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Activity Number: 367 - SPEED: Statistical Epidemiology
Type: Contributed
Date/Time: Tuesday, July 31, 2018 : 11:35 AM to 12:20 PM
Sponsor: Section on Statistics in Epidemiology
Abstract #332938
Title: A Probabilistic Linkage Approach for Combining VA and State Prescription Drug Databases for Evaluating Veterans' Receipt of Long-Term Opioid Therapy Across Multiple Systems
Author(s): Larry Cook* and Tess A Gilbert and Kathleen F Carlson
Companies: University of Utah and HSR&D Center to Improve Veteran Involvement in Care and HSR&D Center to Improve Veteran Involvement in Care
Keywords: Probabilistic linkage; Longitudinal analysis; Opioid epidemic; Administrative data; Creating prescription histories; Veterans Healthcare
Abstract:

Prescription drug overdose is an epidemic in the US. Opioids are associated with half of prescription drug overdoses, with 15,281 deaths in 2015 and an average of 54,729 hospitalizations per year from 2009 - 2012. Veterans who use Veterans Health Administration (VA) healthcare have a higher rate of fatal prescription drug overdose than the US population. US states have established prescription drug monitoring programs (PDMPs) to track dispensation of controlled medications across providers and healthcare systems, including the VA. CDC and VA prescribing guidelines recommend PDMP queries be conducted regularly and for new opioid prescriptions; however, adherence is not universal. Veterans filling opioid prescriptions from both VA and non-VA providers may be receiving risky doses of opioids while appearing safe within each individual VA and non-VA systems. Using probabilistic linkage, we demonstrate how VA and state PDMP data can be combined into a single data set to examine overlapping opioid receipt. Focusing on veterans receiving long term opioid therapy (LTOT), differences between LTOT populations as defined within a single system compared to the combined database are examined.


Authors who are presenting talks have a * after their name.

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