Real-World Treatment Patterns of Glucose-Lowering Agents Among Patients with Type 2 Diabetes Mellitus and Cardiovascular Disease or At Risk for Cardiovascular Disease: An Observational, Cross-Sectional, Retrospective Study.

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.

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 (60­78%), but fewer than 11% of patients aged 50­64 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.

Latino-white disparities in ICD-coded asthma diagnosis among US children.

INTRODUCTION: It is uncertain if disparities in asthma diagnosis between Latino and non-Hispanic white children stem from differences in diagnosis over time among children presenting with similar clinical scenarios suggestive of asthma. METHODS: We evaluated the odds of International Classification of Disease (ICD)-coded asthma diagnosis in Latino (English and Spanish preferring) and non-Hispanic white children, overall (N = 524,456) and among those presenting with possible asthma indicators (N = 85,516) over a 13-year period, using electronic health record data from a multi-state network of community health centers. RESULTS: Among those with possible asthma indicators, Spanish-preferring Latinos had lower adjusted odds of ICD-coded asthma diagnosis compared to non-Hispanic whites (OR = 0.87, 95%CI = 0.77-0.99); English-preferring Latinos did not differ from non-Hispanic whites. Differences in ICD-coded diagnosis between ethnicity/language groups varied by presenting symptom. CONCLUSIONS: Spanish-preferring Latino children may be less-likely to have ICD-coded asthma documented in the EHR when presenting with certain clinical indicators suggestive of asthma. Clinicians should be cognizant of the need for the follow-up of these indicators in Spanish-preferring Latino children.

"I didn't know you could do that": A Pilot Assessment of EHR Optimization Training.

BACKGROUND: Informatics tools within electronic health records (EHRs)-for example, data rosters and clinical reminders-can help disseminate care guidelines into clinical practice. Such tools' adoption varies widely, however, possibly because many primary care providers receive minimal training in even basic EHR functions. OBJECTIVES: This mixed-methods evaluation of a pilot training program sought to identify factors to consider when providing EHR use optimization training in community health centers (CHCs) as a step toward supporting CHC providers' adoption of EHR tools. METHODS: In spring 2018, we offered 10 CHCs a 2-day, 16-hour training in EHR use optimization, provided by clinician trainers, and customized to each CHC's needs. We surveyed trainees pre- and immediately post-training and again 3 months later. We conducted post-training interviews with selected clinic staff, and conducted a focus group with the trainers, to assess satisfaction with the training, and perceptions of how it impacted subsequent EHR use. RESULTS: Six CHCs accepted and received the training; 122 clinic staff members registered to attend, and most who completed the post-training survey reported high satisfaction. Three months post-training, 80% of survey respondents said the training had changed their daily EHR use somewhat or significantly. CONCLUSION: Factors to consider when planning EHR use optimization training in CHCs include: CHCs may face barriers to taking part in such training; it may be necessary to customize training to a given clinic's needs and to different trainees' clinic roles; identifying trainees' skill level a priori would help but is challenging; in-person training may be preferable; and inclusion of a practice coach may be helpful. Additional research is needed to identify how to provide such training most effectively.

Role of social deprivation on asthma care quality among a cohort of children in US community health centres.

OBJECTIVE: Social 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. RESULTS: Children 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. CONCLUSIONS: Higher 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.

Lessons learned about the effective operationalization of champions as an implementation strategy: results from a qualitative process evaluation of a pragmatic trial.

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.

Comparison of Community-Level and Patient-Level Social Risk Data in a Network of Community Health Centers.

Importance: 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. Objective: 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. Design, Setting, and Participants: 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. Exposures: Social risk screening documented in the electronic health record. Main Outcomes and Measures: 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. Results: 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%. Conclusions and Relevance: 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.

Assessment of Opioid Prescribing Patterns in a Large Network of US Community Health Centers, 2009 to 2018.

Importance: Understanding opioid prescribing patterns in community health centers (CHCs) that disproportionately serve low-income patients may help to guide strategies to reduce opioid-related harms. Objective: To assess opioid prescribing patterns between January 1, 2009, and December 31, 2018, in a network of safety-net clinics serving high-risk patients. Design, Setting, and Participants: Cross-sectional study of 3 227 459 opioid prescriptions abstracted from the electronic health records of 2 129 097 unique primary care patients treated from 2009 through 2018 at a network of CHCs that included 449 clinic sites in 17 states. All age groups were included in the analysis. Main Outcomes and Measures: The following measures were described at the population level for each study year: (1) percentage of patients with at least 1 prescription for an opioid by age and sex, (2) number of opioid prescriptions per 100 patients, (3) number of long-acting opioid prescriptions per 100 patients, (4) mean annual morphine milligram equivalents (MMEs) per patient, (5) mean MME per prescription, (6) number of chronic opioid users, and (7) mean of high-dose opioid users. Results: The study population included 2 129 097 patients (1 158 413 women [54.4%]) with a mean (SD) age of 32.2 (21.1) years and a total of 3 227 459 opioid prescriptions. The percentage of patients receiving at least 1 opioid prescription in a calendar year declined 67.4% from 15.9% in 2009 to 5.2% in 2018. Over the 10-year study period, a greater percentage of women received a prescription (13.1%) compared with men (10.9%), and a greater percentage of non-Hispanic White patients (18.1%) received an opioid prescription compared with non-Hispanic Black patients (9.5%), non-Hispanic patients who self-identified as other races (8.0%), and Hispanic patients (6.9%). The number of opioid prescriptions for every 100 patients decreased 73.7% from 110.8 in 2009 to 29.1 in 2018. The number of long-acting opioids for every 100 patients decreased 85.5% during the same period, from 22.0 to 3.2. The MMEs per patient decreased from 1682.7 in 2009 to 243.1 in 2018, a decline of 85.6%. Conclusions and Relevance: In this cross-sectional study, the opioid prescribing rate in 2009 in the CHC network was higher than national population estimates but began to decline earlier and more precipitously. This finding likely reflects harm mitigation policies and efforts at federal, state, and clinic levels and strong clinical quality improvement strategies within the CHCs.

Using Electronic Health Record Data to Study Latino Immigrant Populations in Health Services Research.

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.

Oral corticosteroid use, obesity, and ethnicity in children with asthma.

Objective: Comorbid asthma and obesity leads to poorer asthma outcomes, partially due to decreased response to controller medication. Increased oral steroid prescription, a marker of uncontrolled asthma, may follow. Little is known about this phenomenon among Latino children. Our objective was to determine whether obesity is associated with increased oral steroid prescription for children with asthma, and to assess potential disparities in these associations between Latino and non-Hispanic white children.Methods: We examined electronic health record data from the ADVANCE national network of community health centers. The sample included 16,763 children aged 5-17 years with an asthma diagnosis and ≥1 ambulatory visit in ADVANCE clinics across 22 states between 2012 and 2017. Poisson regression analysis was used to examine the rate of oral steroid prescription overall and by ethnicity controlling for potential confounders.Results: Among Latino children, those who were always overweight/obese at study visits had a 15% higher rate of receiving an oral steroid prescription than those who were never overweight/obese [rate ratio (RR) = 1.15, 95% CI 1.05-1.26]. A similar effect size was observed for non-Hispanic white children, though the relationship was not statistically significant (RR = 1.10, 95% CI: 0.92-1.33). The interactions between body mass index and ethnicity were not significant (sometimes overweight/obese p = 0.95, always overweight/obese p = 0.58), suggesting a lack of disparities in the association between obesity and oral steroid prescription by ethnicity.Conclusions: Children with obesity received more oral steroid prescriptions than those at a healthy weight, which may be indicative of worse asthma control. We did not observe significant ethnic disparities.

Does increased implementation support improve community clinics' guideline-concordant care? Results of a mixed methods, pragmatic comparative effectiveness trial.

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.

Variation in Electronic Health Record Documentation of Social Determinants of Health Across a National Network of Community Health Centers.

INTRODUCTION: This paper describes the adoption of an electronic health record-based social determinants of health screening tool in a national network of more than 100 community health centers. METHODS: In 2016, a screening tool with questions on 7 social determinants of health domains was developed and deployed in the electronic health record, with technical instructions on how to use the tool and suggested clinical workflows. To understand adoption patterns, the study team extracted electronic health record data for any patient with a community health center visit between June 2016 and May 2018. Patients were considered "screened" if a response to at least 1 social determinants of health domain was documented in the electronic health record tool. RESULTS: A total of 31,549 patients (2% of those with a visit in the study period) had a documented social determinants of health screening. The number of screenings increased over time, time; 71 community health centers (67%) conducted at least one screening, but almost 50% took place in only 4 community health centers. Over half (55%) of screenings only included responses for only 1 domain. Screening was most likely to occur during an office visit with an established patient and documented in the electronic health record by a medical assistant. CONCLUSIONS: Screening documentation patterns varied widely across the network of community health centers. Despite the growing national emphasis on the importance of screening for social determinants of health, these findings suggest that simply activating electronic health record tools for social determinants of health screening does not lead to widespread adoption. Potential barriers to screening adoption and implementation should be explored further. SUPPLEMENT INFORMATION: This article is part of a supplement entitled Identifying and Intervening on Social Needs in Clinical Settings: Evidence and Evidence Gaps, which is sponsored by the Agency for Healthcare Research and Quality of the U.S. Department of Health and Human Services, Kaiser Permanente, and the Robert Wood Johnson Foundation.

Study protocol: a pragmatic, stepped-wedge trial of tailored support for implementing social determinants of health documentation/action in community health centers, with realist evaluation.

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.

Adoption of Social Determinants of Health EHR Tools by Community Health Centers.

PURPOSE: This pilot study assessed the feasibility of implementing electronic health record (EHR) tools for collecting, reviewing, and acting on patient-reported social determinants of health (SDH) data in community health centers (CHCs). We believe it is the first such US study. METHODS: We implemented a suite of SDH data tools in 3 Pacific Northwest CHCs in June 2016, and used mixed methods to assess their adoption through July 2017. We modified the tools at clinic request; for example, we added questions that ask if the patient wanted assistance with SDH needs. RESULTS: Social determinants of health data were collected on 1,130 patients during the study period; 97% to 99% of screened patients (n = 1,098) had ≥1 SDH need documented in the EHR, of whom 211 (19%) had an EHR-documented SDH referral. Only 15% to 21% of patients with a documented SDH need indicated wanting help. Examples of lessons learned on adoption of EHR SDH tools indicate that clinics should: consider how to best integrate tools into existing workflow processes; ensure that staff tasked with SDH efforts receive adequate tool training and access; and consider that timing of data entry impacts how and when SDH data can be used. CONCLUSIONS: Our results indicate that adoption of systematic EHR-based SDH documentation may be feasible, but substantial barriers to adoption exist. Lessons from this study may inform primary care providers seeking to implement SDH-related efforts, and related health policies. Far more research is needed to address implementation barriers related to SDH documentation in EHRs.

Role of Race/Ethnicity, Language, and Insurance in Use of Cervical Cancer Prevention Services Among Low-Income Hispanic Women, 2009-2013.

INTRODUCTION: Hispanic women in the United States have an elevated risk of cervical cancer, but the existing literature does not reveal why this disparity persists. METHODS: We performed a retrospective cohort analysis of 17,828 low-income women aged 21 to 64 years seeking care at Oregon community health centers served by a hosted, linked electronic health record during 2009 through 2013. We assessed the odds of having had Papanicolaou (Pap) tests and receiving human papillomavirus (HPV) vaccine, by race/ethnicity, insurance status, and language. RESULTS: Hispanic women, regardless of pregnancy status or insurance, had greater odds of having had Pap tests than non-Hispanic white women during the study period. English-preferring Hispanic women had higher odds of having had Pap tests than Spanish-preferring Hispanic women (OR, 2.08; 95% confidence interval [CI], 1.63-2.66) but lower odds of having received HPV vaccination (OR, 0.21; 95% CI, 0.12-0.38). Uninsured patients, regardless of race/ethnicity, had lower odds of HPV vaccine initiation than insured patients did. Once a single dose was received, there were no significant racial/ethnic differences in vaccine series completion. CONCLUSION: In this sample of low-income women seeking care at Oregon community health centers, we found minimal racial/ethnic disparities in the receipt of cervical cancer prevention services. Inequities by insurance status, especially in the receipt of HPV vaccine, persist. Community health center-based care may be a useful model to address racial/ethnic disparities in prevention, but this model would need further population-wide study.

Developing Electronic Health Record (EHR) Strategies Related to Health Center Patients' Social Determinants of Health.

BACKGROUND: "Social determinants of heath" (SDHs) are nonclinical factors that profoundly affect health. Helping community health centers (CHCs) document patients' SDH data in electronic health records (EHRs) could yield substantial health benefits, but little has been reported about CHCs' development of EHR-based tools for SDH data collection and presentation. METHODS: We worked with 27 diverse CHC stakeholders to develop strategies for optimizing SDH data collection and presentation in their EHR, and approaches for integrating SDH data collection and the use of those data (eg, through referrals to community resources) into CHC workflows. RESULTS: We iteratively developed a set of EHR-based SDH data collection, summary, and referral tools for CHCs. We describe considerations that arose while developing the tools and present some preliminary lessons learned. CONCLUSION: Standardizing SDH data collection and presentation in EHRs could lead to improved patient and population health outcomes in CHCs and other care settings. We know of no previous reports of processes used to develop similar tools. This article provides an example of 1 such process. Lessons from our process may be useful to health care organizations interested in using EHRs to collect and act on SDH data. Research is needed to empirically test the generalizability of these lessons.

Cardiovascular care guideline implementation in community health centers in Oregon: a mixed-methods analysis of real-world barriers and challenges.

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.

Lack of Lipid Screening Disparities in Obese Latino Adults at Health Centers.

INTRODUCTION: In cross-sectional survey studies, obese Latinos are less likely to be screened for elevated serum cholesterol, despite their higher risk for hyperlipidemia and coronary artery disease. This study evaluated insurance and racial/ethnic disparities in lipid screening receipt between obese Latino and non-Hispanic white patients in Oregon community health centers (CHCs) over 5 years, using electronic health record data. METHODS: This retrospective cohort study evaluated obese (BMI ≥30), low-income, adult patients (aged 21-79 years) with at least one visit at an Oregon CHC during 2009-2013 (n=11,095). Odds of lipid screening in the study period (clinical data collected in 2009-2013) were measured, adjusting for age, sex, primary clinic, and comorbidities, stratified by utilization in the study period. Analysis was done in 2016. RESULTS: Sixty percent of the study population received at least one lipid screening in 2009-2013. There were no significant differences in screening between insured Latinos and insured non-Hispanic whites, except those with more than five visits over 5 years (OR=0.75, 95% CI=0.60, 0.94). Uninsured Latinos had higher odds of screening versus insured non-Hispanic whites among the low visit strata (OR=1.65, 95% CI=1.18, 2.30). Among Latinos, Spanish preference resulted in higher screening odds versus English preference in the two- to five-visit stratum (OR=1.63, 95% CI=1.12, 2.35). CONCLUSIONS: Obese, low-income patients at CHCs underutilize cholesterol screening. However, screening differences by race/ethnicity and preferred language are minimal. Further research is necessary to understand how care delivered by CHCs may mitigate previously reported disparities in lipid screening.

In Low-Income Latino Patients, Post-Affordable Care Act Insurance Disparities May Be Reduced Even More than Broader National Estimates: Evidence from Oregon.

BACKGROUND: Early survey evidence suggests a reduction of disparities in insurance coverage between Latinos and non-Hispanic Whites post-Affordable Care Act (ACA). These findings may not describe the insurance status of vulnerable, low-income Latino populations served in community health centers (CHCs) over the course of this policy change. Cross-sectional surveys also may be of limited use in describing longitudinal phenomena such as changes in health insurance status. METHODS: Using electronic health record (EHR) data, we compared the insurance status of N = 42,392 low-income patients served in 23 CHCs in Oregon, by race/ethnicity and language, over a period of 6 years straddling the implementation of ACA-related Medicaid expansion on January 1, 2014. FINDINGS: Prior to 2014, Spanish-preferring Latinos were more likely to be uninsured than English-preferring Latinos and non-Hispanic Whites. Among uninsured patients who returned for at least one visit in 2014, Spanish-preferring Latinos had the largest increase in insurance coverage rates, and all three racial/ethnic/language groups had similar rates of insurance coverage. There were no racial/ethnic/language differences between those who did and did not have visit in 2014. CONCLUSION: Among previously uninsured low-income patients returning to Oregon CHCs, insurance disparities were eliminated after Medicaid expansion, especially in Spanish-speaking Latinos. Further study is needed to understand the elimination of insurance disparities in this cohort.

Pneumococcal Vaccination in Low-Income Latinos: An Unexpected Trend in Oregon Community Health Centers.

BACKGROUND: In cross-sectional studies, Latino and Spanish-speaking U.S. residents age 65 and over are less likely to receive pneumococcal vaccination than non-Hispanic Whites. METHODS: We performed a time-to-event, cohort analysis, in 23 Oregon community health centers of low-income patients who turned 65 in the study period (2009-2013; n = 1,248). The outcome measure was receipt of PPSV-23 in the study period by race / ethnicity, preferred language, and insurance status. RESULTS: Insured Latino patients were more likely to receive PPSV-23 than insured non-Hispanic Whites (HR = 2.05, p < .001). Uninsured Latino seniors showed no difference from insured non-Hispanic Whites in PPSV-23 receipt (HR = 1.26, p = .381) unless they averaged fewer than one clinic visit yearly (HR = 1.80, p = .001). CONCLUSIONS: Low-income Latino seniors in Oregon community health centers were immunized against pneumococcus more frequently than insured non-Hispanic Whites, although this finding was mitigated in Latinos without insurance. This finding needs further research in order to reduce adult immunization disparities in the society at large.

Measuring Preventive Care Delivery: Comparing Rates Across Three Data Sources.

INTRODUCTION: Preventive care delivery is an important quality outcome, and electronic data reports are being used increasingly to track these services. It is highly informative when electronic data sources are compared to information manually extracted from medical charts to assess validity and completeness. METHODS: This cross-sectional study used a random sample of Medicaid-insured patients seen at 43 community health centers in 2011 to calculate standard measures of correspondence between manual chart review and two automated sources (electronic health records [EHRs] and Medicaid claims), comparing documentation of orders for and receipt of ten preventive services (n=150 patients/service). Data were analyzed in 2015. RESULTS: Using manual chart review as the gold standard, automated EHR extraction showed near-perfect to perfect agreement (κ=0.96-1.0) for services received within the primary care setting (e.g., BMI, blood pressure). Receipt of breast and colorectal cancer screenings, services commonly referred out, showed moderate (κ=0.42) to substantial (κ=0.62) agreement, respectively. Automated EHR extraction showed near-perfect agreement (κ=0.83-0.97) for documentation of ordered services. Medicaid claims showed near-perfect agreement (κ=0.87) for hyperlipidemia and diabetes screening, and substantial agreement (κ=0.67-0.80) for receipt of breast, cervical, and colorectal cancer screenings, and influenza vaccination. Claims showed moderate agreement (κ=0.59) for chlamydia screening receipt. Medicaid claims did not capture ordered or unbilled services. CONCLUSIONS: Findings suggest that automated EHR and claims data provide valid sources for measuring receipt of most preventive services; however, ordered and unbilled services were primarily captured via EHR data and completed referrals were more often documented in claims data.