Last month, EvidenceConneKTion introduced the concept of implementation science laboratories (IS labs). Mainly, we focused on the mutual benefits that IS labs can bring to both health research and health system communities. Most importantly, IS labs bring together the knowledge and skills of health system employees and academic researchers to improve the likelihood of successful healthcare changes. Implementation practitioners have critical, sometimes tacit, knowledge of health care system dynamics. Meanwhile, implementation scientists have research expertise and can contribute thinking required for theory-based project planning. Both types of knowledge are essential for successful implementation project planning.

To really understand IS labs, we first have to clarify the difference between implementation and implementation science.

In health care, implementation is the act of creating and applying road maps to use new evidence to change practice. This is the work that implementation practitioners are tasked to do in order to improve patient outcomes in their local contexts.

Implementation science, as defined by the National Institute of Health, is “the study of methods to promote integration of research findings and evidence into healthcare policy and practice.” In other words implementation science is the study of what works, when, why, how, and for whom. This is the theory-driven intervention design and evaluation of new practices that researchers conduct.

Implementation science activities are all geared towards helping researchers understand why or how an implementation approach creates the intended change (or not!). One of the central activities required to make this knowledge is evaluation of the implementation strategy. All implementation projects should include an evaluation component. Traditionally, teams that design, pilot, and evaluate high-quality projects are academic-health system collaborations, much like the collaborations that would be facilitated by an IS lab. However, without an IS lab infrastructure to support ongoing collaboration, projects suffer from common pitfalls:

• They tend to be one-off studies, forcing teams to undertake a massive amount of legwork for each separate project.

• This leg work requires enormous amounts of time and skill for activities such as building partnerships, negotiating agreements between academic institutions and healthcare systems, and conducting studies.

• Because partnerships disband after each pilot, there is no mechanism to communicate lessons between implementation research projects. This not only drastically limits the potential for the people involved to reflect and learn, but means that often actors in the system repeat mistakes from project to project.

In another sense, an IS lab can enable people to create processes to advance theory in implementation science. Leadership in IS labs can identify research and practice priorities and develop standardized evaluation measures and mechanisms. In this way, projects developed with IS labs can be coordinated and designed in ways that uncover comparative effectiveness of different implementation methods.

As an infrastructure and a process, an IS lab can contribute to broader learning health systems in ways that single-study research partnerships, no matter how good they are, simply cannot.

What exactly is a learning health system and how would an IS lab fit into one? Join us in our next EvidenceConneKTion to hear about the power of learning health systems and the potential impact of IS labs.