Brigit Hatch

Using Electronic Health Records to Conduct Children’s Health Insurance Surveillance

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.

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.

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.

Community Health Center Utilization Following the 2008 Medicaid Expansion in Oregon: Implications for the Affordable Care Act

OBJECTIVES To assess longitudinal patterns of community health center (CHC) utilization and the effect of insurance discontinuity after Oregons 2008 Medicaid expansion (the Oregon Experiment). METHODS We conducted a retrospective cohort study with electronic health records and Medicaid data. We divided individuals who gained Medicaid in the Oregon Experiment into those who maintained (n = 788) or lost (n = 944) insurance coverage. We compared these groups with continuously insured (n = 921) and continuously uninsured (n = 5416) reference groups for community health center utilization rates over a 36-month period. RESULTS Both newly insured groups increased utilization in the first 6 months. After 6 months, use among those who maintained coverage stabilized at a level consistent with the continuously insured, whereas it returned to baseline for those who lost coverage. CONCLUSIONS Individuals who maintained coverage through Oregons Medicaid expansion increased long-term utilization of CHCs, whereas those with unstable coverage did not. POLICY IMPLICATIONS This study predicts long-term increase in CHC utilization following Affordable Care Act Medicaid expansion and emphasizes the need for policies that support insurance retention.

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.

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.

Role of race/ethnicity, language, and insurance in use of cervical cancer prevention services among low-income Hispanic Women, 2009-2013

Introduction Hispanic women in the United States have an elevated risk of cervical cancer, but the existing literature does not reveal why this disparity persists. Methods We performed a retrospective cohort analysis of 17,828 low-income women aged 21 to 64 years seeking care at Oregon community health centers served by a hosted, linked electronic health record during 2009 through 2013. We assessed the odds of having had Papanicolaou (Pap) tests and receiving human papillomavirus (HPV) vaccine, by race/ethnicity, insurance status, and language. Results Hispanic women, regardless of pregnancy status or insurance, had greater odds of having had Pap tests than non-Hispanic white women during the study period. English-preferring Hispanic women had higher odds of having had Pap tests than Spanish-preferring Hispanic women (OR, 2.08; 95% confidence interval [CI], 1.63–2.66) but lower odds of having received HPV vaccination (OR, 0.21; 95% CI, 0.12–0.38). Uninsured patients, regardless of race/ethnicity, had lower odds of HPV vaccine initiation than insured patients did. Once a single dose was received, there were no significant racial/ethnic differences in vaccine series completion. Conclusion In this sample of low-income women seeking care at Oregon community health centers, we found minimal racial/ethnic disparities in the receipt of cervical cancer prevention services. Inequities by insurance status, especially in the receipt of HPV vaccine, persist. Community health center–based care may be a useful model to address racial/ethnic disparities in prevention, but this model would need further population-wide study.

Implementation of Health Insurance Support Tools in Community Health Centers

Background: Health information technology (HIT) provides new opportunities for primary care clinics to support patients with health insurance enrollment and maintenance. We present strategies, early findings, and clinic reflections on the development and implementation of HIT tools designed to streamline and improve health insurance tracking at community health centers. Methods: We are conducting a hybrid implementation-effectiveness trial to assess novel health insurance enrollment and support tools in primary care clinics. Twenty-three clinics in 7 health centers from the OCHIN practice-based research network are participating in the implementation component of the trial. Participating health centers were randomized to 1 of 2 levels of implementation support, including arm 1 (n = 4 health centers, 11 clinic sites) that received HIT tools and educational materials and arm 2 (n = 3 health centers, 12 clinic sites) that received HIT tools, educational materials, and individualized implementation support with a practice coach. We used mixed-methods (qualitative and quantitative) to assess tool use rates and facilitators and barriers to implementation in the first 6 months. Results: Clinics reported favorable attitudes toward the HIT tools, which replace less efficient and more cumbersome processes, and reflect on the importance of clinic engagement in tool development and refinement. Five of 7 health centers are now regularly using the tools and are actively working to increase tool use. Six months after formal implementation, arm 2 clinics demonstrated higher rates of tool use, compared with arm 1. Discussion: These results highlight the value of early clinic input in tool development, the potential benefit of practice coaching during HIT tool development and implementation, and a novel method for coupling a hybrid implementation-effectiveness design with principles of improvement science in primary care research.