Validation of prescriber risk indicators obtained from prescription drug monitoring program data.

Abstract

BACKGROUND Prescription opioids are commonly overprescribed. However, validated measures of inappropriate controlled substance prescribing are lacking. This study examined associations between prescriber risk indicators developed as part of a public health surveillance project and medical board disciplinary actions against prescribers. METHODS We compiled 12 prescriber risk indicators using data from the Maine prescription drug monitoring program (PDMP) for 2010. We used logistic regression models to assess the relative likelihood of the top 1%, 2%, 5%, and 10% of prescribers on each risk indicator having been subject to medical board disciplinary actions, those citing inappropriate prescribing, or those involving license suspension or revocation, during 2010-2014, controlling for prescriber medical specialty and gender. RESULTS The top 1% of prescribers for number of patients, opioid prescriptions per day, and opioid dosage prescribed per day had a greater likelihood of medical board disciplinary actions citing inappropriate prescribing, relative to a matched sample of other (non-top 1%) prescribers. Of the 56 prescribers in the top 1% for opioid prescriptions per day, nine (16.1%) were sanctioned for inappropriate prescribing, compared with 11 of 224 (0.5%) in the comparison group. The top 2% of prescribers for opioid dosage per day, and average distance patients travel to prescriber, had a greater likelihood of actions involving license suspension, revocation, or denial for renewal. CONCLUSIONS Measures derived from PDMP data may be useful in assessing levels of inappropriate prescribing of controlled substances in a population of prescribers, and in evaluating changes associated with efforts to influence prescriber behavior.

DOI: 10.1016/j.drugalcdep.2016.11.020

Cite this paper

@article{Kreiner2017ValidationOP, title={Validation of prescriber risk indicators obtained from prescription drug monitoring program data.}, author={Peter Kreiner and Gail K. Strickler and Eduardo A Undurraga and Mar{\'i}a Elisa Torres and Ruslan V Nikitin and Anne F. Rogers}, journal={Drug and alcohol dependence}, year={2017}, volume={173 Suppl 1}, pages={S31-S38} }