Background: Many interventions found to be effective in health services research studies fail to translate into meaningful patient care outcomes across multiple contexts. Health services researchers recognize the need to evaluate not only summative outcomes but also formative outcomes to assess the extent to which implementation is effective in a specific setting, prolongs sustainability, and promotes dissemination into other settings. Many implementation theories have been published to help promote effective implementation. However, they overlap considerably in the constructs included in individual theories, and a comparison of theories reveals that each is missing important constructs included in other theories. In addition, terminology and definitions are not consistent across theories. We describe the Consolidated Framework For Implementation Research (CFIR) that offers an overarching typology to promote implementation theory development and verification about what works where and why across multiple contexts.

BackgroundMuch research does not address the practical needs of stakeholders responsible for introducing health care delivery interventions into organizations working to achieve better outcomes. In this article, we present an approach to using the Consolidated Framework for Implementation Research (CFIR) to guide systematic research that supports rapid-cycle evaluation of the implementation of health care delivery interventions and produces actionable evaluation findings intended to improve implementation in a timely manner.MethodsTo present our approach, we describe a formative cross-case qualitative investigation of 21 primary care practices participating in the Comprehensive Primary Care (CPC) initiative, a multi-payer supported primary care practice transformation intervention led by the Centers for Medicare and Medicaid Services. Qualitative data include observational field notes and semi-structured interviews with primary care practice leadership, clinicians, and administrative and medical support staff. We use intervention-specific codes, and CFIR constructs to reduce and organize the data to support cross-case analysis of patterns of barriers and facilitators relating to different CPC components.ResultsUsing the CFIR to guide data collection, coding, analysis, and reporting of findings supported a systematic, comprehensive, and timely understanding of barriers and facilitators to practice transformation. Our approach to using the CFIR produced actionable findings for improving implementation effectiveness during this initiative and for identifying improvements to implementation strategies for future practice transformation efforts.ConclusionsThe CFIR is a useful tool for guiding rapid-cycle evaluation of the implementation of practice transformation initiatives. Using the approach described here, we systematically identified where adjustments and refinements to the intervention could be made in the second year of the 4-year intervention. We think the approach we describe has broad application and encourage others to use the CFIR, along with intervention-specific codes, to guide the efficient and rigorous analysis of rich qualitative data.Trial registration NCT02318108 Electronic supplementary materialThe online version of this article (doi:10.1186/s13012-017-0550-7) contains supplementary material, which is available to authorized users.

BackgroundAlong with the increasing prevalence of chronic illness has been an increase in interventions, such as nurse case management programs, to improve outcomes for patients with chronic illness. Evidence supports the effectiveness of such interventions in reducing patient morbidity, mortality, and resource utilization, but other studies have produced equivocal results. Often, little is known about how implementation of an intervention actually occurs in clinical practice. While studies often assume that interventions are used in clinical practice exactly as originally designed, this may not be the case. Thus, fidelity of an intervention's implementation reflects how an intervention is, or is not, used in clinical practice and is an important factor in understanding intervention effectiveness and in replicating the intervention in dissemination efforts. The purpose of this paper is to contribute to the understanding of implementation science by (a) proposing a methodology for measuring fidelity of implementation (FOI) and (b) testing the measure by examining the association between FOI and intervention effectiveness.MethodsWe define and measure FOI based on organizational members' level of commitment to using the distinct components that make up an intervention as they were designed. Semistructured interviews were conducted among 18 organizational members in four medical centers, and the interviews were analyzed qualitatively to assess three dimensions of commitment to use--satisfaction, consistency, and quality--and to develop an overall rating of FOI. Mixed methods were used to explore the association between FOI and intervention effectiveness (inpatient resource utilization and mortality).ResultsPredictive validity of the FOI measure was supported based on the statistical significance of FOI as a predictor of intervention effectiveness. The strongest relationship between FOI and intervention effectiveness was found when an alternative measure of FOI was utilized based on individual intervention components that had the greatest variation across medical centers.ConclusionsIn addition to contextual factors, implementation research needs to consider FOI as an important factor in influencing intervention effectiveness. Our proposed methodology offers a systematic means for understanding organizational members' use of distinct intervention components, assessing the reasons for variation in use across components and organizations, and evaluating the impact of FOI on intervention effectiveness.

Improving providers' experiences with and uptake of CCM will require addressing several challenges, including the upfront investment for CCM set-up and the time required to provide CCM to more complex patients.

Primary care practices are increasingly asked to engage patients in improving care delivery. We report early experiences with Patient and Family Advisory Councils (PFACs) from interviews of patients and practice staff in the Comprehensive Primary Care initiative, and identify ways to improve PFACs. Patients and practice staff report PFACs help practices elicit patient feedback and, in response, improve care delivery. Nonetheless, there are areas for refinement, including recruiting more diverse patients, providing an orientation to members, overcoming reticence of some patients to raise issues, and increasing transparency by sharing progress with PFAC members and patients in the practice more generally.

While there has been considerable attention devoted to the deployment of electronic health record (EHR) systems, there has been far less attention given to their appropriation for use in clinical encounters — particularly in the context of complex, chronic illness. The Department of Veterans’ Affairs (VA) has been at the forefront of EHR adoption and, as such, provides a unique opportunity to examine a mature EHR system in widespread use. Moreover, with a high prevalence of diabetes in its patient population, the VA provides a useful platform for examining EHR use in the context of chronic disease care. We conducted a sequential, exploratory qualitative study at two VA Medical Centers in the Midwest. First, we conducted observations of 64 clinical consultations with diabetes patients. These observations involved 31 different health care providers. Second, using insights from these observations, we conducted in-depth, semi-structured interviews with 39 health care providers focusing on their use of information in diabetes patient care. Field notes and interview transcripts were analyzed using a grounded theory approach. Our analysis generated several categories of EHR use in clinical encounters: priming, structuring, assessing, informing, and continuing. We also outline some mismatches between EHR system design and VA diabetes care practices. We conclude by discussing implications of these emergent system uses for improving the software design of EHRs to better support chronic disease care, as well as for our understanding of the integration of technologies in health care.

BackgroundDiabetes is predicted to increase in incidence by 42% from 1995 to 2025. Although most adults with diabetes seek care from primary care practices, adherence to treatment guidelines in these settings is not optimal. Many practices lack the infrastructure to monitor patient adherence to recommended treatment and are slow to implement changes critical for effective management of patients with chronic conditions. Supporting Practices to Adopt Registry-Based Care (SPARC) will evaluate effectiveness and sustainability of a low-cost intervention designed to support work process change in primary care practices and enhance focus on population-based care through implementation of a diabetes registry.MethodsSPARC is a two-armed randomized controlled trial (RCT) of 30 primary care practices in the Virginia Ambulatory Care Outcomes Research Network (ACORN). Participating practices (including control groups) will be introduced to population health concepts and tools for work process redesign and registry adoption at a meeting of practice-level implementation champions. Practices randomized to the intervention will be assigned study peer mentors, receive a list of specific milestones, and have access to a physician informaticist. Peer mentors are clinicians who successfully implemented registries in their practices and will help champions in the intervention practices throughout the implementation process. During the first year, peer mentors will contact intervention practices monthly and visit them quarterly. Control group practices will not receive support or guidance for registry implementation. We will use a mixed-methods explanatory sequential design to guide collection of medical record, participant observation, and semistructured interview data in control and intervention practices at baseline, 12 months, and 24 months. We will use grounded theory and a template-guided approach using the Consolidated Framework for Implementation Research to analyze qualitative data on contextual factors related to registry adoption. We will assess intervention effectiveness by comparing changes in patient-level hemoglobin A1c scores from baseline to year 1 between intervention and control practices.DiscussionFindings will enhance our understanding of how to leverage existing practice resources to improve diabetes care in primary care practices by implementing and using a registry. SPARC has the potential to validate the effectiveness of low-cost implementation strategies that target practice change in primary care.Trial registrationNCT02318108Electronic supplementary materialThe online version of this article (doi:10.1186/s13012-015-0232-2) contains supplementary material, which is available to authorized users.

BACKGROUND: Longitudinal care management (LCM) for high-risk patients is a cornerstone of primary care models aiming to improve quality and reduce costs. OBJECTIVE: Describe the extent to which LCM was implemented in the second year of Comprehensive Primary Care Plus (CPC+), and barriers to and facilitators of implementation. DESIGN: Mixed-methods. PARTICIPANTS: Quantitative: 2715 practices participating in CPC+ in 2018. Qualitative: Interviews with practitioners and staff in 23 representative CPC+ practices. MAIN MEASURES: Across all CPC+ practices, we report median percentages of empaneled patients placed in the highest-risk tiers and, of those, the median percentage receiving LCM. Across 23 CPC+ practices, we report qualitative findings on LCM implementation. KEY RESULTS: While practices reported benefits of LCM, a small proportion of patients received LCM. Practices placed 2.4% (median) of patients in the highest-risk tier; of these, 30% (median) received LCM. Practices placed 10% (median) of patients in the second-highest-risk tier; of these, 7% (median) received LCM. Interviews revealed LCM uptake across tiers was low because of insufficient care manager staffing. Other challenges included lack of practitioner buy-in to using risk stratification to identify high-risk patients, patients' reluctance to engage in LCM or change behaviors, and limited health information technology functionality for developing, maintaining, and accessing high-risk patients' care plans. Facilitators included embedding care managers within practices and electronic health record functionalities that support LCM. CONCLUSIONS: Despite substantial financial and other supports, and practices' perceived benefits of LCM, insufficient care manager staffing and other barriers have limited its potential in CPC+ to date. To expand LCM's reach, practices need additional care managers, training to overcome barriers to patient engagement, better identification of patients who might benefit from LCM, improved information technology tools for risk stratification and care plans, and more practitioner buy-in to risk stratification.