers to anticipate, estimate, or infer the effects of interventions and implementation strategies. Essentially, we propose that researchers collect implementation data early in the research pipeline, in situations where they might not typically be thinking about implementation science. We describe three broad contextual scenarios through which the observational-implementation hybrid approach would most productively be applied. The first application is for observational cohorts that individually enroll participants-either for existing (to which implementation concepts could be added) or for newly planned studies. The second application is with routinely collected program data, at either the individual or aggregate levels. The third application is to the collection of data from study participants enrolled in an observational cohort study who are also involved in interventions linked to that study (e.g., collecting data about their experiences with those interventions). Examples of relevant implementation data that could be collected as part of observational studies include factors relevant to transportability, participant preferences, and participant/provider perspectives regarding interventions and implementation strategies. The observational-implementation hybrid model provides a practical approach to make the research pipeline more efficient and to decrease the time from observational research to health impact. If this approach is widely adopted, observational and implementation science studies will become more integrated; this will likely lead to new collaborations, will encourage the expansion of epidemiological training, and, we hope, will push both epidemiologists and implementation scientists to increase the public health impact of their work.
我们提出了观察性实施混合方法——将实施科学方法和措施纳入观察性研究中，以收集能够让研究人员预测、估计或推断干预措施和实施策略效果的信息。本质上，我们建议研究人员在研究管道的早期阶段收集实施数据，在他们可能通常不会考虑实施科学的情况下。我们描述了三种广泛的背景情况，通过这些情况，观察性实施混合方法将最有效地得到应用。第一种应用是针对单独招募参与者的观察性队列——无论是针对现有的（可以添加实施概念）还是新计划的研究。第二种应用是使用常规收集的项目数据，无论是在个体还是群体层面。第三种应用是收集参与观察性队列研究的研究参与者的数据，这些参与者也参与与该研究相关的干预措施（例如，收集他们对这些干预措施的经验数据）。作为观察性研究的一部分可以收集的相关实施数据包括与可转移性、参与者偏好以及参与者/提供者对干预措施和实施策略的看法相关的因素。观察性实施混合模型提供了一种实用的方法，可以提高研究管道的效率，并缩短从观察性研究到对健康产生影响的时间。如果这种方法得到广泛采用，观察性和实施科学研究将更加融合；这可能会导致新的合作，鼓励扩大流行病学培训，并希望推动流行病学家和实施科学家提高他们工作的公共卫生影响力。
