September 9, 2016

Helping primary care practices decide whether to adopt proven programs



To be, or not to be, put into practice? Leah Tuzzio describes a decision-to-implement worksheet for evidence-based interventions

Leah Tuzzio, MPH, is a research associate at Group Health Research Institute

Doing health services research, I really want to make discoveries about what works—and what doesn’t—to make health care more efficient and effective at helping people to be healthy. And when new interventions are proven to work well, I want to see them be put into practice—and spread. But too often they aren’t, even when trusted journals or professional associations recommend them.

To be sure, not every positive finding from the endless production of new research will be relevant to each practice’s patients and priorities. Primary care clinicians and practice administrators need an assessment tool to use to evaluate whether to adapt—or adopt—recommended evidence-based interventions.

That’s just what my colleagues and I developed, through the University of Washington's Institute of Translational Health Sciences (ITHS), a Clinical and Translational Science Award (CTSA). This tool, called the Decision-to-Implement Worksheet, is now part of the Primary Care Evidence Review Toolkit at

Development and testing

In “Decision-to-Implement Worksheet for Evidence-Based Interventions: From the WWAMI Region Practice and Research Network” in the Journal of the American Board of Family Medicine, we describe developing and testing the worksheet.

We developed it based on dissemination and implementation theory with input from colleagues at other CTSAs who are practicing clinicians with expertise in evidence translation. After changing it based on their feedback, we tested it with 26 primary care clinicians who are Washington, Wyoming, Alaska, Montana, Idaho (WWAMI) region Practice and Research Network (WPRN) practice champions. Their feedback led to further refinements.

These clinicians assessed a convenience sample of four interventions published by GHRI-associated researchers.  Their likelihood of implementation ranged from 2 to 3.5 on a scale of 1 (low) to 5 (high).

What mattered most in this decision making was whether each innovation was:

  • Simple to implement;
  • Testable before fully implementing; and
  • Modifiable to meet the practice’s needs.

Pass it on

We hope others will use, adapt, and report on the tool to build shared learning about best practices for fostering the uptake of evidence into community practice. My co-authors are Karin Johnson, PhD; Anne Renz, MPH; Laura-Mae Baldwin, MD, MPH; and Michael Parchman, MD, MPH. The National Center for Advancing Translational Sciences of the National Institutes of Health supports our work under Award Number UL1TR000423.


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