Implementation Science at UW

Research Methods in Implementation Science

A broad and inclusive definition defines implementation science as a systematic, scientific approach to ask and answer questions about how we get “what works” to people who need it, for as long as they need it, with greater speed, fidelity, efficiency, quality and relevant coverage.

This definition allows for the application of at least ten research methods from a broad range of disciplines in order to understand and improve the determinants, processes, and outcomes of implementation and, ultimately, scale-up and sustainability to achieve population-level health benefits.

While this selection of research methods is not exhaustive, together they provide a set of tools that are used to assess and improve implementation and scale-up of health interventions.

Graphic depicting the 10 main research methods used in implementation science.

These methods allow exploration of the continuum consisting of three categories of outcomes:

  • proximal implementation outcomes – acceptability, appropriateness, adoption, costs, feasibility, fidelity, penetration, and sustainability
  • intermediate service delivery outcomes – efficiency, equity, timeliness, and patient-centeredness
  • distal health outcomes
Open Access articles will be marked with ✪
Please note some journals will require subscriptions to access a linked article.
Definition: Defined by the developers as the 'mentored, iterative application of a systems analysis tool and related improvement approach to provide facility-level staff and managers with a holistic view of their system’s performance, identify which steps in the [care] cascade are the highest priority for improvement and which bottlenecks are modifiable, and test contextually appropriate solutions.'1

Examples of use:
Definition: Routine surveillance data from control and experimental groups can be used illustrate the performance or impact of new policies and programs in an environment.

Examples of use: