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INTRODUCTION: Little has previously been reported about the implementation of social risk screening across racial/ethnic/language groups. To address this knowledge gap, the associations between race/ethnicity/language, social risk screening, and patient-reported social risks were examined among adult patients at community health centers. METHODS: Patient- and encounter-level data from 2016 to 2020 from 651 community health centers in 21 U.S. states were used; data were extracted from a shared Epic electronic health record and analyzed between December 2020 and February 2022. In adjusted logistic regression analyses stratified by language, robust sandwich variance SE estimators were applied with clustering on patients primary care facility. RESULTS: Social risk screening occurred at 30% of health centers; 11% of eligible adult patients were screened. Screening and reported needs varied significantly by race/ethnicity/language. Black Hispanic and Black non-Hispanic patients were approximately twice as likely to be screened, and Hispanic White patients were 28% less likely to be screened than non-Hispanic White patients. Hispanic Black patients were 87% less likely to report social risks than non-Hispanic White patients. Among patients who preferred a language other than English or Spanish, Black Hispanic patients were 90% less likely to report social needs than non-Hispanic White patients. CONCLUSIONS: Social risk screening documentation and patient reports of social risks differed by race/ethnicity/language in community health centers. Although social care initiatives are intended to promote health equity, inequitable screening practices could inadvertently undermine this goal. Future implementation research should explore strategies for equitable screening and related interventions.

Evidence is needed about how to effectively support health care providers in implementing screening for social risks (adverse social determinants of health) and providing related referrals meant to address identified social risks. This need is greatest in underresourced care settings. The authors tested whether an implementation support intervention (6 months of technical assistance and coaching study clinics through a five-step implementation process) improved adoption of social risk activities in community health centers (CHCs). Thirty-one CHC clinics were block-randomized to six wedges that occurred sequentially. Over the 45-month study period from March 2018 to December 2021, data were collected for 6 or more months preintervention, the 6-month intervention period, and 6 or more months postintervention. The authors calculated clinic-level monthly rates of social risk screening results that were entered at in-person encounters and rates of social risk-related referrals. Secondary analyses measured impacts on diabetes-related outcomes. Intervention impact was assessed by comparing clinic performance based on whether they had versus had not yet received the intervention in the preintervention period compared with the intervention and postintervention periods. In assessing the results, the authors note that five clinics withdrew from the study for various bandwidth-related reasons. Of the remaining 26, a total of 19 fully or partially completed all 5 implementation steps, and 7 fully or partially completed at least the first 3 steps. Social risk screening was 2.45 times (95% confidence interval [CI], 1.32-4.39) higher during the intervention period compared with the preintervention period; this impact was not sustained postintervention (rate ratio, 2.16; 95% CI, 0.64-7.27). No significant difference was seen in social risk referral rates during the intervention or postintervention periods. The intervention was associated with greater blood pressure control among patients with diabetes and lower rates of diabetes biomarker screening postintervention. All results must be interpreted considering that the Covid-19 pandemic began midway through the trial, which affected care delivery generally and patients at CHCs particularly. Finally, the study results show that adaptive implementation support was effective at temporarily increasing social risk screening. It is possible that the intervention did not adequately address barriers to sustained implementation or that 6 months was not long enough to cement this change. Underresourced clinics may struggle to participate in support activities over longer periods without adequate resources, even if lengthier support is needed. As policies start requiring documentation of social risk activities, safety-net clinics may be unable to meet these requirements without adequate financial and coaching/technical support.

PurposeTo assess the extent that patients' social determinants of health (SDOH) influence safety-net primary care clinicians' decisions at the point of care; examine how that information comes to the clinician's attention; and analyze clinician, patient, and encounter characteristics associated with the use of SDOH data in clinical decision making.MethodsThirty-eight clinicians working in 21 clinics were prompted to complete 2 short card surveys embedded in the electronic health record (EHR) daily for 3 weeks. Survey data were matched with clinician-, encounter-, and patient-level variables from the EHR. Descriptive statistics and generalized estimating equation models were used to assess relationships between the variables and the clinician reported use of SDOH data to inform care.ResultsSocial determinants of health were reported to influence care in 35% of surveyed encounters. The most common sources of information on patients' SDOH were conversations with patients (76%), prior knowledge (64%), and the EHR (46%). Social determinants of health were significantly more likely to influence care among male and non-English-speaking patients, and those with discrete SDOH screening data documented in the EHR.ConclusionsElectronic health records present an opportunity to support clinicians integrating information about patients' social and economic circumstances into care planning. Study findings suggest that SDOH information from standardized screening documented in the EHR, combined with patient-clinician conversations, may enable social risk-adjusted care. Electronic health record tools and clinic workflows could be used to support both documentation and conversations. Study results also identified factors that may cue clinicians to include SDOH information in point-of-care decision-making. Future research should explore this topic further.

IntroductionThe American Heart Association and American College of Cardiology have proposed adjusting hypertension-related care quality measures by excluding patients with economic/access issues from the denominator of rate calculations. No research to date has explored the methods to operationalize this recommendation or how to measure economic/access issues. This study applied and compared different approaches to populating these denominator exceptions.MethodsElectronic health record data from 2019 were used in 2021 to calculate hypertension control rates in 84 community health centers. A total of 10 different indicators of patient economic/access barriers to care were used as denominator exclusions to calculate and then compare adjusted quality measure performance. Data came from a nonprofit health center‒controlled network that hosts a shared electronic health record for community health centers located in 22 states.ResultsA total of 5 of 10 measures yielded an increase in adjusted hypertension control rates in ≥50% of clinics (average rate increases of 0.7-3.71 percentage points). A total of 3 of 10 measures yielded a decrease in adjusted hypertension control rates in >50% of clinics (average rate decreases of 1.33-13.82 percentage points). A total of 5 measures resulted in excluding >50% of the clinic's patient population from quality measure assessments.ConclusionsChanges in clinic-level hypertension control rates after adjustment differed depending on the measure of economic/access issue. Regardless of the exclusion method, changes between baseline and adjusted rates were small. Removing community health center patients experiencing economic/access barriers from a hypertension control quality measure resulted in excluding a large proportion of patients, raising concerns about whether this calculation can be a meaningful measure of clinical performance.

IntroductionSocial risks (e.g., food/transportation insecurity) can hamper type 2 diabetes mellitus (T2DM) self-management, leading to poor outcomes. To determine the extent to which high-quality care can overcome social risks' health impacts, this study assessed the associations between reported social risks, receipt of guideline-based T2DM care, and T2DM outcomes when care is up to date among community health center patients.MethodsA cross-sectional study of adults aged ≥18 years (N=73,484) seen at 186 community health centers, with T2DM and ≥1 year of observation between July 2016 and February 2020. Measures of T2DM care included up-to-date HbA1c, microalbuminuria, low-density lipoprotein screening, and foot examination, and active statin prescription when indicated. Measures of T2DM outcomes among patients with up-to-date care included blood pressure, HbA1c, and low-density lipoprotein control on or within 6‒12 months of an index encounter. Analyses were conducted in 2021.ResultsIndividuals reporting transportation or housing insecurity were less likely to have up-to-date low-density lipoprotein screening; no other associations were seen between social risks and clinical care quality. Among individuals with up-to-date care, food insecurity was associated with lower adjusted rates of controlled HbA1c (79% vs 75%, p

Card studies--short surveys about the circumstances within which patients receive care-are traditionally completed on physical cards. We report on the development of an electronic health record (EHR)-embedded card study intended to decrease logistical challenges inherent to paper-based approaches, including distributing, tracking, and transferring the physical cards, as well as data entry and respondent prompts, while simultaneously decreasing the complexity for participants and facilitating rich analyses by linking to clinical and demographic data found in the EHR. Developing the EHR-based programming and data extraction was time consuming, required specialized expertise, and necessitated iteration to rectify issues encountered during implementation. Nonetheless, future EHR-embedded card studies will be able to replicate many of the same processes as informed by these results. Once built, the EHR-embedded card study simplified survey implementation for both the research team and clinic staff, resulting in research-quality data, the ability to link survey responses to relevant EHR data, and a 79% response rate. This detailed accounting of the development and implementation process, including issues encountered and addressed, might guide others in conducting EHR-embedded card studies. Key words: card study; survey method; electronic health record; patient care, INTRODUCTION Card studies--short surveys focused on the circumstances within which patients receive care--have been used to collect descriptive data on a range of research questions for decades. (1) Topics explored [...]

PURPOSE The Patient Protection and Affordable Care Act (ACA) has improved access to health insurance, yet millions remain uninsured. Many patients who remain uninsured access care at community health centers (CHCs); however, little is known about their health conditions and health care use. We assessed ambulatory care use and diagnosed health conditions among a cohort of CHC patients uninsured before enactment of the ACA (pre-ACA: January 1, 2012 to December 31, 2013) and followed them after enactment (post-ACA: January 1, 2014 to December 31, 2015). METHODS This retrospective cohort analysis used electronic health record data from CHCs in 11 US states that expanded Medicaid eligibility. We assessed ambulatory care visits and documented health conditions among a cohort of 138,246 patients (aged 19 to 64 years) who were uninsured pre-ACA and either remained uninsured, gained Medicaid, gained other health insurance, or did not have a visit post-ACA. We estimated adjusted predicted probabilities of ambulatory care use using an ordinal logistic mixed-effects regression model. RESULTS Post-ACA, 20.9% of patients remained uninsured, 15.0% gained Medicaid, 12.4% gained other insurance, and 51.7% did not have a visit. The majority of patients had [greater than or equal to]1 diagnosed health condition. The adjusted proportion of patients with high use ([greater than or equal to]6 visits over 2 years) increased from pre-ACA to post-ACA among those who gained Medicaid (pre-ACA: 23%, post-ACA: 34%, P CONCLUSIONS A significant percentage of CHC patients remained uninsured; many who remained uninsured had diagnosed health conditions, and one-half continued to have [greater than or equal to]3 visits to CHCs. CHCs continue to be essential providers for uninsured patients., INTRODUCTION In 2010, the Patient Protection and Affordable Care Act (ACA) was enacted with the goal of expanding health insurance coverage to all US citizens and legal residents. (1) The [...]

Objective The future of the Children's Health Insurance Program (CHIP) is uncertain after 2017. Survey-based research shows positive associations between CHIP expansions and children's healthcare utilization. To build on this prior work, we used electronic health record (EHR) data to assess temporal patterns of healthcare utilization after Oregon's 2009-2010 CHIP expansion. We hypothesized increased post-expansion utilization among children who gained public insurance. Methods Using EHR data from 154 Oregon community health centers, we conducted a retrospective cohort study of pediatric patients (2-18 years old) who gained public insurance coverage during the Oregon expansion (n = 3054), compared to those who were continuously publicly insured (n = 10,946) or continuously uninsured (n = 10,307) during the 2-year study period. We compared pre-post rates of primary care visits, well-child visits, and dental visits within- and between-groups. We also conducted longitudinal analysis of monthly visit rates, comparing the three insurance groups. Results After Oregon's 2009-2010 CHIP expansions, newly insured patients' utilization rates were more than double their pre-expansion rates [adjusted rate ratios (95 % confidence intervals); increases ranged from 2.10 (1.94-2.26) for primary care visits to 2.77 (2.56-2.99) for dental visits]. Utilization among the newly insured spiked shortly after coverage began, then leveled off, but remained higher than the uninsured group. Conclusions This study used EHR data to confirm that CHIP expansions are associated with increased utilization of essential pediatric primary and preventive care. These findings are timely to pending policy decisions that could impact children's access to public health insurance in the United States., Author(s): Steffani R. Bailey[sup.1] , Miguel Marino[sup.1] [sup.2] , Megan Hoopes[sup.3] , John Heintzman[sup.1] , Rachel Gold[sup.3] [sup.4] , Heather Angier[sup.1] , Jean P. O'Malley[sup.2] , Jennifer E. DeVoe[sup.1] [sup.3] [...]