An evidence integration triangle for aligning science with policy and practice.

Over-reliance on decontextualized, standardized implementation of efficacy evidence has contributed to slow integration of evidence-based interventions into health policy and practice. This article describes an "evidence integration triangle" (EIT) to guide translation, implementation, prevention efforts, comparative effectiveness research, funding, and policymaking. The EIT emphasizes interactions among three related components needed for effective evidence implementation: (1) practical evidence-based interventions; (2) pragmatic, longitudinal measures of progress; and (3) participatory implementation processes. At the center of the EIT is active engagement of key stakeholders and scientific evidence and attention to the context in which a program is implemented. The EIT model is a straightforward framework to guide practice, research, and policy toward greater effectiveness and is designed to be applicable across multiple levels-from individual-focused and patient-provider interventions, to health systems and policy-level change initiatives.

Harmonized patient-reported data elements in the electronic health record: supporting meaningful use by primary care action on health behaviors and key psychosocial factors.

BACKGROUND: Electronic health records (EHR) have the potential to improve patient care through efficient access to complete patient health information. This potential may not be reached because many of the most important determinants of health outcome are rarely included. Successful health promotion and disease prevention requires patient-reported data reflecting health behaviors and psychosocial issues. Furthermore, there is a need to harmonize this information across different EHR systems. METHODS: To fill this gap a three-phased process was used to conceptualize, identify and recommend patient-reported data elements on health behaviors and psychosocial factors for the EHR. Expert panels (n=13) identified candidate measures (phase 1) that were reviewed and rated by a wide range of health professionals (n=93) using the grid-enabled measures wiki social media platform (phase 2). Recommendations were finalized through a town hall meeting with key stakeholders including patients, providers, researchers, policy makers, and representatives from healthcare settings (phase 3). RESULTS: Nine key elements from three areas emerged as the initial critical patient-reported elements to incorporate systematically into EHR--health behaviors (eg, exercise), psychosocial issues (eg, distress), and patient-centered factors (eg, demographics). Recommendations were also made regarding the frequency of collection ranging from a single assessment (eg, demographic characteristics), to annual assessment (eg, health behaviors), or more frequent (eg, patient goals). CONCLUSIONS: There was strong stakeholder support for this initiative reflecting the perceived value of incorporating patient-reported elements into EHR. The next steps will include testing the feasibility of incorporating these elements into the EHR across diverse primary care settings.