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Background Though the knowledge base on implementation strategies is growing, much remains unknown about how to most effectively operationalize these strategies in diverse contexts. For example, while evidence shows that champions can effectively support implementation efforts in some circumstances, little has been reported on how to operationalize this role optimally in different settings, or on the specific pathways through which champions enact change. Methods This is a secondary analysis of data from a pragmatic trial comparing implementation strategies supporting the adoption of guideline-concordant cardioprotective prescribing in community health centers in the USA. Quantitative data came from the community health centers’ shared electronic health record; qualitative data sources included community health center staff interviews over 3 years. Using a convergent mixed-methods design, data were collected concurrently and merged for interpretation to identify factors associated with improved outcomes. Qualitative analysis was guided by the constant comparative method. As results from the quantitative and initial qualitative analyses indicated the essential role that champions played in promoting guideline-concordant prescribing, we conducted multiple immersion-crystallization cycles to better understand this finding. Results Five community health centers demonstrated statistically significant increases in guideline-concordant cardioprotective prescribing. A combination of factors appeared key to their successful practice change: (1) A clinician champion who demonstrated a sustained commitment to implementation activities and exhibited engagement, influence, credibility, and capacity; and (2) organizational support for the intervention. In contrast, the seven community health centers that did not show improved outcomes lacked a champion with the necessary characteristics, and/or organizational support. Case studies illustrate the diverse, context-specific pathways that enabled or prevented study implementers from advancing practice change. Conclusion This analysis confirms the important role of champions in implementation efforts and offers insight into the context-specific mechanisms through which champions enact practice change. The results also highlight the potential impact of misaligned implementation support and key modifiable barriers and facilitators on implementation outcomes. Here, unexamined assumptions and a lack of evidence-based guidance on how best to identify and prepare effective champions led to implementation support that failed to address important barriers to intervention success. Trial registration ClinicalTrials.gov , NCT02325531 . Registered 15 December 2014.

ObjectiveSocial deprivation is associated with worse asthma outcomes. The Social Deprivation Index is a composite measure of social determinants of health used to identify neighbourhood-level disadvantage in healthcare. Our objective was to determine if higher neighbourhood-level social deprivation is associated with documented asthma care quality measures among children treated at community health centres (CHCs).Methods (setting, participants, outcome measures)We used data from CHCs in 15 states in the Accelerating Data Value Across a National Community Health Center Network (ADVANCE). The sample included 34 266 children with asthma from 2008 to 2017, aged 3–17 living in neighbourhoods with differing levels of social deprivation measured using quartiles of the Social Deprivation Index score. We conducted logistic regression to examine the odds of problem list documentation of asthma and asthma severity, and negative binomial regression for rates of albuterol, inhaled steroid and oral steroid prescription adjusted for patient-level covariates.ResultsChildren from the most deprived neighbourhoods had increased rates of albuterol (rate ratio (RR)=1.22, 95% CI 1.13 to 1.32) compared with those in the least deprived neighbourhoods, while the point estimate for inhaled steroids was higher, but fell just short of significance at the alpha=0.05 level (RR=1.16, 95% CI 0.99 to 1.34). We did not observe community-level differences in problem list documentation of asthma or asthma severity.ConclusionsHigher neighbourhood-level social deprivation was associated with more albuterol and inhaled steroid prescriptions among children with asthma, while problem list documentation of asthma and asthma severity varied little across neighbourhoods with differing deprivation scores. While the homogeneity of the CHC safety net setting studied may mitigate variation in diagnosis and documentation of asthma, enhanced clinician awareness of differences in community risk could help target paediatric patients at risk of lower quality asthma care.

Background National leaders recommend documenting social determinants of health and actions taken to address social determinants of health in electronic health records, and a growing body of evidence suggests the health benefits of doing so. However, little evidence exists to guide implementation of social determinants of health documentation/action. Methods This paper describes a 5-year, mixed-methods, stepped-wedge trial with realist evaluation, designed to test the impact of providing 30 community health centers with step-by-step guidance on implementing electronic health record-based social determinants of health documentation. This guidance will entail 6 months of tailored support from an interdisciplinary team, including training and technical assistance. We will report on tailored support provided at each of five implementation steps; impact of tailored implementation support; a method for tracking such tailoring; and context-specific pathways through which these tailored strategies effect change. We will track the competencies and resources needed to support the study clinics’ implementation efforts. Discussion Results will inform how to tailor implementation strategies to meet local needs in real-world practice settings. Secondary analyses will assess impacts of social determinants of health documentation and referral-making on diabetes outcomes. By learning whether and how scalable, tailored implementation strategies help community health centers adopt social determinants of health documentation and action, this study will yield timely guidance to primary care providers. We are not aware of previous studies exploring implementation strategies that support adoption of social determinants of action using electronic health and interventions, despite the pressing need for such guidance. Trial registration clinicaltrials.gov, NCT03607617 , registration date: 7/31/2018—retrospectively registered

Background Disseminating care guidelines into clinical practice remains challenging, partly due to inadequate evidence on how best to help clinics incorporate new guidelines into routine care. This is particularly true in safety net community health centers (CHCs). Methods This pragmatic comparative effectiveness trial used a parallel mixed methods design. Twenty-nine CHC clinics were randomized to receive increasingly intensive implementation support (implementation toolkit (arm 1); toolkit + in-person training + training webinars (arm 2); toolkit + training + webinars + offered practice facilitation (arm 3)) targeting uptake of electronic health record (EHR) tools focused on guideline-concordant cardioprotective prescribing for patients with diabetes. Outcomes were compared across study arms, to test whether increased support yielded additive improvements, and with 137 non-study CHCs that share the same EHR as the study clinics. Quantitative data from the CHCs’ EHR were used to compare the magnitude of change in guideline-concordant ACE/ARB and statin prescribing, using adjusted Poisson regressions. Qualitative data collected using diverse methods (e.g., interviews, observations) identified factors influencing the quantitative outcomes. Results Outcomes at CHCs receiving higher-intensity support did not improve in an additive pattern. ACE/ARB prescribing did not improve in any CHC group. Statin prescribing improved overall and was significantly greater only in the arm 1 and arm 2 CHCs compared with the non-study CHCs. Factors influencing the finding of no additive impact included: aspects of the EHR tools that reduced their utility, barriers to providing the intended implementation support, and study design elements, e.g., inability to adapt the provided support. Factors influencing overall improvements in statin outcomes likely included a secular trend in awareness of statin prescribing guidelines, selection bias where motivated clinics volunteered for the study, and study participation focusing clinic staff on the targeted outcomes. Conclusions Efforts to implement care guidelines should: ensure adaptability when providing implementation support and conduct formative evaluations to determine the optimal form of such support for a given clinic; consider how study data collection influences adoption; and consider barriers to clinics’ ability to use/accept implementation support as planned. More research is needed on supporting change implementation in under-resourced settings like CHCs. Trial registration ClinicalTrials.gov , NCT02325531. Registered 15 December 2014.

Background Spreading effective, guideline-based cardioprotective care quality improvement strategies between healthcare settings could yield great benefits, particularly in under-resourced contexts. Understanding the diverse factors facilitating or impeding such guideline implementation could improve cardiovascular care quality and outcomes for vulnerable patients. Methods We sought to identify multi-level factors affecting uptake of cardioprotective care guidelines in community health centers (CHCs), within a successful trial of cross-setting implementation of an effective intervention. Quantitative analyses used multivariable logistic regression to examine in-person patient encounters at 10 CHCs from June 2011-May 2014. At these encounters, a point-of-care alert flagged adults with diabetes who were clinically indicated for, but not currently prescribed, cardioprotective medications. The main outcome measure was the rate of relevant prescriptions issued within two days of encounters. Qualitative analyses focused on CHC providers and staff, and, guided by the constant comparative method, were used to enhance understanding of the factors that influenced this prescribing. Results Recommended prescribing occurred at 13–16% of encounters with patients who were indicated for such prescribing. The odds of this prescribing were higher when the patient was male, had HbA1c ≥7, was previously prescribed a similar medication, gave diabetes as the chief complaint, saw a mid-level practitioner, or saw their primary care provider. The odds were lower when the patient was insured, had ≥1 clinic visits in the past year, had kidney disease, or was prescribed certain other medications. Additional factors were associated with prescribing of each medication class. Qualitative results both supported and challenged the quantitative findings, illustrating important tensions involved in guideline-based prescribing. Clinic staff stressed the importance of the provider-patient relationship in guiding prescribing decisions in the face of competing priorities and care needs, and the impact of rapidly changing guidelines. Conclusions Diverse factors associated with guideline-concordant prescribing illuminate the complexity of delivering evidence-based care in CHCs. We present possible strategies for addressing barriers to guideline-based prescribing. Clinical trials registration This trial was registered retrospectively. Currently Controlled Trials NCT02299791 . Retrospectively registered 10 November 2014.

Responding to the substantial research on the relationship between social risk factors and health, enthusiasm has grown around social risk screening in health care settings, and numerous US health systems are experimenting with social risk screening initiatives. In the absence of standard social risk screening recommendations, some health systems are exploring using publicly available community-level data to identify patients who live in the most vulnerable communities as a way to characterize patient social and economic contexts, identify patients with potential social risks, and/or to target social risk screening efforts. To explore the utility of community-level data for accurately identifying patients with social risks by comparing the social deprivation index score for the census tract where a patient lives with patient-level social risk screening data. Cross-sectional study using patient-level social risk screening data from the electronic health records of a national network of community health centers between June 24, 2016, and November 15, 2018, linked to geocoded community-level data from publicly available sources. Eligible patients were those with a recorded response to social risk screening questions about food, housing, and/or financial resource strain, and a valid address of sufficient quality for geocoding. Social risk screening documented in the electronic health record. Community-level social risk was assessed using census tract-level social deprivation index score stratified by quartile. Patient-level social risks were identified using food insecurity, housing insecurity, and financial resource strain screening responses. The final study sample included 36 578 patients from 13 US states; 22 113 (60.5%) received public insurance, 21 181 (57.9%) were female, 17 578 (48.1%) were White, and 10 918 (29.8%) were Black. Although 6516 (60.0%) of those with at least 1 social risk factor were in the most deprived quartile of census tracts, patients with social risk factors lived in all census tracts. Overall, the accuracy of the community-level data for identifying patients with and without social risks was 48.0%. Although there is overlap, patient-level and community-level approaches for assessing patient social risks are not equivalent. Using community-level data to guide patient-level activities may mean that some patients who could benefit from targeted interventions or care adjustments would not be identified.

Introduction There is limited published literature on longitudinal utilization of glucose-lowering agents (GLAs) among patients with type 2 diabetes (T2D) and cardiovascular disease (CVD or risk of CVD). This retrospective, observational study aimed to provide updated evidence on patient characteristics and utilization of GLAs among patients with T2D and CVD or risk of CVD in the United States. Methods This was a cross-sectional evaluation of patients with T2D aged 50–89 years with annual continuous enrolment in a Medicare Advantage and Prescription Drug plan, identified from administrative claims data (Humana Research Database). Patients with T2D and atherosclerotic cardiovascular disease (ASCVD) or heart failure (HF) (CVD cohort), or T2D and an additional CVD risk factor without pre-existing CVD (CVD risk cohort) were identified from 2015 to 2019. Patients were followed from their first observed ASCVD/HF diagnosis or CVD risk factor for each year they were continuously enrolled or until occurrence of a CVD diagnosis (CVD risk cohort only). Use of GLA classes were reported by year, cohort, and age groups (50–64 years and ≥ 65 years). Results The percentage of patients on sodium-glucose co-transporter-2 inhibitors (SGLT-2is), glucagon-like peptide-1 receptor agonists (GLP-1 RAs), and GLP-1 RAs with proven cardiovascular benefit, respectively, increased from 2015 to 2019 among ≥ 65 years (CVD cohort: 1.1–3.4%, 1.6–4.0%, and 1.2–3.8%; CVD risk cohort: 1.4–3.7%, 2.0–4.3%, and 1.5–4.1%); and among 50–64 years (CVD cohort: 2.6–7.3%, 4.3–10.1%, and 3.4–9.4%; CVD risk cohort: 3.3–6.8%, 4.6–9.6%, and 3.5–8.9%). Conclusions Although use of SGLT-2is and GLP-1 RAs increased over time, overall utilization of these agents in patients with T2D and ASCVD/HF or at risk for ASCVD/HF remained low, especially for those aged ≥ 65 years. Plain Language Summary Sodium-glucose co-transporter-2 inhibitors (SGLT-2is) and glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are types of glucose-lowering medications for patients with type 2 diabetes (T2D). The American Diabetes Association, the American Association of Clinical Endocrinologists, and American College of Endocrinology have recommended these medications for patients who have been diagnosed with T2D and atherosclerotic cardiovascular disease or heart failure (ASCVD/HF). The purpose of this study was to find out how many patients in a US-based health insurance population with T2D and ASCVD/HF were treated with SGLT-2is, GLP-1 RAs, and other glucose-lowering medications from 2015 to 2019. Using insurance claims data, we identified 50- to 89-year-old patients with T2D and either ASCVD/HF or at least one risk factor for ASCVD/HF. We tracked the number of patients with T2D and either ASCVD/HF or ASCVD/HF risk factors who were using different glucose-lowering medications. Glucose-lowering medications were used in most patients (60–78%), but fewer than 11% of patients aged 50–64 years, and fewer than 5% of patients over 65 years of age were prescribed SGLT-2i and GLP-1 RA medications, despite clinical guidelines recommending their use for the above-mentioned indications. Increasing awareness among healthcare providers may be required to ensure patients with T2D and ASCVD/HF or ASCVD/HF risk factors are prescribed the guideline-recommended cardioprotective glucose-lowering agents.

Objectives. To assess longitudinal patterns of community health center (CHC) utilization and the effect of insurance discontinuity after Oregon’s 2008 Medicaid expansion (the Oregon Experiment). Methods. We conducted a retrospective cohort study with electronic health records and Medicaid data. We divided individuals who gained Medicaid in the Oregon Experiment into those who maintained (n = 788) or lost (n = 944) insurance coverage. We compared these groups with continuously insured (n = 921) and continuously uninsured (n = 5416) reference groups for community health center utilization rates over a 36-month period. Results. Both newly insured groups increased utilization in the first 6 months. After 6 months, use among those who maintained coverage stabilized at a level consistent with the continuously insured, whereas it returned to baseline for those who lost coverage. Conclusions. Individuals who maintained coverage through Oregon’s Medicaid expansion increased long-term utilization of CHCs, whereas those with unstable coverage did not. Policy implications. This study predicts long-term increase in CHC utilization following Affordable Care Act Medicaid expansion and emphasizes the need for policies that support insurance retention.

Objectives. We examined the association between insurance continuity and human papillomavirus (HPV) vaccine uptake in a network of federally qualified health clinics (FQHCs). Methods. We analyzed retrospective electronic health record data for females, aged 9–26 years in 2008 through 2010. Based on electronic health record insurance coverage information, patients were categorized by percent of time insured during the study period (0%, 1%–32%, 33%–65%, 66%–99%, or 100%). We used bilevel multivariable Poisson regression to compare vaccine-initiation prevalence between insurance groups, stratified by race/ethnicity and age. We also examined vaccine series completion among initiators who had at least 12 months to complete all 3 doses. Results. Significant interactions were observed between insurance category, age, and race/ethnicity. Juxtaposed with their continuously insured peers, patients were less likely to initiate the HPV vaccine if they were insured for less than 66% of the study period, aged 13 years or older, and identified as a racial/ethnic minority. Insurance coverage was not associated with vaccine series completion. Conclusions. Disparities in vaccine uptake by insurance status were present in the FQHCs studied here, despite the fact that HPV vaccines are available to many patients regardless of ability to pay.

The study of healthcare disparities in Latino immigrants is underdeveloped and limited by risk to participants. To validate an electronic health record (EHR)-based algorithm that could serve as a safe proxy for self-reported immigration status for health services researchers. Primary collection/analysis of interview data and secondary analysis of electronic health record data. We developed an EHR algorithm to classify a population of patients as likely undocumented or recent Latino immigrants and validated this algorithm by conducting semi-structured interviews of staff whose main role entails asking about immigration status. We presented them with a list of patients (masked to the interviewer) with whom they had worked, and asked them to indicate patient’s immigration status, if they recalled it. We analyzed the correspondence between staff knowledge and our EHR algorithm. Staff described routine conversations with patients about immigration status. The EHR algorithm had fair agreement (66.2%, 95% CI 57.3–74.2) with staff knowledge. When the staff were more confident of their assessment, agreement increased (77.6%, 95% CI 63.4–88.2). The EHR has potential for studying immigration status in health services research, although more study is needed to determine the accuracy and utility of EHRs for this purpose.