Accelerating Data Value Across A National Community Health Center Network Research Articles

Landscape of Pregnancy Care in US Community Health Centers.

Community health centers (CHCs) provide critical health care access for people who experience high risks during and after pregnancy, however it is unclear to what extent they provide prenatal care. This study seeks to describe clinic and patient characteristics associated with longitudinal prenatal care delivery in CHC settings. This retrospective cohort study utilized electronic health record (EHR) data from the Accelerating Data Value Across a National Community Health Center Network (ADVANCE) between 2018 to 2019 to describe prenatal care provision among CHCs (n = 408), and pregnant CHC patients (n = 28,578) and compared characteristics of patients who received longitudinal prenatal care at CHCs versus those who did not. 41% of CHCs provided longitudinal prenatal care; these CHCs were more likely to be larger, have multidisciplinary teams, and serve higher proportions of nonwhite or non-English speaking patients. Patients who received longitudinal prenatal care at CHCs were racially and ethnically diverse and many had comorbidities. Patients who received longitudinal prenatal care at CHCs (compared with pregnant patients who did not) were more likely to be white or Latinx and more likely to have non-English language preference. Many CHCs in this national network provide prenatal care and serve pregnant patients at high risk of pregnancy-related complications, including people of color, those with low income, and those with comorbidities. CHCs provide critical access to care for vulnerable populations and will be an important partner in work addressing inequities in maternal morbidity and mortality.

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

ObjectiveSocial deprivation is associated with worse asthma outcomes. The Social Deprivation Index is a composite measure of social determinants of health used to identify neighbourhood-level disadvantage in healthcare. Our objective...

Role of health insurance and neighborhood-level social deprivation on hypertension control following the affordable care act health insurance opportunities.

To understand if neighborhood-level social deprivation moderates the association between gaining health insurance and improved hypertension control. We used electronic health record (EHR) data from the Accelerating Data Value Across a National Community Health Center Network (ADVANCE) clinical data research network from five states that expanded Medicaid eligibility (CA, OH, OR, WA, WI). We include patients with hypertension aged 19-64. Controlled hypertension was assessed for four groups pre-(1/1/2012-12/31/2013) to post-(1/1/2014-12/31/2017) Affordable Care Act (ACA) Medicaid expansion: (1) newly insured, (2) continuously insured, (3) discontinuously insured, and (4) continuously uninsured. We also used Social Deprivation Index score to derive predicted probability of controlled hypertension using logistic mixed effects. N = 28,485 patients. All groups experienced improved hypertension control: the newly insured saw a greater increase than the other groups (8.6% vs. 0.9% for the continuously uninsured, 1.3% for the continuously and 3.0% for the discontinuously insured). The likelihood of hypertension control rose more for the newly insured (vs. the other insurance groups) for patients living in the most deprived neighborhoods (16% from pre- to post-ACA). Gaining health insurance was related to hypertension control; individuals living in the most disadvantaged communities experienced the greatest benefit. Ensuring health insurance access is important for cardiovascular health, especially among disadvantaged communities.

The Affordable Care Act: Effects of Insurance on Diabetes Biomarkers.

We sought to understand how Affordable Care Act (ACA) Medicaid expansion insurance coverage gains are associated with changes in diabetes-related biomarkers. 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. 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]. 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.

Using Electronic Health Records in Longitudinal Studies: Estimating Patient Attrition.

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. 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. 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. 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. 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. 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. 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.

Building Meaningful Patient Engagement in Research: Case Study From ADVANCE Clinical Data Research Network.

Strategies to engage patients to improve and enhance research and clinical care are increasingly being implemented in the United States, yet little is known about best practices for or the impacts of meaningful patient engagement. We describe and reflect on our patient stakeholder groups, engagement framework, experiences, and lessons learned in engaging patients in research, from generating proposal ideas to disseminating findings. The ADVANCE (Accelerating Data Value Across a National Community Health Center Network) clinical data research network is the nation's largest clinical dataset on the safety net, with outpatient clinical data from 122 health systems (1109 clinics) in 23 states. Patients stakeholders codeveloped the ADVANCE engagement framework and its implementation in partnership with network leaders. In phase I of ADVANCE, patients were involved with designing studies (input on primary outcome measures and methods) and usability testing (of the patient portal). In phase II, the network is prioritizing research training, dissemination opportunities, an "ambassador" program to pair more experienced patient stakeholders with those less experienced, and evaluation of engagement activities and impacts. The ADVANCE framework for patient engagement has successfully involved a diverse group of patients in the design, implementation, and interpretation of comparative effectiveness research. Our experience and framework can be used by other organizations and research networks to support patient engagement activities.

Protocol for the analysis of a natural experiment on the impact of the Affordable Care Act on diabetes care in community health centers

BackgroundIt 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/designData 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.DiscussionFindings 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 registrationThis project is registered with ClinicalTrials.gov (NCT02685384). Registered 18 May 2016.

The ADVANCE network: accelerating data value across a national community health center network.

The ADVANCE (Accelerating Data Value Across a National Community Health Center Network) clinical data research network (CDRN) is led by the OCHIN Community Health Information Network in partnership with Health Choice Network and Fenway Health. The ADVANCE CDRN will ‘horizontally’ integrate outpatient electronic health record data for over one million federally qualified health center patients, and ‘vertically’ integrate hospital, health plan, and community data for these patients, often under-represented in research studies. Patient investigators, community investigators, and academic investigators with diverse expertise will work together to meet project goals related to data integration, patient engagement and recruitment, and the development of streamlined regulatory policies. By enhancing the data and research infrastructure of participating organizations, the ADVANCE CDRN will serve as a ‘community laboratory’ for including disadvantaged and vulnerable patients in patient-centered outcomes research that is aligned with the priorities of patients, clinics, and communities in our network.