Demonstrating a diagnostic test works is no longer enough. Clinicians and laboratories also need evidence on how to adopt it in everyday practice. Andrea Prinzi, PhD, MPH, SM(ASCP), explains how implementation science can help infectious disease and clinical microbiology teams turn evidence into routine care.
Implementation science is gaining popularity, but it has been around far longer than many realize, says Andrea Prinzi, PhD, MPH, SM(ASCP), director of scientists, Global Medical Affairs, at bioMérieux. At its core, the field aims to close what researchers call the "know-do gap." This is the distance between an intervention proven effective in the literature or written into guidelines and its consistent use in routine clinical practice.
Prinzi says the discipline is especially relevant to infectious diseases and clinical microbiology. New therapies and in vitro diagnostic tests depend heavily on context, workflows, and clinician behavior. She also stresses implementation science is a formal field with established theories, models, and frameworks. Rather than an informal review of workflows, it offers a rigorous, systematic way to study how an intervention gets adopted.
Clinical microbiology faces a unique challenge, Prinzi notes. Classic implementation science would never implement an intervention before its effectiveness was demonstrated. With diagnostic tests, however, laboratories often need to establish effectiveness and understand adoption at the same time.
"There's some unique approaches in implementation science that can help with that, called hybrid effectiveness-implementation designs. So, if you're studying the effectiveness or impact of a diagnostic test, you could move it into one of these types of study designs if you want to also understand how it might be implemented," Prinzi said. "And that's something I think clinical microbiologists should start looking into because it's the kind of data I don't think we always have on hand, and it really helps support the understanding of how a test really works in the real world."
For infectious disease clinicians and researchers, Prinzi says this is where much of clinical outcomes research is heading. Showing an intervention works is no longer sufficient on its own. Systems change, payer policies, and access to tests and therapies in areas of need all increasingly demand evidence on how an intervention performs in context.
She points to rapid phenotypic antimicrobial susceptibility testing for bloodstream infections as a clear example. As new data emerge, other barriers unrelated to test performance are surfacing, from transitions of care to whether oral antibiotics are available in the setting where a test is deployed.
"The test may perform beautifully or do what you think it does, but if those things aren't in place, how do you actually adopt something like this in the real world," Prinzi said. "Same thing with when guidelines are made. Sometimes guidelines are developed, but then it takes a while for the guidelines to actually get used in clinical practice. Implementation science could help infectious disease clinicians get guidelines into practice."
Implementation science overlaps with quality improvement, change management, and systems change. Prinzi acknowledges the number of available theories, models, and frameworks can feel overwhelming, and says there is no single right way to combine them. The best approach depends on factors such as an organization's readiness for change, she says. A system-wide initiative calls for a different strategy than introducing a new test into a single laboratory.
For those new to the field, Prinzi recommends freely available online toolkits. Different tools help teams assess readiness for change, identify barriers and facilitators to implementing an evidence-based intervention, and measure outcomes after implementation.
