Search

Objective: To develop and validate prediction models for inference of Latino nativity to advance health equity research., Data Sources/study Setting: This study used electronic health records (EHRs) from 19,985 Latino children with self-reported country of birth seeking care from January 1, 2012 to December 31, 2018 at 456 community health centers (CHCs) across 15 states along with census-tract geocoded neighborhood composition and surname data., Study Design: We constructed and evaluated the performance of prediction models within a broad machine learning framework (Super Learner) for the estimation of Latino nativity. Outcomes included binary indicators denoting nativity (US vs. foreign-born) and Latino country of birth (Mexican, Cuban, Guatemalan). The performance of these models was compared using the area under the receiver operating characteristics curve (AUC) from an externally withheld patient sample., Data Collection/extraction Methods: Census surname lists, census neighborhood composition, and Forebears administrative data were linked to EHR data., Principal Findings: Of the 19,985 Latino patients, 10.7% reported a non-US country of birth (5.1% Mexican, 4.7% Guatemalan, 0.8% Cuban). Overall, prediction models for nativity showed outstanding performance with external validation (US-born vs. foreign: AUC = 0.90; Mexican vs. non-Mexican: AUC = 0.89; Guatemalan vs. non-Guatemalan: AUC = 0.95; Cuban vs. non-Cuban: AUC = 0.99)., Conclusions: Among challenges facing health equity researchers in health services is the absence of methods for data disaggregation, and the specific ability to determine Latino country of birth (nativity) to inform disparities. Recent interest in more robust health equity research has called attention to the importance of data disaggregation. In a multistate network of CHCs using multilevel inputs from EHR data linked to surname and community data, we developed and validated novel prediction models for the use of available EHR data to infer Latino nativity for health disparities research in primary care and health services research, which is a significant potential methodologic advance in studying this population., (© 2023 Health Research and Educational Trust.)

Objective: To assess and compare electronic health record (EHR) documentation of chronic disease in problem lists and encounter diagnosis records among Community Health Center (CHC) patients., Materials and Methods: We assessed patient EHR data in a large clinical research network during 2012-2019. We included CHCs who provided outpatient, older adult primary care to patients age ≥45 years, with ≥2 office visits during the study. Our study sample included 1 180 290 patients from 545 CHCs across 22 states. We used diagnosis codes from 39 Chronic Condition Warehouse algorithms to identify chronic conditions from encounter diagnoses only and compared against problem list records. We measured correspondence including agreement, kappa, prevalence index, bias index, and prevalence-adjusted bias-adjusted kappa., Results: Overlap of encounter diagnosis and problem list ascertainment was 59.4% among chronic conditions identified, with 12.2% of conditions identified only in encounters and 28.4% identified only in problem lists. Rates of coidentification varied by condition from 7.1% to 84.4%. Greatest agreement was found in diabetes (84.4%), HIV (78.1%), and hypertension (74.7%). Sixteen conditions had <50% agreement, including cancers and substance use disorders. Overlap for mental health conditions ranged from 47.4% for anxiety to 59.8% for depression., Discussion: Agreement between the 2 sources varied substantially. Conditions requiring regular management in primary care settings may have a higher agreement than those diagnosed and treated in specialty care., Conclusion: Relying on EHR encounter data to identify chronic conditions without reference to patient problem lists may under-capture conditions among CHC patients in the United States., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Many cancer survivors receive primary care in community health centers (CHCs). Cancer history is an important factor to consider in the provision of primary care, yet little is known about the completeness or accuracy of cancer history data contained in CHC electronic health records (EHRs)., Methods: We probabilistically linked EHR data from more than1.5 million adult CHC patients to state cancer registries in California, Oregon, and Washington and estimated measures of agreement (eg, kappa, sensitivity, specificity). We compared demographic and clinical characteristics of cancer patients as estimated by each data source, evaluating distributional differences with absolute standardized mean differences., Results: A total 74 707 cancer patients were identified between the 2 sources (EHR only, n = 22 730; registry only, n = 23 616; both, n = 28 361). Nearly one-half of cancer patients identified in registries were missing cancer documentation in the EHR. Overall agreement of cancer ascertainment in the EHR vs cancer registries (gold standard) was moderate (kappa = 0.535). Cancer site-specific agreement ranged from substantial (eg, prostate and female breast; kappa > 0.60) to fair (melanoma and cervix; kappa < 0.40). Comparing population characteristics of cancer patients as ascertained from each data source, groups were similar for sex, age, and federal poverty level, but EHR-recorded cases showed greater medical complexity than those ascertained from cancer registries., Conclusions: Agreement between EHR and cancer registry data was moderate and varied by cancer site. These findings suggest the need for strategies to improve capture of cancer history information in CHC EHRs to ensure adequate delivery of care and optimal health outcomes for cancer survivors., (© The Author(s) 2020. Published by Oxford University Press.)

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.

Data from a large network of community health centers connected via a single electronic health record (EHR) system examined associations between psychiatric disorders and documentation of a cannabis-related disorder among patients with reported cannabis use. Participants were adults who had at least one ambulatory visit at a clinic in three states between 1/1/2012 and 12/31/2016 and had either 1) a documented cannabis-related disorder indicated by an ICD-9/10 code on the problem list or encounter list or 2) documentation of cannabis use in the EHR social history section. Clinics included 101,405 patients with either cannabis use recorded in the social history of the EHR (n = 71,660) or a cannabis-related disorder documented in the encounter or problem list (n = 29,745). GEE logistic regression modeling estimated adjusted odds ratios (aOR). Odds of patients having cannabis-related disorder recorded on the encounter or problem list were higher for individuals with depression (aOR = 1.08, 95% CI: 1.04-1.13), anxiety (aOR = 1.16, CI: 1.11-1.21) and bipolar disorder (aOR = 1.16, CI: 1.10-1.23). A diagnosis of schizophrenia increased the odds of a cannabis-related disorder by 62% (aOR = 1.62, CI: 1.48- 1.78). Primary care providers should routinely screen for and document cannabis-related disorders and psychiatric disorders.

Background: Electronic health records (EHRs) provide rich data on many domains not routinely available in other data, as such, they are a promising source to study changes in health outcomes using longitudinal study designs (eg, cohort studies, natural experiments, etc.). Yet, patient attrition rates in these data are unknown., Objective: The objective of this study was to estimate overall and among adults with diabetes or hypertension: (1) patient attrition over a 3-year period at community health centers; and (2) the likelihood that patients with Medicaid permanently switched their source of primary care., Research Design: A retrospective cohort study of 2012-2017 data from the Accelerating Data Value Across a National Community Health Center Network (ADVANCE) Clinical Data Research Network of community health centers were used to assess EHR data attrition. Oregon Medicaid enrollment and claims data were used to estimate the likelihood of changing the source of primary care., Subjects: A total of 827,657 patients aged 19-64 with ≥1 ambulatory visit from 76 community health center systems across 20 states. In all, 232,891 Oregon Medicaid enrollees (aged 19-64) with a gap of ≥6 months following a claim for a visit billed to a primary care source., Measures: Percentage of patients not returning within 3 years of their qualifying visit (attrition). The probability that a patient with Medicaid permanently changed their primary care source., Results: Attrition over the 3 years averaged 33.5%; attrition rates were lower (<25%) among patients with diabetes and/or hypertension. Among Medicaid enrollees, the percentage of provider change after a 6-month gap between visits was 12% for community health center patients compared with 39% for single-provider practice patients. Over 3 years, the likelihood of a patient changing to a new provider increased with length of time since their last visit but remained lowest among community health center patients., Conclusion: This study demonstrates the use of the EHR dataset is a reliable source of data to support longitudinal studies while highlighting variability in attrition by primary care source and chronic conditions.

Background: In addition to delivering vital health care to millions of patients in the United States, community health centers (CHCs) provide needed health insurance outreach and enrollment support to their communities. We developed a health insurance enrollment tracking tool integrated within the electronic health record (EHR) and conducted a hybrid implementation-effectiveness trial in a CHC-based research network to assess tool adoption using two implementation strategies., Methods: CHCs were recruited from the OCHIN practice-based research network. Seven health center systems (23 CHC clinic sites) were recruited and randomized to receive basic educational materials alone (Arm 1), or these materials plus facilitation (Arm 2) during the 18-month study period, September 2016-April 2018. Facilitation consisted of monthly contacts with clinic staff and utilized audit and feedback and guided improvement cycles. We measured total and monthly tool utilization from the EHR. We conducted structured interviews of CHC staff to assess factors associated with tool utilization. Qualitative data were analyzed using an immersion-crystallization approach with barriers and facilitators identified using the Consolidated Framework for Implementation Research., Results: The majority of CHCs in both study arms adopted the enrollment tool. The rate of tool utilization was, on average, higher in Arm 2 compared to Arm 1 (20.0% versus 4.7%, p < 0.01). However, by the end of the study period, the rate of tool utilization was similar in both arms; and observed between-arm differences in tool utilization were largely driven by a single, large health center in Arm 2. Perceived relative advantage of the tool was the key factor identified by clinic staff as driving tool utilization. Implementation climate and leadership engagement were also associated with tool utilization., Conclusions: Using basic education materials and low-intensity facilitation, CHCs quickly adopted an EHR-based tool to support critical outreach and enrollment activities aimed at improving access to health insurance in their communities. Though facilitation carried some benefit, a CHC's perceived relative advantage of the tool was the primary driver of decisions to implement the tool., Trial Registration: ClinicalTrials.gov: NCT02355262, Posted February 4, 2015.

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., (Copyright © 2019 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

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.

Objective: Medication adherence is an important aspect of chronic disease management. Electronic health record (EHR) data are often not linked to dispensing data, limiting clinicians' understanding of which of their patients fill their medications, and how to tailor care appropriately. We aimed to develop an algorithm to link EHR prescribing to claims-based dispensing data and use the results to quantify how often patients with diabetes filled prescribed chronic disease medications., Materials and Methods: We developed an algorithm linking EHR prescribing data (RxNorm terminology) to claims-based dispensing data (NDC terminology), within sample of adult (19-64) community health center (CHC) patients with diabetes from a network of CHCs across 12 states. We demonstrate an application of the method by calculating dispense rates for a set of commonly prescribed diabetes and cardio-protective medications. To further inform clinical care, we computed adjusted odds ratios of dispense by patient-, encounter-, and clinic-level characteristics., Results: Seventy-six percent of cardio-protective medication prescriptions and 74% of diabetes medications were linked to a dispensing record. Age, income, ethnicity, insurance, assigned primary care provider, comorbidity, time on EHR, and clinic size were significantly associated with odds of dispensing., Discussion: EHR prescriptions and pharmacy dispense data can be linked at the record level across different terminologies. Dispensing rates in this low-income population with diabetes were similar to other populations., Conclusion: Record linkage resulted in the finding that CHC patients with diabetes largely had their chronic disease medications dispensed. Understanding factors associated with dispensing rates highlight barriers and opportunities for optimal disease management.

Background: Children with health insurance have increased access to healthcare and receive higher quality care. However, despite recent initiatives expanding children's coverage, many remain uninsured. New technologies present opportunities for helping clinics provide enrollment support for patients. We developed and tested electronic health record (EHR)-based tools to help clinics provide children's insurance assistance., Methods: We used mixed methods to understand tool adoption, and to assess impact of tool use on insurance coverage, healthcare utilization, and receipt of recommended care. We conducted intent-to-treat (ITT) analyses comparing pediatric patients in 4 intervention clinics (n = 15,024) to those at 4 matched control clinics (n = 12,227). We conducted effect-of-treatment-on-the-treated (ETOT) analyses comparing intervention clinic patients with tool use (n = 2240) to intervention clinic patients without tool use (n = 12,784)., Results: Tools were used for only 15% of eligible patients. Qualitative data indicated that tool adoption was limited by: (1) concurrent initiatives that duplicated the work associated with the tools, and (2) inability to obtain accurate insurance coverage data and end dates. The ITT analyses showed that intervention clinic patients had higher odds of gaining insurance coverage (adjusted odds ratio [aOR] = 1.32, 95% confidence interval [95%CI] 1.14-1.51) and lower odds of losing coverage (aOR = 0.77, 95%CI 0.68-0.88), compared to control clinic patients. Similarly, ETOT findings showed that intervention clinic patients with tool use had higher odds of gaining insurance (aOR = 1.83, 95%CI 1.64-2.04) and lower odds of losing coverage (aOR = 0.70, 95%CI 0.53-0.91), compared to patients without tool use. The ETOT analyses also showed higher rates of receipt of return visits, well-child visits, and several immunizations among patients for whom the tools were used., Conclusions: This pragmatic trial, the first to evaluate EHR-based insurance assistance tools, suggests that it is feasible to create and implement tools that help clinics provide insurance enrollment support to pediatric patients. While ITT findings were limited by low rates of tool use, ITT and ETOT findings suggest tool use was associated with better odds of gaining and keeping coverage. Further, ETOT findings suggest that use of such tools may positively impact healthcare utilization and quality of pediatric care., Trial Registration: ClinicalTrials.gov, NCT02298361 ; retrospectively registered on November 5, 2014.

Federal value-based payment programs require primary care practices to conduct quality improvement activities, informed by the electronic reports on clinical quality measures that their electronic health records (EHRs) generate. To determine whether EHRs produce reports adequate to the task, we examined survey responses from 1,492 practices across twelve states, supplemented with qualitative data. Meaningful-use participation, which requires the use of a federally certified EHR, was associated with the ability to generate reports-but the reports did not necessarily support quality improvement initiatives. Practices reported numerous challenges in generating adequate reports, such as difficulty manipulating and aligning measurement time frames with quality improvement needs, lack of functionality for generating reports on electronic clinical quality measures at different levels, discordance between clinical guidelines and measures available in reports, questionable data quality, and vendors that were unreceptive to changing EHR configuration beyond federal requirements. The current state of EHR measurement functionality may be insufficient to support federal initiatives that tie payment to clinical quality measures.

Introduction: Brief smoking-cessation interventions in primary care settings are effective, but delivery of these services remains low. The Centers for Medicare and Medicaid Services' Meaningful Use (MU) of Electronic Health Record (EHR) Incentive Program could increase rates of smoking assessment and cessation assistance among vulnerable populations. This study examined whether smoking status assessment, cessation assistance, and odds of being a current smoker changed after Stage 1 MU implementation., Methods: EHR data were extracted from 26 community health centers with an EHR in place by June 15, 2009. AORs were computed for each binary outcome (smoking status assessment, counseling given, smoking-cessation medications ordered/discussed, current smoking status), comparing 2010 (pre-MU), 2012 (MU preparation), and 2014 (MU fully implemented) for pregnant and non-pregnant patients., Results: Non-pregnant patients had decreased odds of current smoking over time; odds for all other outcomes increased except for medication orders from 2010 to 2012. Among pregnant patients, odds of assessment and counseling increased across all years. Odds of discussing or ordering of cessation medications increased from 2010 compared with the other 2 study years; however, medication orders alone did not change over time, and current smoking only decreased from 2010 to 2012. Compared with non-pregnant patients, a lower percentage of pregnant patients were provided counseling., Conclusions: Findings suggest that incentives for MU of EHRs increase the odds of smoking assessment and cessation assistance, which could lead to decreased smoking rates among vulnerable populations. Continued efforts for provision of cessation assistance among pregnant patients is warranted., (Copyright © 2017 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

Objective: To demonstrate use of the electronic health record (EHR) for health insurance surveillance and identify factors associated with lack of coverage., Materials and Methods: Using EHR data, we conducted a retrospective, longitudinal cohort study of adult patients (n = 279 654) within a national network of community health centers during a 2-year period (2012-2013)., Results: Factors associated with higher odds of being uninsured (vs Medicaid-insured) included: male gender, age >25 years, Hispanic ethnicity, income above the federal poverty level, and rural residence (P < .01 for all). Among patients with no insurance at their initial visit (n = 114 000), 50% remained uninsured for every subsequent visit., Discussion: During the 2 years prior to 2014, many patients utilizing community health centers were unable to maintain stable health insurance coverage., Conclusion: As patients gain access to health insurance under the Affordable Care Act, the EHR provides a novel approach to help track coverage and support vulnerable patients in gaining and maintaining coverage., (© The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

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.

Objective: To validate electronic health record (EHR) insurance information for low-income pediatric patients at Oregon community health centers (CHCs), compared to reimbursement data and Medicaid coverage data., Materials and Methods: Subjects Children visiting any of 96 CHCs (N = 69 189) from 2011 to 2012. Analysis The authors measured correspondence (whether or not the visit was covered by Medicaid) between EHR coverage data and (i) reimbursement data and (ii) coverage data from Medicaid., Results: Compared to reimbursement data and Medicaid coverage data, EHR coverage data had high agreement (87% and 95%, respectively), sensitivity (0.97 and 0.96), positive predictive value (0.88 and 0.98), but lower kappa statistics (0.32 and 0.49), specificity (0.27 and 0.60), and negative predictive value (0.66 and 0.45). These varied among clinics., Discussion/conclusions: EHR coverage data for children had a high overall correspondence with Medicaid data and reimbursement data, suggesting that in some systems EHR data could be utilized to promote insurance stability in their patients. Future work should attempt to replicate these analyses in other settings., (© The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

The objective of this study was to develop methodologies for creating child-parent 'links' in two healthcare-related data sources. We linked children and parents who were patients in a network of Oregon clinics with a shared electronic health record (EHR), using data that reported the child's emergency contact information or the 'guarantor' for the child's visits. We also linked children and parents enrolled in the Oregon Health Plan (OHP; Oregon's public health insurance programs), using administrative data; here, we defined a 'child' as aged <19 years and identified potential 'parents' from among adults sharing the same OHP household identification (ID) number. In both data sources, parents had to be 12-55 years older than the child. We used OHP individual client ID and EHR patient ID numbers to assess the quality of our linkages through cross-validation. Of the 249,079 children in the EHR dataset, we identified 62,967 who had a 'linkable' parent with patient information in the EHR. In the OHP data, 889,452 household IDs were assigned to at least one child; 525,578 with a household ID had a 'linkable' parent (272,578 households). Cross-validation of linkages revealed 99.8 % of EHR links validated in OHP data and 97.7 % of OHP links validated in EHR data. The ability to link children and their parents in healthcare-related datasets will be useful to inform efforts to improve children's health. Thus, we developed strategies for linking children with their parents in an EHR and a public health insurance administrative dataset.

Objective: This study compared the preventive service utilization of uninsured patients receiving care at Oregon community health centers (CHCs) in 2008 through 2011 with that of continuously insured patients at the same CHCs in the same period, using electronic health record (EHR) data., Methods: We performed a retrospective cohort analysis, using logistic mixed effects regression modeling to calculate odds ratios and rates of preventive service utilization for patients without insurance, or with continuous insurance., Results: CHCs provided many preventive services to uninsured patients. Uninsured patients were less likely than continuously insured patients to receive 5 of 11 preventive services, ranging from OR 0.52 (95% CI: 0.35-0.77) for mammogram orders to 0.75 (95% CI: 0.66-0.86) for lipid panels. This disparity persisted even in patients who visited the clinic regularly., Conclusion: Lack of insurance is a barrier to preventive service utilization, even in patients who can access care at a CHC. Policymakers in the United States should continue to address this significant prevention disparity., (Copyright © 2014 Elsevier Inc. All rights reserved.)

To compare the agreement of electronic health record (EHR) data versus Medicaid claims data in documenting adult preventive care. Insurance claims are commonly used to measure care quality. EHR data could serve this purpose, but little information exists about how this source compares in service documentation. For 13 101 Medicaid-insured adult patients attending 43 Oregon community health centers, we compared documentation of 11 preventive services, based on EHR versus Medicaid claims data. Documentation was comparable for most services. Agreement was highest for influenza vaccination (κ =  0.77; 95% CI 0.75 to 0.79), cholesterol screening (κ = 0.80; 95% CI 0.79 to 0.81), and cervical cancer screening (κ = 0.71; 95% CI 0.70 to 0.73), and lowest on services commonly referred out of primary care clinics and those that usually do not generate claims. EHRs show promise for use in quality reporting. Strategies to maximize data capture in EHRs are needed to optimize the use of EHR data for service documentation., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Objective: To evaluate selected Children's Health Insurance Program Reauthorization Act claims-based quality measures using claims data alone, electronic health record (EHR) data alone, and both data sources combined., Methods: Our population included pediatric patients from 46 clinics in the OCHIN network of community health centers, who were continuously enrolled in Oregon's public health insurance program during 2010. Within this population, we calculated selected pediatric care quality measures according to the Children's Health Insurance Program Reauthorization Act technical specifications within administrative claims. We then calculated these measures in the same cohort, by using EHR data, by using the technical specifications plus clinical data previously shown to enhance capture of a given measure. We used the k statistic to determine agreement in measurement when using claims versus EHR data. Finally, we measured quality of care delivered to the study population, when using a combined dataset of linked, patient-level administrative claims and EHR data., Results: When using administrative claims data, 1.0% of children (aged 3-17) had a BMI percentile recorded, compared with 71.9% based on the EHR data (k agreement [k] # 0.01), and 72.0% in the combined dataset. Among children turning 2 in 2010, 20.2% received all recommended immunizations according to the administrative claims data, 17.2% according to the EHR data (k = 0.82), and 21.4% according to the combined dataset., Conclusions: Children's care quality measures may not be accurate when assessed using only administrative claims. Adding EHR data to administrative claims data may yield more complete measurement.

Objective: Health insurance options are changing. Electronic health record (EHR) databases present new opportunities for providers to track the insurance coverage status of their patients. This study demonstrates the use of EHR data for this purpose., Methods: Using EHR data from the OCHIN Network of community health centers, we conducted a retrospective cohort study of data from children presenting to a community health center in 2010-2011 (N = 185,959). We described coverage patterns for children, used generalized estimating equation logistic regression to compare uninsured children with those with insurance, and assessed insurance status at subsequent visits., Results: At their first visit during the study period, 21% of children had no insurance. Among children uninsured at a first visit, 30% were uninsured at all subsequent visits. In multivariable analyses (including gender, age, race, ethnicity, language, income, location, and type of clinic), we observed significant differences in the characteristics of children who were uninsured as compared with those with insurance coverage. For example, compared with white, non-Hispanic children, nonwhite and/or Hispanic children had lower odds of being uninsured than having Medicaid/Medicare (adjusted odds ratio, 0.73; 95% confidence interval: 0.71-0.75) but had higher odds of being uninsured than having commercial insurance (adjusted odds ratio, 1.50; 95% confidence interval: 1.44-1.56)., Conclusions: Nearly one-third of children uninsured at their first visit remained uninsured at all subsequent visits, which suggests a need for clinics to conduct insurance surveillance and develop mechanisms to assist patients with obtaining coverage. EHRs can facilitate insurance surveillance and inform interventions aimed at helping patients obtain and retain coverage.

Background: It is uncertain if the American College of Cardiology/American Heart Association (ACC/AHA) 2013 guidelines for the use of HMGCoA reductase inhibitors (statins) were associated with increased statin eligibility and prescribing across underserved groups. Objective: To analyze, by race, ethnicity, and preferred language, patients with indications for and presence of a statin prescription before and after the guideline change. Design: Retrospective cohort study. Setting: Multistate community health center (CHC) network with linked electronic health records. Patients: Low-income patients aged ≥ 50 with a primary care visit in 2009–2013 or 2014–2018. Main Measures: (1) Odds of each race/ethnicity/language group meeting statin eligibility via the National Cholesterol Education Program Adult Treatment Panel III Guidelines in 2009–2013 or the ACC/AHA guidelines in 2014–2018. (2) Among those eligible, odds of each group in each period with a statin prescription. Key Results: In 2009–2013 (n = 109,330), non-English-preferring Latino (OR = 1.10, 95% CI = 1.03, 1.17), White (OR = 1.41, 95% CI = 1.16, 1.72), and Black patients (OR = 1.25, 95% CI = 1.11, 1.42), were more likely than English-preferring non-Hispanic Whites to meet guideline criteria for statins. Non-English-preferring Black patients, when eligible, were no more likely than non-Hispanic Whites to have statin prescriptions (OR = 1.16, 95% CI = 0.88, 1.54). In 2014–2018 (n = 319,904), English-preferring Latino patients (OR = 1.02, 95% CI = 0.96–1.07) and non-English-preferring Black patients (OR = 1.08, 95% CI = 0.98, 1.19) had similar odds of statin prescription to English-preferring non-Hispanic White patients. English-preferring Black patients were less likely (OR = 0.95, 95% CI = 0.91–0.99) to have a prescription than English-preferring non-Hispanic Whites. Conclusion: Across the 2013 ACC/AHA guideline change in CHCs serving low-income patients, non-English-preferring patients were consistently more likely to be eligible for and have been prescribed statins. English-preferring Latino and English-preferring Black patients experienced reduced prescribing, comparatively, after the guideline change. Further work should explore the contextual factors that may influence guideline effectiveness and care equity. [ABSTRACT FROM AUTHOR]

Introduction Country of birth/nativity information may be crucial to understanding health equity in Latino populations and is routinely called for in health services literature assessing cardiovascular disease and risk, but is not thought to co-occur with longitudinal, objective health information such as that found in electronic health records (EHRs). Methods We used a multistate network of community health centres to describe the extent to which country of birth is recorded in EHRs in Latinos, and to describe demographic features and cardiovascular risk profiles by country of birth. We compared geographical/demographic/clinical characteristics, from 2012 to 2020 (9 years of data), of 914 495 Latinos recorded as US-born, non-US-born and without a country of birth recorded. We also described the state in which these data were collected. Results Country of birth was collected for 127 138 Latinos in 782 clinics in 22 states. Compared with those with a country of birth recorded, Latinos without this record were more often uninsured and less often preferred Spanish. While covariate adjusted prevalence of heart disease and risk factors were similar between the three groups, when results were disaggregated to five specific Latin countries (Mexico, Guatemala, Dominican Republic, Cuba, El Salvador), significant variation was observed, especially in diabetes, hypertension and hyperlipidaemia. Conclusions In a multistate network, thousands of non-US-born, US-born and patients without a country of birth recorded had differing demographic characteristics, but clinical variation was not observed until data was disaggregated into specific country of origin. State policies that enhance the safety of immigrant populations may enhance the collection of health equity related data. Rigorous and effective health equity research using Latino country of birth information paired with longitudinal healthcare information found in EHRs might have significant potential for aiding clinical and public health practice, but it depends on increased, widespread and accurate availability of this information, co-occurring with other robust demographic and clinical data nativity. [ABSTRACT FROM AUTHOR]

Medication maintenance is critical in the management of asthma. We investigated the differences in electronic health record (EHR) documentation of medication refills for Spanish- and English-speaking Latino children and non-Hispanic white children by examining rates of albuterol rescue inhaler refills from 2005 to 2017, and and inhaled corticosteroid refills from 2015 to 2017 in a multi-state network of community health centers (CHCs). We used data from the ADVANCE network of CHCs. Our sample consisted of children aged 3–17, with a diagnosis of asthma and either albuterol or inhaled corticosteroid prescriptions (n = 39,162; n = 4,738 children, respectively). Negative binomial regression was used to calculate rates of refills per prescription adjusted for relevant patient-level covariates. Analyses stratified by asthma severity were also conducted. English-speaking Latino children had lower rates of albuterol refills compared with non-Hispanic white children (rate ratio [RR] = 0.88, 95% confidence interval [CI]: 0.80–0.98), a trend that persisted among children with moderate/severe persistent asthma severity (RR = 0.85, 95% CI: 0.76–0.95). Spanish-speaking Latino and non-Hispanic white children had similar albuterol refills. Inhaled corticosteroid refill rates were comparable between all groups. In a multi-state network, these findings suggest that CHCs deliver equitable asthma care related to prescription refills between their Latino and white patients, but there is still opportunity for providers to ensure that their English-speaking Latino patients have access to necessary emergency asthma medication. [ABSTRACT FROM AUTHOR]

BACKGROUND: Receipt of recommended well-child care is lowest for children without insurance, many of whom receive care in community health centers (CHCs). OBJECTIVE: TO understand if there is an association between parent preventive care and their children's well-child visits. METHODS: We used electronic health record data to identify children and link them to parents both seen in an OCHIN network (CHC; n = 363 clinics from 17 states), randomly selected a child aged 3 to 17 with >1 ambulatory visit between 2015 and 2018. We employed a retrospective, cohort study design and used general estimating equations Poisson regression to estimate yearly rates of well-child visits based on parent preventive care adjusted for relevant covariates and stratified by child age for 3 linked samples: mother only, father only, and two parents. RESULTS: We included 75,398 linked mother only pairs, 12,438 in our father only, and 4,156 in our 2-parent sample. Children in the mother only sample had a 6% greater rate of yearly well-child visits when their mother received preventive care (adjusted rate ratio [ ARR] = 1.06: 95% Cl = 1.03-1.08) compared to no preventive care. Children in the father only sample had a 7% greater rate of yearly well-child visits when their father received preventive care (ARR = 1.07; 95% CI = 1.04-1.11) versus no preventive care. Children in the two parent sample had an 11 % greater rate of yearly well-child visits when both parents received preventive care (ARR = 1.11; 95% CI = 1.03-1.19) computed to neither receiving preventive care. CONCLUSIONS: These findings suggest focusing on receipt of healthcare for the whole family may improve well-child visit rates. [ABSTRACT FROM AUTHOR]

BACKGROUND: Foreign-born Latino children in the United States (US) have poor asthma outcomes, but the role of routine care utilization in these outcomes is unclear. Our objective was to compare select ambulatory care utilization measures for asthma between foreign-born Latino, US-born Latino, and non-Hispanic white children. METHODS: Using a multistate network of clinics with a linked electronic health record, we compared the International Classification of Disease (ICD)-coded asthma diagnosis among those with respiratory symptoms, electronic health records documentation of diagnosis, prescriptions, and influenza vaccination of foreign-born and US-born Latino children, and non-Hispanic white children over a 10+ year study period. We also examined outcomes by country of birth in children from Mexico, Cuba, and Guatemala. RESULTS: Among our study population (n = 155,902), 134,570 were non-Hispanic white, 19,143 were US-born Latino, and 2189 were foreign-born Latino. Among those with suspicious respiratory symptoms, there was no difference between these groups in the predicted probability of an ICD-coded asthma diagnosis. US-born Latino children with asthma were less likely to have asthma documented on their problem list, more likely to have an albuterol prescription, and less likely to have an inhaled steroid prescribed. All Latino children had higher rates of influenza vaccination than non-Hispanic white children. CONCLUSIONS: In a national network, there were few disparities between Latino (US- and foreign-born) children and non-Hispanic white comparators in many common asthma care services, except some measures in US-born Latino children. Providers should understand that their US-born Latino children may be at elevated risk for not receiving adequate asthma care. [ABSTRACT FROM AUTHOR]

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. 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. 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. 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. [ABSTRACT FROM AUTHOR]

Introduction: National reports suggest that Hispanic patients may underutilize influenza and pneumococcal vaccination, although studies sometimes conflict on this point. A clearer picture of adult immunization utilization in older Hispanic patients is necessary to ensure equity in adult vaccinations. Methods: Using electronic health records from 648 community health centers (CHCs) across 21 states, we compared English‐preferring Hispanic patients, Spanish‐preferring Hispanic patients, and Non‐Hispanic White (NHW) adults aged ≥50 years across five outcomes between 2012–2017: (1) Odds of ever receiving pneumococcal vaccination after age 65, (2) Odds of ever receiving ≥2 pneumococcal vaccinations for those ≥65, (3) odds of vaccination between the ages of 50 and 64 for those with diabetes or heart disease, (4) odds of influenza vaccine, and (5) annual rate of influenza vaccination. Results: Of our total study sample (N = 143,869), 85,562 were age 50–64 during the entire study period, and 65,977 were ≥65 at some point during the study period. In patients aged 50–64, Spanish‐preferring Hispanic patients were more likely to have ever had an influenza vaccination (covariate‐adjusted odds ratio [aOR] = 1.33, 95% CI = 1.29–1.37), had higher rates of annual influenza vaccination (covariate‐adjusted rate ratio [aRR] = 1.41, 95% CI = 1.38–1.44), and higher odds of pneumococcal vaccination (aOR = 1.87, 95% CI = 1.76–1.98) than NHW patients. These findings were similar in Spanish‐preferring Hispanic patients ≥65. English‐preferring Hispanics ≥65 were less likely than NHW patients to ever have an influenza vaccination (aOR = 0.91, 95% CI = 0.85–0.98) and to have ever received at least one (aOR = 0.92, 95% CI = 0.86–0.99) or two (aOR = 0.86, 95% CI = 0.77–0.95) pneumococcal vaccine doses. Conclusions: In a multistate CHC network, Spanish‐preferring Hispanic patients were more likely to receive influenza and pneumococcal vaccinations than NHW patients; older English‐preferring Hispanic patients were often less likely than NHW patients to receive these vaccinations. In vaccine initiatives, English‐preferring Hispanic patients may be at higher risk of vaccination inequity. [ABSTRACT FROM AUTHOR]

Background: Many cancer survivors receive primary care in community health centers (CHCs). Cancer history is an important factor to consider in the provision of primary care, yet little is known about the completeness or accuracy of cancer history data contained in CHC electronic health records (EHRs).Methods: We probabilistically linked EHR data from more than1.5 million adult CHC patients to state cancer registries in California, Oregon, and Washington and estimated measures of agreement (eg, kappa, sensitivity, specificity). We compared demographic and clinical characteristics of cancer patients as estimated by each data source, evaluating distributional differences with absolute standardized mean differences.Results: A total 74 707 cancer patients were identified between the 2 sources (EHR only, n = 22 730; registry only, n = 23 616; both, n = 28 361). Nearly one-half of cancer patients identified in registries were missing cancer documentation in the EHR. Overall agreement of cancer ascertainment in the EHR vs cancer registries (gold standard) was moderate (kappa = 0.535). Cancer site-specific agreement ranged from substantial (eg, prostate and female breast; kappa > 0.60) to fair (melanoma and cervix; kappa < 0.40). Comparing population characteristics of cancer patients as ascertained from each data source, groups were similar for sex, age, and federal poverty level, but EHR-recorded cases showed greater medical complexity than those ascertained from cancer registries.Conclusions: Agreement between EHR and cancer registry data was moderate and varied by cancer site. These findings suggest the need for strategies to improve capture of cancer history information in CHC EHRs to ensure adequate delivery of care and optimal health outcomes for cancer survivors. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objective: We sought to understand how Affordable Care Act (ACA) Medicaid expansion insurance coverage gains are associated with changes in diabetes-related biomarkers.Research Design and Methods: This was a retrospective observational cohort study using electronic health record data from 178 community health centers (CHCs) in the ADVANCE (Accelerating Data Value Across a National Community Health Center Network) network. We assessed changes in diabetes-related biomarkers among adult patients with diabetes in 10 Medicaid expansion states (n = 25,279), comparing newly insured with continuously insured, discontinuously insured, and continuously uninsured patients pre- to post-ACA expansion. Primary outcomes included changes from 24 months pre- to 24 months post-ACA in glycosylated hemoglobin (HbA1c), systolic (SBP) and diastolic (DBP) blood pressure, and LDL cholesterol levels.Results: Newly insured patients exhibited a reduction in adjusted mean HbA1c levels (8.24% [67 mmol/mol] to 8.17% [66 mmol/mol]), which was significantly different from continuously uninsured patients, whose HbA1c levels increased (8.12% [65 mmol/mol] to 8.29% [67 mmol/mol]; difference-in-differences [DID] -0.24%; P < 0.001). Newly insured patients showed greater reductions than continuously uninsured patients in adjusted mean SBP (DID -1.8 mmHg; P < 0.001), DBP (DID -1.0 mmHg; P < 0.001), and LDL (DID -3.3 mg/dL; P < 0.001). Among patients with elevated HbA1c in the 3 months prior to expansion, newly insured patients were more likely than continuously uninsured patients to have a controlled HbA1c measurement by 24 months post-ACA (hazard ratio 1.25; 95% CI 1.02-1.54].Conclusions: Post-ACA, newly insured patients had greater improvements in diabetes-related biomarkers than continuously uninsured, discontinuously insured, or continuously insured patients. Findings suggest that health insurance gain via ACA facilitates access to appropriate diabetes care, leading to improvements in diabetes-related biomarkers. [ABSTRACT FROM AUTHOR]

Background: Primary care providers must understand the use patterns, clinical complexity, and primary care needs of cancer survivors to provide quality health care services. However, to the authors' knowledge, little is known regarding the prevalence and health care needs of this growing population, particularly in safety net settings.Methods: The authors identified adults with a history of cancer documented in primary care electronic health records within a network of community health centers (CHCs) in 19 states. The authors estimated cancer history prevalence among >1.2 million patients and compared sex-specific site distributions with national estimates. Each survivor was matched to 3 patients without cancer from the same set of clinics. The demographic characteristics, primary care use, and comorbidity burden then were compared between the 2 groups, assessing differences with absolute standardized mean differences (ASMDs). ASMD values >0.1 denote meaningful differences between groups. Generalized estimating equations yielded adjusted odds ratios (aORs) for select indicators.Results: A total of 40,266 cancer survivors were identified (prevalence of 3.0% of adult CHC patients). Compared with matched cancer-free patients, a higher percentage of survivors had ≥6 primary care visits across 3 years (62% vs 48%) and were insured (83% vs 74%) (ASMD, >0.1 for both). Cancer survivors had excess medical complexity, including a higher prevalence of depression, asthma/chronic obstructive pulmonary disease, and liver disease (ASMD, >0.1 for all). Survivors had higher odds of any opioid prescription (aOR, 1.23; 95% CI, 1.19-1.27) and chronic opioid therapy (aOR, 1.27; 95% CI, 1.23-1.32) compared with matched controls (P < .001 for all).Conclusions: Identifying cancer survivors and understanding their patterns of utilization and physical and mental comorbidities present an opportunity to tailor primary health care services to this population. [ABSTRACT FROM AUTHOR]

Obstructive pulmonary disease outcomes in the United States differ between Latinos and non-Hispanic whites. There is little objective data about diagnosis prevalence and primary care visit frequency in these disease processes. We used electronic health record data to perform a retrospective cohort analysis of 34,849 low-income patients seen at Oregon community health centers between 2009 and 2013 to assess joint racial/ethnic and insurance disparities in diagnosis and visit rates between Latino and non-Hispanic white patients. The overall study prevalence of obstructive lung disease was 18%. Latinos had lower odds of obstructive lung disease diagnosis (OR 0.37, 95% CI 0.30–0.44). Among those diagnosed prior to 2009, the uninsured (regardless of race/ethnicity) had lower visit rates during 2009–2013 than the insured. This study identified racial/ethnic disparities in the diagnosis of obstructive pulmonary disease between Latinos and non-Hispanic Whites, confirming trends observed in survey research but controlling for important confounders. Health insurance was associated with basic care utilization, suggesting that lack of health insurance could lessen the quality of care for obstructive pulmonary disease in Latino and non-Hispanic white patients. [ABSTRACT FROM AUTHOR]

Purpose: Improving primary care quality is a national priority, but little is known about the extent to which small to medium-size practices use quality improvement (QI) strategies to improve care. We examined variations in use of QI strategies among 1,181 small to medium-size primary care practices engaged in a national initiative spanning 12 US states to improve quality of care for heart health and assessed factors associated with those variations.Methods: In this cross-sectional study, practice characteristics were assessed by surveying practice leaders. Practice use of QI strategies was measured by the validated Change Process Capability Questionnaire (CPCQ) Strategies Scale (scores range from -28 to 28, with higher scores indicating more use of QI strategies). Multivariable linear regression was used to examine the association between practice characteristics and the CPCQ strategies score.Results: The mean CPCQ strategies score was 9.1 (SD = 12.2). Practices that participated in accountable care organizations and those that had someone in the practice to configure clinical quality reports from electronic health records (EHRs), had produced quality reports, or had discussed clinical quality data during meetings had higher CPCQ strategies scores. Health system-owned practices and those experiencing major disruptive changes, such as implementing a new EHR system or clinician turnover, had lower CPCQ strategies scores.Conclusion: There is substantial variation in the use of QI strategies among small to medium-size primary care practices across 12 US states. Findings suggest that practices may need external support to strengthen their ability to do QI and to be prepared for new payment and delivery models. [ABSTRACT FROM AUTHOR]

Background: Understanding the impact of health insurance is critical, particularly in the era of Affordable Care Act Medicaid expansion. The electronic health record (EHR) provides new opportunities to quantify health outcomes.Objective: To assess changes in biomarkers of chronic disease among community health center (CHC) patients who gained Medicaid coverage with the Oregon Medicaid expansion (2008-2011).Design: Prospective cohort. Patients were followed for 24 months, and rate of mean biomarker change was calculated. Time to a controlled follow-up measurement was compared using Cox regression models.Setting/patients: Using EHR data from OCHIN (a non-profit network of CHCs) linked to state Medicaid data, we identified three cohorts of patients with uncontrolled chronic conditions (diabetes, hypertension, and hyperlipidemia). Within these cohorts, we included patients who gained Medicaid coverage along with a propensity score-matched comparison group who remained uninsured (diabetes n = 608; hypertension n = 1244; hyperlipidemia n = 546).Main Measures: Hemoglobin A1c (HbA1c) for the diabetes cohort, systolic and diastolic blood pressure (SBP and DBP, respectively) for the hypertension cohort, and low-density lipoprotein (LDL) for the hyperlipidemia cohort.Key Results: All cohorts improved over time. Compared to matched uninsured patients, adults in the diabetes and hypertension cohorts who gained Medicaid coverage were significantly more likely to have a follow-up controlled measurement (hazard ratio [HR] =1.26, p = 0.020; HR = 1.35, p < 0.001, respectively). No significant difference was observed in the hyperlipidemia cohort (HR = 1.09, p = 0.392).Conclusions: OCHIN patients with uncontrolled chronic conditions experienced objective health improvements over time. In two of three chronic disease cohorts, those who gained Medicaid coverage were more likely to achieve a controlled measurement than those who remained uninsured. These findings demonstrate the effective care provided by CHCs and the importance of health insurance coverage within a usual source of care setting.Clinical Trials Registration: NCT02355132 [ https://clinicaltrials.gov/ct2/show/NCT02355132 ]. [ABSTRACT FROM AUTHOR]

Background: It is hypothesized that Affordable Care Act (ACA) Medicaid expansions could substantially improve access to health insurance and healthcare services for patients at risk for diabetes mellitus (DM), with pre-DM, or already diagnosed with DM. The ACA called for every state to expand Medicaid coverage by 2014. In a 2012 legal challenge, the US Supreme Court ruled that states were not required to implement Medicaid expansions. This 'natural experiment' presents a unique opportunity to learn whether and to what extent Medicaid expansion can affect healthcare access and services for patients with DM risk, pre-DM, or DM.Methods/design: Data from electronic health records (EHRs) from the Accelerating Data Value Across a National Community Health Center Network (ADVANCE) clinical data research network, which has data from >700 community health centers (CHCs), was included in the study. EHR data will be linked to Oregon Medicaid claims data. Data collection will include information on changes in health insurance, service receipt, and health outcomes, spanning 9 years (pre- and post-expansion), comparing states that expanded Medicaid, and those that did not. Patients included in this study will be diagnosed with DM, be at risk for DM, or have pre-DM, between the ages of 19 and 64, with ≥1 ambulatory visit. Sample size is estimated to be roughly 275,000 patients. Biostatistical analyses will include the difference-in-differences (DID) methodology and a generalized linear mixed model. Econometric analyses will include a DID two-part method to calculate the difference in Medicaid expenditures in Oregon among newly insured CHC patients.Discussion: Findings will have national relevance on DM health services and outcomes and will be shared through national conferences and publications. The findings will provide information needed to impact the policy as it is related to access to health insurance and receipt of healthcare among a vulnerable population.Trial Registration: This project is registered with ClinicalTrials.gov ( NCT02685384 ). Registered 18 May 2016. [ABSTRACT FROM AUTHOR]

Electronic health record (EHR) tools such as documentation shortcuts and ordering templates are designed to enhance both the efficiency and quality of care delivery. Use of such tools vary widely in primary care. Understanding patterns of use as a means to identify priority areas for improvement are lacking. Objective: This study is designed to identify and understand patterns of EHR efficiency use among primary care clinicians as a means to inform training support needs. Study Design: Retrospective observational study. Setting or Dataset: 340 Community Health Centers (CHCs) across 48 US states from the OCHIN Network. Population studied: The OCHIN's network and 2033 primary care clinicians engaged in patient care at least 2 days a week during DEC 2019-FEB 2020. Methods: Six EHR efficiency indicators were drawn from the Epic EHR Signal efficiency indicators which are automatically generated monthly for clinicians. Indicators include: use of quick actions, preference lists, level of service and diagnosis speed buttons and chart search functions and notes written with smart tools. A weighted score of these indicators represented overall EHR proficiency with a possible range of 0-10 with higher scores suggesting higher efficiency. Latent profile analysis (LPA) was used to identify clusters of clinicians defined by distinct patterns of efficiency indicators. Results: The median EHR proficiency score was 4 and ranged from 0 to 9.5. The 9 cluster LPA solution the best overall fit. Clusters represented different patterns with notable strengths and deficiencies in EHR use efficiency. Cluster 2 was large (n=518) and characterized by being low on all indicators except for chart search. In contrast, cluster 9 was very small (n=12) and characterized by high scores for 4/6 indicators and low on quick actions. Conclusions: Substantial variation in EHR use efficiency among primary care clinicians was observed and can be represented by nine different patterns of indicators. These patterns show strengths and deficiencies in EHR use efficiency and could guide a tailored training approach to improve EHR efficiency. [ABSTRACT FROM AUTHOR]

Atherosclerotic cardiovascular disease (ASCVD) disproportionally affects racial and ethnic minority populations. Statin prescribing guidelines changed in 2013 to improve ASCVD prevention. It is unknown whether risk screening for statin eligibility differed across race and ethnicity over this guideline change. We examine racial/ethnic/language differences in screening measure prevalence for period-specific statin consideration using a retrospective cohort design and linked electronic health records from 635 community health centers in 24 U.S. states. Adults 50+ years, without known ASCVD, and ≥ 1 visit in 2009-2013 and/or 2014-2018 were included, grouped as: Asian, Latino, Black, or White further distinguished by language preference. Outcomes included screening measure prevalence for statin consideration, 2009-2013: low-density lipoprotein (LDL), 2014-2018: pooled cohort equation (PCE) components age, sex, race, systolic blood pressure, total cholesterol, high-density lipoprotein, smoking status. Among patients seen both periods, change in period-specific measure prevalence was assessed. Adjusting for sociodemographic and clinical factors, compared to English-preferring White patients, all other groups were more likely to have LDL documented (2009-2013, n = 195,061) and all PCE components documented (2014-2018, n = 344,504). Among patients seen in both periods (n = 128,621), all groups had lower odds of PCE components versus LDL documented in the measures' respective period; English-preferring Black adults experienced a greater decline compared to English-preferring White adults (OR 0.81; 95% CI: 0.72-0.91). Racial/ethnic/language disparities in documented screening measures that guide statin therapy for ASCVD prevention were unaffected by a major guideline change advising this practice. It is important to understand whether the newer guidelines have altered disparate prescribing and morbidity/mortality for this disease. [ABSTRACT FROM AUTHOR]

Background: The Agency for Healthcare Research and Quality (AHRQ) launched the EvidenceNOW Initiative to rapidly disseminate and implement evidence-based cardiovascular disease (CVD) preventive care in smaller primary care practices. AHRQ funded eight grantees (seven regional Cooperatives and one independent national evaluation) to participate in EvidenceNOW. The national evaluation examines quality improvement efforts and outcomes for more than 1500 small primary care practices (restricted to those with fewer than ten physicians per clinic). Examples of external support include practice facilitation, expert consultation, performance feedback, and educational materials and activities. This paper describes the study protocol for the EvidenceNOW national evaluation, which is called Evaluating System Change to Advance Learning and Take Evidence to Scale (ESCALATES).Methods: This prospective observational study will examine the portfolio of EvidenceNOW Cooperatives using both qualitative and quantitative data. Qualitative data include: online implementation diaries, observation and interviews at Cooperatives and practices, and systematic assessment of context from the perspective of Cooperative team members. Quantitative data include: practice-level performance on clinical quality measures (aspirin prescribing, blood pressure and cholesterol control, and smoking cessation; ABCS) collected by Cooperatives from electronic health records (EHRs); practice and practice member surveys to assess practice capacity and other organizational and structural characteristics; and systematic tracking of intervention delivery. Quantitative, qualitative, and mixed methods analyses will be conducted to examine how Cooperatives organize to provide external support to practices, to compare effectiveness of the dissemination and implementation approaches they implement, and to examine how regional variations and other organization and contextual factors influence implementation and effectiveness.Discussion: ESCALATES is a national evaluation of an ambitious large-scale dissemination and implementation effort focused on transforming smaller primary care practices. Insights will help to inform the design of national health care practice extension systems aimed at supporting practice transformation efforts in the USA.Clinical Trial Registration: NCT02560428 (09/21/15). [ABSTRACT FROM AUTHOR]

OBJECTIVES: One in 5 people in the United States lives with chronic pain. Many patients with chronic pain experience a subset of specific co-occurring pain conditions that may share a common pain mechanism and that have been designated as chronic overlapping pain conditions (COPCs). Little is known about chronic opioid prescribing patterns among patients with COPCs in primary care settings, especially among socioeconomically vulnerable patients. This study aims to evaluate opioid prescribing among patients with COPCs in US community health centers and to identify individual COPCs and their combinations that are associated with long-term opioid treatment (LOT). STUDY DESIGN: Retrospective cohort study. METHODS: We conducted analyses of more than 1 million patients 18 years and older based on electronic health record data from 449 US community health centers across 17 states between January 1, 2009, and December 31, 2018. Logistic regression models were used to assess the relationship between COPCs and LOT. RESULTS: Individuals with COPCs were prescribed LOT 4 times more often than individuals without a COPC (16.9% vs 4.0%). The presence of chronic low back pain, migraine headache, fibromyalgia, or irritable bowel syndrome combined with any of the other COPCs increased the odds of LOT prescribing compared with the presence of a single COPC. CONCLUSIONS: Although LOT prescribing has declined over time, it remains relatively high among patients with certain COPCs and for those with multiple COPCs. These study findings suggest target populations for future interventions to manage chronic pain among socioeconomically vulnerable patients. [ABSTRACT FROM AUTHOR]

To estimate how the Affordable Care Act's Medicaid expansions will affect demand for services, we measured ambulatory care utilization among adult patients who gained insurance during Oregon's 2008 Medicaid expansion. Using electronic health record data from 67 community health centers, we assessed pre- and postcoverage utilization among patients who gained insurance, compared with patients continuously insured or uninsured. In comparisons of the pre- and postcoverage periods, mean annual encounters among persons who gained insurance increased 22% to 35%, but declined in the comparison groups. These findings suggest that providers should expect a significant increase in demand among patients who gain Medicaid coverage through the Affordable Care Act. [ABSTRACT FROM AUTHOR]

Only half of the United States population regularly receives recommended preventive care services. Alternative payment models (e.g., a per-member-per-month capitated payment model) may encourage the delivery of preventive services when compared to a fee-for-service visitbased model; however, evaluation is lacking in the United States. This study assesses the impact of implementing Oregon's Alternative Payment Methodology (APM) on orders for preventive services within community health centers (CHCs). This retrospective cohort study uses electronic health record data from the OCHIN, Inc., 2012-2018, analyzed in 2018-2019. Twenty-seven CHCs which implemented APM in 2013-2016 were compared to six non-APM CHCs. Clinic-level quarterly rates of ordering nine preventive services in 2012-2018 were calculated. For each phase and preventive service, we used difference-in-differences analysis to assess the APM impact on ordering preventive care. We found greater increases for APM CHCs compared to non-APM CHCs for orders of mammograms (difference-in-differences estimates (DDs) across four phases:1.69-2.45). Both groups had decreases in ordering cervical cancer screenings, however, APM CHCs had smaller decreases (DDs:1.62-1.93). The APM CHCs had significantly greater decreases in influenza vaccinations (DDs:0.17-0.32). There were no consistent significant differences in pre-post changes in APM vs. non-APM CHCs for cardiometabolic risk screenings, smoking status and depression assessments. There was nonsignificant change in the proportion of nontraditional encounters in APM clinics compared to controls. Transition from fee-for-service to an APM did not negatively impact delivery of preventive care. Further studies are needed to understand how to change encounter structures to best deliver recommended preventive care. [ABSTRACT FROM AUTHOR]

Introduction: Patients with multiple chronic conditions (multimorbidity) are seen commonly in primary care practices and often have suboptimal uptake of preventive care owing to competing treatment demands. The complexity of multimorbidity patterns and their impact on receiving preventive services is not fully understood. This study identifies multimorbidity combinations associated with low receipt of preventive services.Methods: This was a retrospective cohort study of U.S. community health center patients aged ≥19 years. Electronic health record data from 209 community health centers for the January 1, 2014-December 31, 2017 study period were analyzed in 2018-2019. Multimorbidity patterns included physical only, mental health only, and physical and mental health multimorbidity patterns, with no multimorbidity as a reference category. Electronic health record-based preventive ratios (number of months services were up-to-date/total months the patient was eligible for services) were calculated for the 14 preventive services. Negative binomial regression models assessed the relationship between multimorbidity physical and/or mental health patterns and the preventive ratio for each service.Results: There was a variation in receipt of preventive care between multimorbidity groups: individuals with mental health only multimorbidity were less likely to be up-to-date with cardiometabolic and cancer screenings than the no multimorbidity group or groups with physical health conditions, and the physical only multimorbidity group had low rates of depression screening.Conclusions: This study provided critical insights into receipt of preventive service among adults with multimorbidity using a more precise method for measuring up-to-date preventive care delivery. Findings would be useful to identify target populations for future intervention programs to improve preventive care. [ABSTRACT FROM AUTHOR]

Background: Patients with gaps in health insurance coverage often defer or forgo cancer prevention services. These delays in cancer detection and diagnoses lead to higher rates of morbidity and mortality and increased costs. Recent advances in health information technology (HIT) create new opportunities to enhance insurance support services that reduce coverage gaps through automated processes applied in healthcare settings. This study will assess the implementation of insurance support HIT tools and their effectiveness at improving patients' insurance coverage continuity and cancer screening rates.Methods/design: This study uses a hybrid cluster-randomized design-a combined effectiveness and implementation trial-in community health centers (CHCs) in the USA. Eligible CHC clinic sites will be randomly assigned to one of two groups in the trial's implementation component: tools + basic training (Arm I) and tools + enhanced training + facilitation (Arm II). A propensity score-matched control group of clinics will be selected to assess the tools' effectiveness. Quantitative analyses of the tools' impact will use electronic health record and Medicaid data to assess effectiveness. Qualitative data will be collected to evaluate the implementation process, understand how the HIT tools are being used, and identify facilitators and barriers to their implementation and use.Discussion: This study will test the effectiveness of HIT tools to enhance insurance support in CHCs and will compare strategies for facilitating their implementation in "real-world" practice settings. Findings will inform further development and, if indicated, more widespread implementation of insurance support HIT tools.Trial Registration: Clinical trial NTC02355262. [ABSTRACT FROM AUTHOR]

Parent and child vaccination behavior is related for human papillomavirus (HPV) and flu vaccine. Thus, it is likely that parental vaccination status is also associated with their children's adherence to guideline-concordant childhood vaccination schedules. We hypothesized that parent influenza (flu) vaccination would be associated with their child's vaccination status at age two. We used electronic health record data to identify children and linked parents seen in a community health center (CHC) within the OCHIN network (292 CHCs in 16 states). We randomly selected a child aged <2 years with ≥1 ambulatory visit between 2009-2018. Employing a retrospective, cohort study design, we used general estimating equations logistic regression to estimate the odds of a child being up-to-date on vaccinations based on their linked parents' flu vaccination status. We adjusted for relevant parent and child covariates and stratified by mother only, father only, and two-parent samples. The study included 40,007 family-units: mother only = 35,444, father only = 2,784, and two parents = 1,779. A higher percentage of children were fully vaccinated if their parent or parents received a flu vaccine. Children in the two-parent sample whose parents both received a flu vaccine had more than twice the odds of being fully vaccinated, and two and a half times the odds of being fully vaccinated except flu vaccine compared to children with two parents who did not receive a flu vaccine (covariate-adjusted odds ratio [aOR] = 2.39, 95% CI = 1.67, 3.43 and aOR = 2.54, 95% CI = 1.54, 4.19, respectively). Parent flu vaccination is associated with routine child vaccination. Future research is needed to understand if this relationship persists over time and in different settings. [ABSTRACT FROM AUTHOR]

Introduction: Colorectal cancer is the second leading cause of cancer deaths in Latinos in the U.S., but it is unclear, from previous research, whether Latinos have differing rates of colorectal cancer screening methods from those of non-Hispanic Whites.Methods: This study used electronic health records from 686 community health centers across 21 states in the Accelerating Data Value Across a National Community Health Center of the National Patient-Centered Clinical Research Network. Records from English-preferring Latinos, Spanish-preferring Latinos, and non-Hispanic Whites aged 50-75 years were included. A total of 5 outcomes were compared between 2012 and 2017 to provide a comprehensive view of colorectal cancer screening: (1) any colorectal cancer screening, (2) stool-based screening, (3) annual rates of stool testing, (4) any referral for lower gastrointestinal endoscopy, and (5) endoscopy referral among patients with a positive stool-based screening.Results: In this study (N=204,243), Spanish-preferring Latinos had higher odds of any colorectal cancer screening (OR=1.44, 95% CI=1.23, 1.68) and stool-based testing (OR=1.82, 95% CI=1.55, 2.13) than non-Hispanic Whites. English- and Spanish-preferring Latinos had lower odds of having ever had a referral for endoscopy in the study period than non-Hispanic Whites (English: OR=0.23, 95% CI=0.15, 0.34; Spanish: OR=0.55, 95% CI=0.40, 0.74), even with a positive stool-based screening (English: OR=0.14, 95% CI=0.06, 0.33; Spanish: OR=0.33, 95% CI=0.19, 0.57).Conclusions: In a multistate network of community health centers, Latino patients aged >50 years were more likely to receive stool-based screening tests for colorectal cancer than non-Hispanic Whites but were less likely to receive endoscopy referrals than non-Hispanic Whites, even when experiencing a positive stool-based screening test. Initiatives to improve Latino colorectal cancer outcomes should encourage indicated referrals for lower gastrointestinal endoscopy. [ABSTRACT FROM AUTHOR]

The Affordable Care Act (ACA) increased health insurance coverage throughout the United States and improved care delivery for some services. We assess whether ACA implementation and Medicaid expansion were followed by greater receipt of recommended preventive services among women and girls in a large network of community health centers. Using electronic health record data from 354 community health centers in 14 states (10 expansion, 4 nonexpansion), we used generalized estimating equations and difference-in-difference methods to compare receipt of six recommended preventive services (cervical cancer screening, human papilloma virus vaccination, chlamydia screening, influenza vaccination, human immunodeficiency virus screening, and blood pressure screening) among active female patients ages 11 to 65 (N = 711,121) before and after ACA implementation and between states that expanded versus did not expand Medicaid. Except for blood pressure screening, receipt of all examined preventive services increased after ACA implementation in both Medicaid expansion and nonexpansion states. Influenza vaccination and blood pressure screening increased more in expansion states (adjusted absolute prevalence difference-in-difference, 1.55; 95% confidence interval, 0.51–2.60; and 1.98; 95% confidence interval, 0.91–3.05, respectively). Chlamydia screening increased more in nonexpansion states (adjusted absolute prevalence difference-in-difference: −4.21; 95% confidence interval, −6.98 to −1.45). Increases in cervical cancer screening, human immunodeficiency virus screening, and human papilloma virus vaccination did not differ significantly between expansion and nonexpansion states. Among female patients at community health centers, receipt of recommended preventive care improved after ACA implementation in both Medicaid expansion and nonexpansion states, although the overall rates remained low. Continued support is needed to overcome barriers to preventive care in this population. [ABSTRACT FROM AUTHOR]

Background: Lack of insurance is associated with suboptimal receipt of diabetes preventive care. One known reason for this is an access barrier to obtaining healthcare visits; however, little is known about whether insurance status is associated with differential rates of receipt of diabetes care during visits. Purpose: To examine the association between health insurance and receipt of diabetes preventive care during an office visit. Methods: This retrospective cohort study used electronic health record and Medicaid data from 38 Oregon community health centers. Logistic regression was used to test the association between insurance and receipt of four diabetes services during an office visit among patients who were continuously uninsured (n=1,117); continuously insured (n=1,466); and discontinuously insured (n=336) in 2006-2007. Generalized estimating equations were used to account for within-patient correlation. Data were analyzed in 2013. Results: Overall, continuously uninsured patients had lower odds of receiving services at visits when due, compared to those who were continuously insured (AOR=0.73, 95% CI=0.66, 0.80). Among the discontinuously insured, being uninsured at a visit was associated with lower odds of receipt of services due at that visit (AOR=0.77, 95% CI=0.64, 0.92) than being insured at a visit. Conclusions: Lack of insurance is associated with a lower probability of receiving recommended services that are due during a clinic visit. Thus, the association between being uninsured and receiving fewer preventive services may not be completely mediated by access to clinic visits. [ABSTRACT FROM AUTHOR]

Prevention is critical to optimizing health, yet most people do not receive all recommended preventive services. As the complexity of preventive recommendations increases, there is a need for new measurements to capture the degree to which a person is up to date, and identify individual-level barriers and facilitators to receiving needed preventive care. We used electronic health record data from a national network of community health centers (CHCs) in the United States (US) during 2014-2017 to measure patient-level up-to-date status with preventive ratios (measuring up-to-date person-time denoted as a percent) for 12 preventive services and an aggregate preventive index. We use negative binomial regression to identify factors associated with up-to-date preventive care. We assessed 267,767 patients across 165 primary care clinics. Mean preventive ratios ranged from 8.7% for Hepatitis C screening to 83.3% for blood pressure screening. The mean aggregate preventive index was 43%. Lack of health insurance, smoking, and homelessness were associated with lower preventive ratios for most cancer and cardiovascular screenings (p < 0.05). Having more ambulatory visits, better continuity of care, and enrollment in the patient portal were positively associated with the aggregate preventive index (p < 0.05) and higher preventive ratios for all services (p < 0.05) except chlamydia and HIV screening. Overall, receipt of preventive services was low. CHC patients experience many barriers to receiving needed preventive care, but certain healthcare behaviors - regular visits, usual provider continuity, and patient portal enrollment - were consistently associated with more up-to-date preventive care. These associations should inform future efforts to improve preventive care delivery. [ABSTRACT FROM AUTHOR]