An Effectiveness Study of a Primary Care-embedded Clinical Pharmacist-Led Intervention Among Patients With Diabetes and Medicaid Coverage.

OBJECTIVE: Examine the impact of a primary care-embedded clinical pharmacist-led intervention (UCMyRx) on hemoglobin A1C and blood pressure control, relative to usual care, among patients with Type 2 diabetes (TD2) and Medicaid, in a large healthcare system. METHODS: We used data extracted from the Electronic Health Records system and a Difference-In-Differences study design with a 2:1 propensity-matched comparison group to evaluate the impact of UCMyRx on HbA1c and systolic blood pressure among patients with TD2 and Medicaid, relative to usual care. RESULTS: Having at least one UCMyRx clinical pharmacist visit was associated with a significant reduction in HbA1c; (-.27%, P-value= .03) but no impact on SBP. We do not find differential UCMyRx effects on HbA1c or SBP among the subpopulations with baseline HbA1C ≥9% or SBP ≥150 mmHg, respectively. In Charlson Comorbidity Index (CCI)-stratified analyses we found stronger UCMyRx effects on HbA1C (-.47%, P-value< .02) among the CCI tercile with the lowest comorbidity score (CC1 ≤ 5). Significant UCMyRx effects are only observed among the subpopulation of Medicaid beneficiaries without Medicare (-.35%, P-value= .02). CONCLUSIONS: The UCMyRx intervention is a useful strategy for improving HbA1c control among patients with TD2 and Medicaid.

Accuracy of an Electronic Health Record Patient Linkage Module Evaluated between Neighboring Academic Health Care Centers.

BACKGROUND: Patients often seek medical treatment among different health care organizations, which can lead to redundant tests and treatments. One electronic health record (EHR) platform, Epic Systems, uses a patient linkage tool called Care Everywhere (CE), to match patients across institutions. To the extent that such linkages accurately identify shared patients across organizations, they would hold potential for improving care. OBJECTIVE: This study aimed to understand how accurate the CE tool with default settings is to identify identical patients between two neighboring academic health care systems in Southern California, The University of California Los Angeles (UCLA) and Cedars-Sinai Medical Center. METHODS: We studied CE patient linkage queries received at UCLA from Cedars-Sinai between November 1, 2016, and April 30, 2017. We constructed datasets comprised of linkages ("successful" queries), as well as nonlinkages ("unsuccessful" queries) during this time period. To identify false positive linkages, we screened the "successful" linkages for potential errors and then manually reviewed all that screened positive. To identify false-negative linkages, we applied our own patient matching algorithm to the "unsuccessful" queries and then manually reviewed a sample to identify missed patient linkages. RESULTS: During the 6-month study period, Cedars-Sinai attempted to link 181,567 unique patient identities to records at UCLA. CE made 22,923 "successful" linkages and returned 158,644 "unsuccessful" queries among these patients. Manual review of the screened "successful" linkages between the two institutions determined there were no false positives. Manual review of a sample of the "unsuccessful" queries (n = 623), demonstrated an extrapolated false-negative rate of 2.97% (95% confidence interval [CI]: 1.6-4.4%). CONCLUSION: We found that CE provided very reliable patient matching across institutions. The system missed a few linkages, but the false-negative rate was low and there were no false-positive matches over 6 months of use between two nearby institutions.