Megan J. Hoopes

An Early Look at Rates of Uninsured Safety Net Clinic Visits After the Affordable Care Act

PURPOSE The Affordable Care Act of 2010 supports marked expansions in Medicaid coverage in the United States. As of January 1, 2014, a total of 25 states and the District of Columbia expanded their Medicaid programs. We tested the hypothesis that rates of uninsured safety net clinic visits would significantly decrease in states that implemented Medicaid expansion, compared with states that did not. METHODS We undertook a longitudinal observational study of coverage status for adult visits in community health centers, from 12 months before Medicaid expansion (January 1, 2013 to December 31, 2013) through 6 months after expansion (January 1, 2014 to June 30, 2014). We analyzed data from 156 clinics in the OCHIN practice-based research network, with a shared electronic health record, located in 9 states (5 expanded Medicaid coverage and 4 did not). RESULTS Analyses were based on 333,655 nonpregnant adult patients and their 1,276,298 in-person billed encounters. Overall, clinics in the expansion states had a 40% decrease in the rate of uninsured visits in the postexpansion period and a 36% increase in the rate of Medicaid-covered visits. In contrast, clinics in the nonexpansion states had a significant 16% decline in the rate of uninsured visits but no change in the rate of Medicaid-covered visits. CONCLUSIONS There was a substantial decrease in uninsured community health center visits and a significant increase in Medicaid-covered visits in study clinics in states that expanded Medicaid in 2014, whereas study clinics in states opting out of the expansion continued to have a high rate of uninsured visits. These findings suggest that Affordable Care Act–related Medicaid expansions have successfully decreased the number of uninsured safety net patients in the United States.

Agreement of Medicaid claims and electronic health records for assessing preventive care quality among adults.

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.

Community Health Center Use After Oregon’s Randomized Medicaid Experiment

PURPOSE There is debate about whether community health centers (CHCs) will experience increased demand from patients gaining coverage through Affordable Care Act Medicaid expansions. To better understand the effect of new Medicaid coverage on CHC use over time, we studied Oregon’s 2008 randomized Medicaid expansion (the “Oregon Experiment”). METHODS We probabilistically matched demographic data from adults (aged 19–64 years) participating in the Oregon Experiment to electronic health record data from 108 Oregon CHCs within the OCHIN community health information network (originally the Oregon Community Health Information Network) (N = 34,849). We performed intent-to-treat analyses using zero-inflated Poisson regression models to compare 36-month (2008–2011) usage rates among those selected to apply for Medicaid vs not selected, and instrumental variable analyses to estimate the effect of gaining Medicaid coverage on use. Use outcomes included primary care visits, behavioral/mental health visits, laboratory tests, referrals, immunizations, and imaging. RESULTS The intent-to-treat analyses revealed statistically significant differences in rates of behavioral/mental health visits, referrals, and imaging between patients randomly selected to apply for Medicaid vs those not selected. In instrumental variable analyses, gaining Medicaid coverage significantly increased the rate of primary care visits, laboratory tests, referrals, and imaging; rate ratios ranged from 1.27 (95% CI, 1.05–1.55) for laboratory tests to 1.58 (95% CI, 1.10–2.28) for referrals. CONCLUSIONS Our results suggest that use of many different types of CHC services will increase as patients gain Medicaid through Affordable Care Act expansions. To maximize access to critical health services, it will be important to ensure that the health care system can support increasing demands by providing more resources to CHCs and other primary care settings.

Estimating demand for care after a medicaid expansion: lessons from Oregon

To estimate how the Affordable Care Acts Medicaid expansions will affect demand for services, we measured ambulatory care utilization among adult patients who gained insurance during Oregons 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.

Using electronic health record data to evaluate preventive service utilization among uninsured safety net patients

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.

Utilization of Community Health Centers in Medicaid Expansion and Nonexpansion States, 2013–2014

Using electronic health record data, we examined longitudinal changes in community health center (CHC) visit rates from 2013 through 2014 in Medicaid expansion versus nonexpansion states. Visits from 219 CHCs in 5 expansion states and 4 nonexpansion states were included. Rates were computed using generalized estimating equation Poisson models. Rates increased in expansion state CHCs for new patient, preventive, and limited-service visits (14%, 41%, and 23%, respectively, P < .01 for all), whereas these rates remained unchanged in nonexpansion states. One year after ACA Medicaid expansions, CHCs in expansion states saw an influx of new patients and provided increased preventive services.

Health Care Utilization Rates After Oregon's 2008 Medicaid Expansion: Within-Group and Between-Group Differences Over Time Among New, Returning, and Continuously Insured Enrollees.

Background:Although past research demonstrated that Medicaid expansions were associated with increased emergency department (ED) and primary care (PC) utilization, little is known about how long this increased utilization persists or whether postcoverage utilization is affected by prior insurance status. Objectives:(1) To assess changes in ED, PC, mental and behavioral health care, and specialist care visit rates among individuals gaining Medicaid over 24 months postinsurance gain; and (2) to evaluate the association of previous insurance with utilization. Methods:Using claims data, we conducted a retrospective cohort analysis of adults insured for 24 months following Oregon’s 2008 Medicaid expansion. Utilization rates among 1124 new and 1587 returning enrollees were compared with those among 5126 enrollees with continuous Medicaid coverage (≥1 y preexpansion). Visit rates were adjusted for propensity score classes and geographic region. Results:PC visit rates in both newly and returning insured individuals significantly exceeded those in the continuously insured in months 4 through 12, but were not significantly elevated in the second year. In contrast, ED utilization rates were significantly higher in returning insured compared with newly or continuously insured individuals and remained elevated over time. New visits to PC and specialist care were higher among those who gained Medicaid compared with the continuously insured throughout the study period. Conclusions:Predicting the effect of insurance expansion on health care utilization should account for the prior coverage history of new enrollees. In addition, utilization of outpatient services changes with time after insurance, so expansion evaluations should allow for rate stabilization.

Supporting health insurance expansion: do electronic health records have valid insurance verification and enrollment data?

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.

Using the electronic health record for assessment of health insurance in community health centers

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.

Measuring Preventive Care Delivery: Comparing Rates Across Three Data Sources

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