Rates of Undiagnosed Hypertension and Diagnosed Hypertension Without Anti-hypertensive Medication Following the Affordable Care Act

BACKGROUND

The Affordable Care Act (ACA) Medicaid expansion improved access to health insurance and health care services. This study assessed whether the rate of patients with undiagnosed hypertension and the rate of patients with hypertension without anti-hypertensive medication decreased post-ACA in community health center (CHC).

METHODS

We analyzed electronic health record data from 2012 to 2017 for 126,699 CHC patients aged 19-64 years with ≥1 visit pre-ACA and ≥1 post-ACA in 14 Medicaid expansion states. We estimated the prevalence of patients with undiagnosed hypertension (high blood pressure reading without a diagnosis for ≥1 day) and the prevalence of patients with hypertension without anti-hypertensive medication by year and health insurance type (continuously uninsured, continuously insured, gained insurance, and discontinuously insured). We compared the time to diagnosis or to anti-hypertensive medication pre- vs. post-ACA.

RESULTS

Overall, 37.3% of patients had undiagnosed hypertension and 27.0% of patients with diagnosed hypertension were without a prescribed anti-hypertensive medication for ≥1 day during the study period. The rate of undiagnosed hypertension decreased from 2012 through 2017. Those who gained insurance had the lowest rates of undiagnosed hypertension (2012: 14.8%; 2017: 6.1%). Patients with hypertension were also more likely to receive anti-hypertension medication during this period, especially uninsured patients who experienced the largest decline (from 47.0% to 8.1%). Post-ACA, among patients with undiagnosed hypertension, time to diagnosis was shorter for those who gained insurance than other insurance types.

CONCLUSIONS

Those who gained health insurance were appropriately diagnosed with hypertension faster and more frequently post-ACA than those with other insurance types.

CLINICAL TRIALS REGISTRATION

Trial Number NCT03545763.

Creation of a linked cohort of children and their parents in a large, national electronic health record dataset

To examine which parental health care and health factors are most strongly associated with a child's receipt of recommended care we must be able to link children to their parents in electronic health record data. Yet, there is not an easy way to link these data.To identify a national cohort of children that link to at least one parent in the same electronic health record dataset and describe their demographics.Methodology to link parents and children in electronic health records and descriptive sociodemographic data.Children with at least one encounter with a primary care clinician between Januray 1, 2007 and December 12, 2018 to a community health center in the OCHIN national network. We identified parents of these children who also had at least one encounter to a community health center in the network using emergency contact and guarantor record fields.A total of 227,552 children had parents with a linkable patient record. After exclusions, our final cohort included 213,513 distinct children with either one or two parent-links. 82% of children linked to a mother only, 14% linked to a father only, and 4% linked to both a mother and a father. Most families consisted of only one linked child (61%).We were able to link 33% of children to a parent in electronic health record data from a large network of community health centers across the United States. Further analyses utilizing these linkages will allow examination of the multi-level factors that impact a child's receipt of recommended health care.

Assessing Cancer History Accuracy in Primary Care Electronic Health Records Through Cancer Registry Linkage

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.

Associations of retention on buprenorphine for opioid use disorder with patient characteristics and models of care in the primary care setting

INTRODUCTION

Buprenorphine, a medication for opioid use disorder (OUD), can be administered within primary care; however, little is known about characteristics associated with retention on buprenorphine in these settings. This study examines patient correlates of buprenorphine retention and whether an integrated, interdisciplinary treatment model (buprenorphine and behavioral health) is associated with higher odds of buprenorphine retention than a primarily medication-only treatment model.

METHODS

Electronic health record data from adult patients with an OUD, ≥1 buprenorphine order and ≥1 visit to either of two primary care clinics between 9/2/2014-6/27/2018 were extracted (N = 494 patients). Two research team members reviewed the medication start and stop dates for each buprenorphine order and classified as retained (≥6 months of orders) or not retained (<6 months of orders). Logistic regressions estimated the odds of retention on buprenorphine by 1) patient characteristics and 2) timing of patient's engagement in buprenorphine treatment (pre- or post-implementation of an integrated treatment model).

RESULTS

Of the study sample, 53% had ≥6 months of buprenorphine orders. Almost two times higher odds of retention were found among patients with ≥1 psychiatric comorbidity (versus none) and among those with buprenorphine orders in the post- versus pre-period.

CONCLUSIONS

An integrated, interdisciplinary model of OUD treatment was associated with ≥6 months of buprenorphine orders among our study population. Continued research is needed in real-world primary care settings to understand the impact of OUD treatment models on patient outcomes. A more nuanced examination of the associations between psychiatric diagnoses and buprenorphine treatment retention is warranted.

Tier-based treatment for opioid use disorder in the primary care setting

Background: Two primary care clinics implemented an opioid use disorder (OUD) treatment program that integrates behavioral health counseling with buprenorphine treatment and uses tiers. This project aimed to understand how patients moved through tiers in this program. Method: We purposively sampled 20 patients with at least 10 OUD-related treatment visits; we documented tier changes at all visits between September 1, 2016 and December 31, 2018 using a standard data collection instrument. These data were used to construct run-charts. Results: About 45% of sampled patients had at least one relapse noted and 60% of patients dropped in tier during the study. Reductions in tier often happened when the patient was navigating difficult psychosocial situations in their life, whereas increases in tier often accompanied positive life events. We also found variation in use of the tiers. Discussion: OUD treatment from two clinics by tier illustrates that recovery is an individualized process based on patient need that can fluctuate due to psychosocial triggers and significant life events. Having tiers can guide treatment and provide both clinicians and patients with information about what to expect during treatment while still allowing the flexibility to meet patients where they are. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

A Medicaid Alternative Payment Model Program In Oregon Led To Reduced Volume Of Imaging Services

The patient-centered medical home model aspires to fundamentally restructure care processes, but a volume-based payment system may hinder such transformations. In 2013 Oregon's Medicaid program changed its reimbursement of traditional primary care services for selected community health centers (CHCs) from a per visit to a per patient rate. Using Oregon claims data, we analyzed the price-weighted volume of care for five service areas: traditional primary care services, including imaging, tests, and procedures; other services provided by CHCs that were carved out from the payment reform; emergency department visits; inpatient services; and other services of non-CHC providers. We further subdivided traditional primary care services using Berenson-Eggers Type of Service categories of care. We compared participating and nonparticipating CHCs in Oregon before and after the payment model was implemented. The payment reform was associated with a 42.4 percent relative reduction in price-weighted traditional primary care services, driven fully by decreased use of imaging services. Other outcomes remained unaffected. Oregon's initiative could provide lessons for other states interested in using payment reform to advance the patient-centered medical home model for the Medicaid population.

The impact of capitated payment on preventive care utilization in community health clinics

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.

New hypertension and diabetes diagnoses following the Affordable Care Act Medicaid expansion

OBJECTIVE

To assess the Affordable Care Act (ACA) Medicaid expansion's impact on new hypertension and diabetes diagnoses in community health centres (CHCs).

DESIGN

Rates of new hypertension and diabetes diagnoses were computed using generalised estimating equation Poisson models and we tested the difference-in-difference (DID) pre-ACA versus post-ACA in states that expanded Medicaid compared with those that did not.

SETTING

We used electronic health record data (pre-ACA: 1 January 2012-31 December 2013-post-ACA: 1 January 2014-31 December 2016) from the Accelerating Data Value Across a National Community Health Center Network clinical data network. We included clinics with ≥50 patients contributing to person-time-at risk in each study year.

PARTICIPANTS

Patients aged 19-64 with ≥1 ambulatory visit in the study period were included. We then excluded patients who were pregnant during the study period (N=127 530). For the hypertension outcome, we excluded individuals with a diagnosis of hypertension prior to the start of the study period, those who had a hypertension diagnosis on their first visit to a clinic or their first visit after 3 years without a visit, and those who had a diagnosis more than 3 years after their last visit (pre-ACA non-expansion N=130 973; expansion N=193 198; post-ACA non-expansion N=186 341; expansion N=251 015). For the diabetes analysis, we excluded patients with a diabetes diagnosis prior to study start, on their first visit or first visit after inactive patient status, and diagnosis while not an active patient (pre-ACA non-expansion N=145 435; expansion N=198 558; post-ACA non-expansion N=215 039; expansion N=264 644).

RESULTS

In non-expansion states, adjusted hypertension diagnosis rates saw a relative decrease of 6%, while in expansion states, the adjusted rates saw a relative increase of 7% (DID 1.14, 95% CI 1.11 to 1.18). For diabetes diagnosis, adjusted rates in non-expansion states experienced a significant relative increase of 28% and in expansion states the relative increase was 25%; yet these differences were not significant pre-ACA to post-ACA comparing expansion and non-expansion states (DID 0.98, 95% CI 0.91 to 1.05).

CONCLUSION

There was a differential impact of Medicaid expansion for hypertension and diabetes diagnoses. Moderate increases were found in diabetes diagnosis rates among all patients served by CHCs post-ACA (both in expansion and non-expansion states). These increases suggest that ACA-related opportunities to gain health insurance (such as marketplaces and the Medicaid expansion) may have facilitated access to diagnostic tests for this population. The study found a small change in hypertension diagnosis rates from pre-ACA to post-ACA (a decrease in non-expansion and an increase in expansion states). Despite the significant difference between expansion and non-expansion states, the small change from pre-ACA to post-ACA suggests that the diagnosis of hypertension is likely documented for patients, regardless of health insurance availability. Future studies are needed to understand the impact of the ACA on hypertension and diabetes treatment and control.

Tobacco Cessation in Affordable Care Act Medicaid Expansion States Versus Non-expansion States

INTRODUCTION

Community health centers (CHCs) care for vulnerable patients who use tobacco at higher than national rates. States that expanded Medicaid eligibility under the Affordable Care Act (ACA) provided insurance coverage to tobacco users not previously Medicaid-eligible, thereby potentially increasing their odds of receiving cessation assistance. We examined if tobacco users in Medicaid expansion states had increased quit rates, cessation medications ordered, and greater health care utilization compared to patients in non-expansion states.

METHODS

Using electronic health record (EHR) data from 219 CHCs in 10 states that expanded Medicaid as of January 1, 2014, we identified patients aged 19-64 with tobacco use status documented in the EHR within 6 months prior to ACA Medicaid expansion and ≥1 visit with tobacco use status assessed within 24 months post-expansion (January 1, 2014 to December 31, 2015). We propensity score matched these patients to tobacco users from 108 CHCs in six non-expansion states (n = 27 670 matched pairs; 55 340 patients). Using a retrospective observational cohort study design, we compared odds of having a quit status, cessation medication ordered, and ≥6 visits within the post-expansion period among patients in expansion versus non-expansion states.

RESULTS

Patients in expansion states had increased adjusted odds of quitting (adjusted odds ratio [aOR] = 1.35, 95% confidence interval [CI]: 1.28-1.43), having a medication ordered (aOR = 1.53, 95% CI: 1.44-1.62), and having ≥6 follow-up visits (aOR = 1.34, 95% CI: 1.28-1.41) compared to patients from non-expansion states.

CONCLUSIONS

Increased access to insurance via the ACA Medicaid expansion likely led to increased quit rates within this vulnerable population.

IMPLICATIONS

CHCs care for vulnerable patients at higher risk of tobacco use than the general population. Medicaid expansion via the ACA provided insurance coverage to a large number of tobacco users not previously Medicaid-eligible. We found that expanded insurance coverage was associated with increased cessation assistance and higher odds of tobacco cessation. Continued provision of insurance coverage could lead to increased quit rates among high-risk populations, resulting in improvements in population health outcomes and reduced total health care costs.

The Affordable Care Act: Effects of Insurance on Diabetes Biomarkers

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 (HbA_1c), systolic (SBP) and diastolic (DBP) blood pressure, and LDL cholesterol levels.

RESULTS

Newly insured patients exhibited a reduction in adjusted mean HbA_1c levels (8.24% [67 mmol/mol] to 8.17% [66 mmol/mol]), which was significantly different from continuously uninsured patients, whose HbA_1c 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 HbA_1c in the 3 months prior to expansion, newly insured patients were more likely than continuously uninsured patients to have a controlled HbA_1c 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.

The Affordable Care Act Medicaid Expansion Positively Impacted Community Health Centers and Their Patients

Community health centers (CHCs) provide primary care for underserved children and adults. The Patient Protection and Affordable Care Act (ACA) aimed to strengthen the CHC network by increasing federal funds and expanding Medicaid eligibility. The ACA also aimed to boost preventive and mental health services and to reduce health and healthcare disparities. Here, we summarize our results to-date as experts in investigating the impact of ACA Medicaid expansion on CHCs and the patients they serve. We found the ACA Medicaid expansion increased access to care and preventive services, primarily in Medicaid expansion states. Rates of physical and mental health conditions rose substantially from pre- to post-ACA in expansion states, suggesting underdiagnosis pre-ACA. Disparities in health insurance coverage by race/ethnicity decreased at CHCs, yet some remain. These findings indicate that the ACA Medicaid expansion significantly helped CHCs and patients. Insurance expansion buoyed CHCs' financial viability by increasing reimbursement. Therefore, the ACA Medicaid expansion enhanced the health of underserved patients and repeal would jeopardize these advances for CHCs and their patients.

Health Care Expenditures Among Adults With Diabetes After Oregon's Medicaid Expansion

OBJECTIVE

To compare trends in Medicaid expenditures among adults with diabetes who were newly eligible due to the Affordable Care Act (ACA) Medicaid expansion to trends among those previously eligible.

RESEARCH DESIGN AND METHODS

Using Oregon Medicaid administrative data from 1 January 2014 to 30 September 2016, a retrospective cohort study was conducted with propensity score-matched Medicaid eligibility groups (newly and previously eligible). Outcome measures included total per-member per-month (PMPM) Medicaid expenditures and PMPM expenditures in the following 12 categories: inpatient visits, emergency department visits, primary care physician visits, specialist visits, prescription drugs, transportation services, tests, imaging and echography, procedures, durable medical equipment, evaluation and management, and other or unknown services.

RESULTS

Total PMPM Medicaid expenditures for newly eligible enrollees with diabetes were initially considerably lower compared with PMPM expenditures for matched previously eligible enrollees during the first postexpansion quarter (mean values $561 vs. $793 PMPM, P = 0.018). Within the first three postexpansion quarters, PMPM expenditures of the newly eligible increased to a similar but slightly lower level. Afterward, PMPM expenditures of both groups continued to increase steadily. Most of the overall PMPM expenditure increase among the newly eligible was due to rapidly increasing prescription drug expenditures.

CONCLUSIONS

Newly eligible Medicaid enrollees with diabetes had slightly lower PMPM expenditures than previously eligible Medicaid enrollees. The increase in PMPM prescription drug expenditures suggests greater access to treatment over time.

Development of an algorithm to link electronic health record prescriptions with pharmacy dispense claims

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.

Racial/Ethnic Disparities in Health Insurance and Differences in Visit Type for a Population of Patients with Diabetes after Medicaid Expansion

This quasi-experimental study evaluated racial/ethnic disparities in health insurance and differences in visits post-versus pre-Affordable Care Act (ACA) Medicaid expansion. We utilized electronic health record data from a population of patients with diabetes aged 19-64 seen in community health centers (CHCs). We used generalized estimating equation Poisson models to estimate incidence rates of insurance type and visits post-(1/1/2014-12/31/2015) versus pre-(1/1/13-12/31/13) ACA, stratified by racial/ethnic group. We assessed difference-in-differences (DD) and difference-in-difference-in-differences (DDD). The relative disparity in uninsured visits increased between Hispanic and non-Hispanic Whites in expansion states (DD=1.93; 95% CI=1.41, 2.64); the magnitude was greater in expansion compared with non-expansion states (DDD=1.84, 95% CI=1.32, 2.56), yet uninsured rates were lower in expansion compared with non-expansion states. We found few changes in visits. Results suggest that the ACA Medicaid expansion increased health insurance coverage and that while some racial/ethnic disparities were improved, some remained.

Prevalence of Pre-existing Conditions Among Community Health Center Patients Before and After the Affordable Care Act

OBJECTIVE

To assess the prevalence of pre-existing conditions for community health center (CHC) patients who gained insurance coverage post-Affordable Care Act (ACA).

METHODS

We analyzed electronic health record data from 78,059 patients aged 19 to 64 uninsured at their last visit pre-ACA from 386 CHCs in 19 states. We compared the prevalence and types of pre-existing conditions pre-ACA (2012 to 2013) and post-ACA (2014 to 2015), by insurance status and race/ethnicity.

RESULTS

Pre-ACA, >50% of patients in the cohort had ≥1 Pre-existing condition. Post-ACA, >70% of those who gained insurance coverage had ≥1 condition. Post-ACA, all racial/ethnic subgroups showed an increase in the number of pre-existing conditions, with non-Hispanic Black and Hispanic patients experiencing the largest increases (adjusted prevalence difference, 18.9; 95% CI, 18.2 to 19.6 and 18.3; 95% CI, 17.8 to 18.7, respectively). The most common conditions post-ACA were mental health disorders with the highest prevalence among patients who gained Medicaid (45.6%) and lowest among those who gained private coverage (30.5%).

CONCLUSIONS

This study emphasizes the high prevalence of pre-existing conditions among CHC patients and the large increase in the proportion of patients with at least 1 of these diagnoses post-ACA. Given how common these conditions are, repealing pre-existing condition protections could be extremely harmful to millions of patients and would likely exacerbate health care and health disparities.

Prescription opioid use patterns, use disorder diagnoses and addiction treatment receipt after the 2014 Medicaid expansion in Oregon

BACKGROUND/AIMS

Evidence suggests that Medicaid beneficiaries in the United States are prescribed opioids more frequently than are people who are privately insured, but little is known about opioid prescribing patterns among Medicaid enrollees who gained coverage via the Affordable Care Act Medicaid expansions. This study compared the prevalence of receipt of opioid prescriptions and opioid use disorder (OUD), along with time from OUD diagnosis to medication-assisted treatment (MAT) receipt between Oregon residents who had been continuously insured by Medicaid, were newly insured after Medicaid expansion in 2014 or returned to Medicaid coverage after expansion.

DESIGN

Cross-sectional study using inverse-propensity weights to adjust for differences among insurance groups.

SETTING

Oregon.

PARTICIPANTS

A total of 225 295 Oregon Medicaid adult beneficiaries insured during 2014-15 and either: (1) newly enrolled, (2) returning in 2014 after a > 12-month gap or (3) continuously insured between 2013 and 2015. We excluded patients in hospice care or with cancer diagnoses.

MEASUREMENTS

Any opioid-dispensed, chronic (> 90-days) and high-dose (> 90 daily morphine milligram equivalence) opioid use, documented OUD diagnosis and MAT receipt.

FINDINGS

Compared with the continuously insured, newly and returning insured enrollees were less likely to be dispensed opioids [newly: 42.3%, 95% confidence interval (CI) = 42.0-42.7%; returning: 49.3%, 95% CI = 48.8-49.7%; continuously: 52.5%, 95% CI = 52.0-53.0%], use opioids chronically (newly: 12.8%, 95% CI = 12.4-13.1%; returning: 11.9%, 95% CI = 11.5-12.3%, continuously: 15.8%, 95% CI = 15.4-16.2%), have OUD diagnoses (newly: 3.6%, 95% CI = 3.4-3.7%; returning: 3.9%, 95% CI = 3.8-4.1%, continuously: 4.7%, 95% CI = 4.5-4.9%) and receive MAT after OUD diagnosis [hazard ratio newly: 0.57, 95% CI = 0.53-0.61; hazard ratio returning: 0.60, 95% CI = 0.56-0.65 (ref: continuously)].

CONCLUSIONS

Residents of Oregon, United States who enrolled or re-enrolled in Medicaid health insurance after expansion of coverage in 2014 as a result of the Affordable Care Act were less likely than those already covered to receive opioids, use them chronically or receive medication-assisted treatment for opioid use disorder.

Following Uninsured Patients Through Medicaid Expansion: Ambulatory Care Use and Diagnosed Conditions

PURPOSE

The Patient Protection and Affordable Care Act (ACA) has improved access to health insurance, yet millions remain uninsured. Many patients who remain uninsured access care at community health centers (CHCs); however, little is known about their health conditions and health care use. We assessed ambulatory care use and diagnosed health conditions among a cohort of CHC patients uninsured before enactment of the ACA (pre-ACA: January 1, 2012 to December 31, 2013) and followed them after enactment (post-ACA: January 1, 2014 to December 31, 2015).

METHODS

This retrospective cohort analysis used electronic health record data from CHCs in 11 US states that expanded Medicaid eligibility. We assessed ambulatory care visits and documented health conditions among a cohort of 138,246 patients (aged 19 to 64 years) who were uninsured pre-ACA and either remained uninsured, gained Medicaid, gained other health insurance, or did not have a visit post-ACA. We estimated adjusted predicted probabilities of ambulatory care use using an ordinal logistic mixed-effects regression model.

RESULTS

Post-ACA, 20.9% of patients remained uninsured, 15.0% gained Medicaid, 12.4% gained other insurance, and 51.7% did not have a visit. The majority of patients had ≥1 diagnosed health condition. The adjusted proportion of patients with high use (≥6 visits over 2 years) increased from pre-ACA to post-ACA among those who gained Medicaid (pre-ACA: 23%, post-ACA: 34%, P <.001) or gained other insurance (pre-ACA: 29%, post-ACA: 48%, P <.001), whereas the percentage fell slightly for those continuously uninsured.

CONCLUSIONS

A significant percentage of CHC patients remained uninsured; many who remained uninsured had diagnosed health conditions, and one-half continued to have ≥3 visits to CHCs. CHCs continue to be essential providers for uninsured patients.

Identifying and characterizing cancer survivors in the US primary care safety net

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.

Using Health Information Technology to Bring Social Determinants of Health into Primary Care: A Conceptual Framework to Guide Research

Several recent national initiatives have called for increased efforts to integrate social determinants of health (SDH) into health care settings using health information technology (HIT). However, there is limited evidence to guide the implementation of these recommendations in practice. Research is needed to understand what SDH information is most important to collect, how SDH information can be used to inform clinical care and referrals, and ultimately, whether and how integrating SDH screening and action into primary care affects individual and population health. We recently proposed a conceptual framework to illustrate how HIT can be used to bring SDH information into primary care. In this paper, we describe how we are putting this conceptual model into practice within the OCHIN network of community health centers by highlighting examples of ongoing research, identifying knowledge gaps, and outlining a roadmap of future research to move the field forward.

Observational study protocol for evaluating control of hypertension and the effects of social determinants

INTRODUCTION

Hypertension is a common chronic health condition. Having health insurance reduces hypertension risk; health insurance coverage could improve hypertension screening, treatment and management. The Medicaid eligibility expansion of the Affordable Care Act was ruled not to be required by the US Supreme Court. Subsequently, a 'natural experiment' was produced with some states expanding Medicaid eligibility while others did not. This presents a unique opportunity to learn whether and to what extent Medicaid expansion can affect healthcare access and services for patients at risk for and diagnosed with hypertension, and patients with undiagnosed hypertension. Additionally, social determinants of health (SDH), at both the individual- and community-level, influence diagnosis and care for hypertension and it is important to understand how they interact with health insurance coverage changes.

METHODS/DESIGN

We will use electronic health record (EHR) data from the Accelerating Data Value Across a National Community Health Center Network clinical data research network, which has data from community health centres in 22 states, some that did and some that did not expand Medicaid. Data include information on changes in health insurance, service receipt and health outcomes from 2012 through the most recent data available. We will include patients between the ages of 19 and 64 years (n=1 524 241) with ≥1 ambulatory visit to a community health centre. We will estimate differences in outcomes using difference-in-difference and difference-in-difference-in-difference approaches. We will test three-way interactions with insurance group, time and social determinants of health factors to compare the potential effect of gaining insurance on our proposed outcomes.

ETHICS AND DISSEMINATION

This study uses secondary data analysis and therefore approval for consent to participate was waived. The Institutional Review Board for OHSU approved this study. Approval reference number is: IRB00011858. We plan to disseminate our findings at relevant conferences, meetings and through peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT03545763.

Progress towards using community context with clinical data in primary care

Community-level factors have significant impacts on health. There is renewed enthusiasm for integrating these data with electronic health record (EHR) data for use in primary care to improve health equity in the USA. Thus, it is valuable to reflect on what has been published to date. Specifically, we comment on: (1) recommendations about combining community-level factors in EHRs for use in primary care; (2) examples of how these data have been combined and used; and (3) the impact of using combined data on healthcare, patient health and health equity. We found publications discussing the potential of combined data to inform clinical care, target interventions, track population health and spark community partnerships with the goal of reducing health disparities and improving health equity. Although there is great enthusiasm and potential for using these data to inform primary care, there is little evidence of improved healthcare, patient health or health equity.

The Impact of the Affordable Care Act (ACA) Medicaid Expansion on Visit Rates for Diabetes in Safety Net Health Centers

OBJECTIVE

To (1) compare clinic-level uninsured, Medicaid-insured, and privately insured visit rates within and between expansion and nonexpansion states before and after the Affordable Care Act (ACA) Medicaid expansion among the 3 cohorts of patient populations; and (2) assess whether there was a change in clinic-level overall, primary care visits, preventive care visits, and diabetes screening rates in expansion versus nonexpansion states from pre-ACA to post-ACA Medicaid expansion.

METHODS

Electronic health record data on nonpregnant patients aged 19 to 64 years, with ≥1 ambulatory visit between 01/01/2012 and 12/31/2015 (n = 483,912 in expansion states; n = 388,466 in nonexpansion states) from 198 primary care community health centers were analyzed. Using a difference-in-difference methodology, we assessed changes in visit rates pre-ACA versus post-ACA among a cohort of patients with diabetes, prediabetes, and no diabetes.

RESULTS

Rates of uninsured visits decreased for all cohorts in expansion and nonexpansion states. For all cohorts, Medicaid-insured visit rates increased significantly more in expansion compared with nonexpansion states, especially among prediabetic patients (+71%). In nonexpansion states, privately insured visit rates more than tripled for the prediabetes cohort and doubled for the diabetes and no diabetes cohorts. Rates for glycosylated hemoglobin screenings increased in all groups, with the largest changes among no diabetes (rate ratio, 2.26; 95% CI, 1.97-2.56) and prediabetes cohorts (rate ratio, 2.00; 95% CI, 1.80-2.19) in expansion states.

CONCLUSION

The ACA reduced uninsurance and increased access to preventive care for vulnerable patients, especially those with prediabetes. These findings are important to consider when making decisions regarding altering the ACA.

Medicaid coverage accuracy in electronic health records

Health insurance coverage facilitates access to preventive screenings and other essential health care services, and is linked to improved health outcomes; therefore, it is critical to understand how well coverage information is documented in the electronic health record (EHR) and which characteristics are associated with accurate documentation. Our objective was to evaluate the validity of EHR data for monitoring longitudinal Medicaid coverage and assess variation by patient demographics, visit types, and clinic characteristics. We conducted a retrospective, observational study comparing Medicaid status agreement between Oregon community health center EHR data linked at the patient-level to Medicaid enrollment data (gold standard). We included adult patients with a Medicaid identification number and ≥1 clinic visit between 1/1/2013-12/31/2014 [>1 million visits (n = 135,514 patients)]. We estimated statistical correspondence between EHR and Medicaid data at each visit (visit-level) and for different insurance cohorts over time (patient-level). Data were collected in 2016 and analyzed 2017-2018. We observed excellent agreement between EHR and Medicaid data for health insurance information: kappa (>0.80), sensitivity (>0.80), and specificity (>0.85). Several characteristics were associated with agreement; at the visit-level, agreement was lower for patients who preferred a non-English language and for visits missing income information. At the patient-level, agreement was lower for black patients and higher for older patients seen in primary care community health centers. Community health center EHR data are a valid source of Medicaid coverage information. Agreement varied with several characteristics, something researchers and clinic staff should consider when using health insurance information from EHR data.