Internet search and medicaid prescription drug data as predictors of opioid emergency department visits

The primary contributors to the opioid crisis continue to rapidly evolve both geographically and temporally, hampering the ability to halt the growing epidemic. To address this issue, we evaluated whether integration of near real-time social/behavioral (i.e., Google Trends) and traditional health care (i.e., Medicaid prescription drug utilization) data might predict geographic and longitudinal trends in opioid-related Emergency Department (ED) visits. From January 2005 through December 2015, we collected quarterly State Drug Utilization Data; opioid-related internet search terms/phrases; and opioid-related ED visit data. Modeling was conducted using least absolute shrinkage and selection operator (LASSO) regression prediction. Models combining Google and Medicaid variables were a better fit and more accurate (R2 values from 0.913 to 0.960, across states) than models using either data source alone. The combined model predicted sharp and state-specific changes in ED visits during the post 2013 transition from heroin to fentanyl. Models integrating internet search and drug utilization data might inform policy efforts about regional medical treatment preferences and needs.

State strategies to address medicaid prescription spending: negotiated pricing vs price transparency

This research longitudinally examines the association between levels of state Medicaid prescription spending and the state strategies intended to constrain cost increases: the negotiated pricing strategy, as indicated by state rebate programs, and the price transparency strategy, as indicated by state operation of All-Payer Claims Databases. The findings demonstrate evidence that state Medicaid prescription spending is influenced by the negotiated pricing strategy, especially Managed Care Organization (MCO) rebates under the Patient Protection and Affordable Care Act, but not influenced by the price transparency strategy. State decisions for MCO rebates, such as carving prescription benefits into managed care benefits, were effective in containing levels of Medicaid prescription spending over time, while other single- and multi-state rebate programs were not. Based on these findings, state policymakers may consider utilizing the MCO rebate program to address increases in Medicaid prescription spending.

Under Prescription of Epinephrine to Medicaid Patients in the Pediatric Emergency Department

Objective. To describe pediatric Medicaid patients with pediatric emergency department (PED) visits for anaphylaxis who received epinephrine auto-injector (EAI) prescriptions in the ED versus those who did not; and to compare patients who filled their prescriptions versus those who did not. Methods. We conducted a cross-sectional study of Medicaid patients aged 0 to 21 years presenting to 2 PEDs, with symptoms meeting the National Institute of Allergy and Infectious Diseases criteria for anaphylaxis, between July 2012 and July 2014. Results. We identified 86 patients across the 2 hospitals with a confirmed diagnosis of anaphylaxis in the PED. Of these, 55 (64%, 95% confidence interval [CI] = 53% to 74%) received a prescription for an EAI during their ED visit. Forty-two (68%; 95% CI = 56% to 80%) received a prescription for EAI in Hospital 1 versus 13 (54%; 95% CI = 33% to 74%) in Hospital 2. Medicaid prescription fill rates were available for Hospital 1. Of the 42 who received an EAI prescription, 36 (86%; 95% CI = 75% to 96%) filled these prescriptions with Medicaid. Of the 20 (32%) out of 62 patients with anaphylaxis who did not receive prescriptions for an EAI, only 5 had previously filled prescriptions for epinephrine. Conclusion. Previous Medicaid patient prescription adherence data suggested that these patients would have a low EAI prescription fill rate. We found Medicaid patients who received prescriptions for an EAI after the ED visit for anaphylaxis filled them; however, a considerable proportion of anaphylaxis visits had no EAI prescription provided at discharge.