Identifying High Risk Prescribers Using PDMP Data: A Tool For Law Enforcement

This grant is funded under NIJ's Research on Illegal Prescription Drug Market Interventions solicitation, which supports the examination of the utility of policies, practices, and resources available to law enforcement for major crime deterrence, prosecution, and other market intervention--specifically under the objective Prescription Drug Monitoring Program (PDMP) Optimization for Law Enforcement. Based on a needs assessment and preliminary analysis of North Carolina's (NC's) PMDP data (2009-2011), the goal of this project is to develop an algorithm to predict high risk prescribers in partnership with the NC State Bureau of Investigation (SBI) and a Multidisciplinary Advisory Committee (including physicians). The needs assessment involved consultation with the 14 SBI diversion unit agents who submit reports to the States District Attorney, who notifies the NC Medical Board of investigations for possible regulatory action. Project methods include: identifying high risk prescribers in past PDMP data and examining SBI investigations following; refining the algorithm in consultation with SBI; generating a list for SBI using 2012 PMDP data; observing subsequent SBI investigations; and evaluating success of the algorithm and SBI screening process. Algorithm variables will include long-distance patients, multiple patients prescribed high dosages, high patient volume, and patients receiving from multiple prescribers; a payment field will be added by the NC PDMP in 1/2013. In addition to the data and written deliverables required by NIJ, anticipated work products include professional conference presentations, manuscripts for submission to professional journals, documentation on algorithm development; and a briefing to NIJ. This project has the potential to promote efficient investigation and prosecution of prescription drug diversion through a tool that identifies aberrant prescribers using PDMP data with fewer false positives.ca/ncf