What AHRQ Learned While Working to Transform Primary Care.

Building on previous efforts to transform primary care, the Agency for Healthcare Research and Quality (AHRQ) launched EvidenceNOW: Advancing Heart Health in 2015. This 3-year initiative provided external quality improvement support to small and medium-size primary care practices to implement evidence-based cardiovascular care. Despite challenges, results from an independent national evaluation demonstrated that the EvidenceNOW model successfully boosted the capacity of primary care practices to improve quality of care, while helping to advance heart health. Reflecting on AHRQ's own learnings as the funder of this work, 3 key lessons emerged: (1) there will always be surprises that will require flexibility and real-time adaptation; (2) primary care transformation is about more than technology; and (3) it takes time and experience to improve care delivery and health outcomes. EvidenceNOW taught us that lasting practice transformation efforts need to be responsive to anticipated and unanticipated changes, relationship-oriented, and not tied to a specific disease or initiative. We believe these lessons argue for a national primary care extension service that provides ongoing support for practice transformation.

Testing consumers' comprehension of quality measures using alternative reporting formats.

CMS has publicly reported nursing home quality measures since 2002, but research has shown that many users do not understand them. Alternative visual displays may improve comprehension. We developed seven reporting templates in different formats, including bar graphs like those displayed on the CMS Nursing Home Compare Web site www.medicare.gov, and tested them with 90 individuals age 45-75, using structured protocols. Tests of significance were conducted, and statistically significant findings identified. Fewer than one-half the respondents accurately interpreted bar graphs as currently displayed on the Nursing Home Compare Web site. Respondents made fewest errors on templates using words to characterize performance as better, average, or worse.