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.

OBJECTIVEReasons for failing to initiate prescribed insulin (primary nonadherence) are poorly understood. We investigated barriers to insulin initiation following a new prescription.RESEARCH DESIGN AND METHODSWe surveyed insulin-naïve patients with poorly controlled type 2 diabetes, already treated with two or more oral agents who were recently prescribed insulin. We compared responses for respondents prescribed, but never initiating, insulin (n = 69) with those dispensed insulin (n = 100).RESULTSSubjects failing to initiate prescribed insulin commonly reported misconceptions regarding insulin risk (35% believed that insulin causes blindness, renal failure, amputations, heart attacks, strokes, or early death), plans to instead work harder on behavioral goals, sense of personal failure, low self-efficacy, injection phobia, hypoglycemia concerns, negative impact on social life and job, inadequate health literacy, health care provider inadequately explaining risks/benefits, and limited insulin self-management training.CONCLUSIONSPrimary adherence for insulin may be improved through better provider communication regarding risks, shared decision making, and insulin self-management training.

Background: Helping patients navigate the complex and fragmented US health care system and coordinating their care are central to the patient-centered medical home. We evaluated the pilot use of a patient navigator (PN), someone who helps patients use the health care system effectively and efficiently, in primary care practices.Methods: This study was a cross-case comparative analysis of 4 community practices that implemented patient navigation. Project meeting notes, PN activity logs and debriefings, physician interviews, and patient/family member interviews were analyzed using a grounded approach.Results: Seventy-five mostly female, elderly patients received navigation services from a social worker. The PN typically helped patients obtain social services and navigate health coverage and complex referrals. Availability of workspace for PN, interaction with practice members, and processes used for selecting and referring patients affected PN collaboration with and integration into practices. Patients found PN services very helpful, and physicians viewed the PN as someone carrying out new tasks that the practice was not previously doing.Conclusions

PURPOSE Social network analysis (SNA) provides a way of quantitatively analyzing relationships among people or other information-processing agents. Using 2 practices as illustrations, we describe how SNA can be used to characterize and compare communication patterns in primary care practices.METHODS Based on data from ethnographic fi eld notes, we constructed matrices identifying how practice members interact when practice-level decisions are made. SNA software (UCINet and KrackPlot) calculates quantitative measures of network structure including density, centralization, hierarchy and clustering coeffi cient. The software also generates a visual representation of networks through network diagrams. RESULTSThe 2 examples show clear distinctions between practices for all the SNA measures. Potential uses of these measures for analysis of primary care practices are described.CONCLUSIONS SNA can be useful for quantitative analysis of interaction patterns that can distinguish differences among primary care practices. INTRODUCTIONP rimary care practices are complex systems that are characterized by dynamic patterns of interactivity among practice members and their environment. [1][2][3] One feature of complex systems is the property of emergence, which is the tendency of organized patterns to emerge that cannot be predicted from the properties of individual parts of the system. 4 Thus, to understand how primary care practices function, it is necessary to study not only the individuals within the practice or individual practice components but also the relationships among individuals.5 Study of such patterns and how they change with time or in response to interventions requires an ability to look at the entire complex web of relationships and interactions within a primary care practice. Although qualitative description 6-10 and practice genograms 11 have demonstrated utility for understanding the complex interactions in practices, a tool that captures quantitative aspects of the patterns of relationships within practices would be a useful aid in studies of primary care practices. Social network analysis (SNA) is such a tool.SNA 13 More recent work examines the association of these quantitative measures with organizational performance outcomes. Cummings and Cross, for example, found that degree of hierarchy, core-periphery structure, and structural holes of leaders correlated negatively with performance in 182 work groups in a large telecommunications company, 14 and Aydin et al found that increased network communication density was associated with higher use of an electronic medical record system by nurse practitioners and physician' s assistants. 15 There have also been studies showing how network parameters change with time. Shah, for example showed that network centrality decreased after downsizing in a consumer electronics fi rm, 16 whereas Burkhardt and Brass documented increased network centrality after introduction of a new computer system in a federal agency. 17In this article, using data from 2 primary ...

OBJECTIVETo examine demographic, socioeconomic, and biological risk factors for all-cause, cardiovascular, and noncardiovascular mortality in patients with type 2 diabetes over 8 years and to construct mortality prediction equations.RESEARCH DESIGN AND METHODSBeginning in 2000, survey and medical record information was obtained from 8,334 participants in Translating Research Into Action for Diabetes (TRIAD), a multicenter prospective observational study of diabetes care in managed care. The National Death Index was searched annually to obtain data on deaths over an 8-year follow-up period (2000–2007). Predictors examined included age, sex, race, education, income, smoking, age at diagnosis of diabetes, duration and treatment of diabetes, BMI, complications, comorbidities, and medication use.RESULTSThere were 1,616 (19%) deaths over the 8-year period. In the most parsimonious equation, the predictors of all-cause mortality included older age, male sex, white race, lower income, smoking, insulin treatment, nephropathy, history of dyslipidemia, higher LDL cholesterol, angina/myocardial infarction/other coronary disease/coronary angioplasty/bypass, congestive heart failure, aspirin, β-blocker, and diuretic use, and higher Charlson Index.CONCLUSIONSRisk of death can be predicted in people with type 2 diabetes using simple demographic, socioeconomic, and biological risk factors with fair reliability. Such prediction equations are essential for computer simulation models of diabetes progression and may, with further validation, be useful for patient management.

OBJECTIVE -To examine racial/ethnic and economic variation in cost-related medication underuse among insured adults with diabetes.RESEARCH DESIGN AND METHODS -We surveyed 5,086 participants from the multicenter Translating Research Into Action for Diabetes Study. Respondents reported whether they used less medication because of cost in the past 12 months. We examined unadjusted and adjusted rates of cost-related medication underuse, using hierarchical regression, to determine whether race/ethnicity differences still existed after accounting for economic, health, and other demographic variables.RESULTS -Participants were 48% white, 14% African American, 14% Latino, 15% Asian/ Pacific Islander, and 8% other. Overall, 14% reported cost-related medication underuse. Unadjusted rates were highest for Latinos (23%) and African Americans (17%) compared with whites (13%), Asian/Pacific Islanders (11%), and others (15%). In multivariate analyses, race/ethnicity significantly predicted cost-related medication underuse (P ϭ 0.048). However, adjusted rates were only slightly higher for Latinos (14%) than whites (10%) (P ϭ 0.026) and were not significantly different for African Americans (11%), Asian/Pacific Islanders (7%), and others (11%). Income and out-of-pocket drug costs showed the greatest differences in adjusted rates of cost-related medication underuse (15 vs. 5% for participants with income Յ$25,000 vs. Ͼ$50,000 and 24 vs. 7% for participants with out-of-pocket costs Ͼ$150 per month vs. Յ$50 per month.CONCLUSIONS -One in seven participants reported cost-related medication underuse. Rates were highest among African Americans and Latinos but were related to lower incomes and higher out-of-pocket drug costs in these groups. Interventions to decrease racial/ethnic disparities in cost-related medication underuse should focus on decreasing financial barriers to medications. Diabetes Care 31:261-266, 2008

This workaround typology provides a framework for EHR users to identify and address workarounds in their own practices, and for researchers to examine the effect of different types of EHR workarounds on patient safety, care quality, and efficiency.

PURPOSEThe Using Learning Teams for Refl ective Adaptation (ULTRA) study used facilitated refl ective adaptive process (RAP) teams to enhance communication and decision making in hopes of improving adherence to multiple clinical guidelines; however, the study failed to show signifi cant clinical improvements. The purpose of this study was to examine qualitative data from 25 intervention practices to understand how they engaged in a team-based collaborative change management strategy and the types of issues they addressed. METHODSWe analyzed fi eld notes and interviews from a multimethod practice assessment, as well as fi eld notes and audio-taped recordings from RAP meetings, using an iterative group process and an immersion-crystallization approach.RESULTS Despite a history of not meeting regularly, 18 of 25 practices successfully convened improvement teams. There was evidence of improved practicewide communication in 12 of these practices. At follow-up, 8 practices continued RAP meetings and found the process valuable in problem solving and decision making. Seven practices failed to engage in RAP primarily because of key leaders dominating the meeting agenda or staff members hesitating to speak up in meetings. Although the number of improvement targets varied considerably, most RAP teams targeted patient care-related issues or practice-level organizational improvement issues. Not a single practice focused on adherence to clinical care guidelines.CONCLUSION Primary care practices can successfully engage in facilitated team meetings; however, leaders must be engaged in the process. Additional strategies are needed to engage practice leaders, particularly physicians, and to target issues related to guideline adherence. Ann Fam Med 2010;8:425-432. doi:10.1370/afm.1159. INTRODUCTIONThe quality of care in the United States is substandard, 1 and the early promise of improving care by translating research into practice has been disappointing. 2,3 Initial efforts to improve quality often target improving knowledge, attitudes, and behaviors of individual health professionals by using such strategies as audit and feedback, reminder systems, continuing medical education, and educational outreach. 4 These strategies have been found to produce modest change. 2,3,[5][6][7][8] Even when improvement changes are adopted, they are often not sustained over time 7 and may deteriorate after practice members' attention shifts elsewhere.8 Sustaining change appears to be an active process that requires continual attention as innovations are adapted to fi t continually evolving environments.9,10 Additionally, small, independent primary care practices often lack the resources 426T E A M -BA SED CHANGE M A NAGEMENT or motivation needed to develop quality improvement strategies that can address multiple clinical issues. 11The substantial, broad improvements required for optimal primary care cannot be achieved by focusing improvement efforts on specifi c diseases or on individual professional behavior. In fact, primary care pract...