Improve Synergy Between Health Information Exchange and Electronic Health Records to Increase Rates of Continuously Insured Patients

Falling short: how state laws can address health information exchange barriers and enablers

Objective

Research on the implementation of health information exchange (HIE) organizations has identified both positive and negative effects of laws relating to governance, incentives, mandates, sustainability, stakeholder participation, patient engagement, privacy, confidentiality, and security. We fill a substantial research gap by describing whether comprehensive state and territorial HIE legal frameworks address identified legal facilitators and barriers.

Materials and Methods

We used the Westlaw database to identify state and territorial laws relating to HIEs in effect on June 7, 2016 (53 jurisdictions). We blind-coded all laws and addressed coding discrepancies in peer-review meetings. We recorded a consensus code for each law in a master database. We compared 20 HIE legal attributes with identified barriers to and enablers of HIE activity in the literature.

Results

Forty-two states, the District of Columbia, and 2 territories have laws relating to HIEs. On average, jurisdictions address 8.32 of the 20 criteria selected in statutes and regulations. Twenty jurisdictions unambiguously address ≤5 criteria in statutes and regulations. None of the significant legal criteria are unambiguously addressed in >60% of the 53 jurisdictions.

Discussion

Laws can be barriers to or enablers of HIEs. However, jurisdictions are not addressing many significant issues identified by researchers. Consequently, there is a substantial risk that existing legal frameworks are not adequately supporting HIEs.

Conclusion

The current evidence base is insufficient for comparative assessments or impact rankings of the various factors. However, the detailed Centers for Disease Control and Prevention dataset of HIE laws could enable investigations into the types of laws that promote or impede HIEs.

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.

A new role for primary care teams in the United States after "Obamacare:" Track and improve health insurance coverage rates

Maintaining continuous health insurance coverage is important. With recent expansions in access to coverage in the United States after "Obamacare," primary care teams have a new role in helping to track and improve coverage rates and to provide outreach to patients. We describe efforts to longitudinally track health insurance rates using data from the electronic health record (EHR) of a primary care network and to use these data to support practice-based insurance outreach and assistance. Although we highlight a few examples from one network, we believe there is great potential for doing this type of work in a broad range of family medicine and community health clinics that provide continuity of care. By partnering with researchers through practice-based research networks and other similar collaboratives, primary care practices can greatly expand the use of EHR data and EHR-based tools targeting improvements in health insurance and quality health care.