Abstract
BackgroundCommunity pharmacists are well-positioned to identify patients engaged in non-medical prescription opioid use (NMPOU) through Prescription Drug Monitoring Program (PDMP) databases. Integrating patient-reported outcomes with PDMP data may improve the interpretability of PDMP information to support clinical decision-making. ObjectiveThis study linked patient-reported clinical measures of substance use with PDMP data to examine relationships between average daily opioid dose in morphine milligram equivalents (MME) and visits to multiple pharmacies/prescribers with self-reported NMPOU. MethodsData from a cross-sectional health assessment given to patients aged ≥18 years filling opioid prescriptions were linked to PDMP records. NMPOU in the past three months was assessed on a continuous scale (range 0–39) using an adapted version of the Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST). PDMP measures included average daily MME and number of distinct pharmacies/prescribers visited in the past 180 days. Univariable and multivariable zero-inflated negative binomial models estimated associations between PDMP measures and any NMPOU and severity of use. ResultsThe sample included 1421 participants. In multivariable models adjusted for sociodemographic, mental health, and physical health characteristics, any NMPOU was associated with higher average daily MME (adjusted OR = 1.22, 95% CI = 1.05–1.39) and number of distinct prescribers visited (adjusted OR = 1.15, 95% CI = 1.01–1.30). Higher average daily MME (adjusted mean ratio (MR) = 1.12, 95% CI = 1.08–1.15), number of distinct pharmacies visited (adjusted MR = 1.11, 95% CI = 1.04–1.18), and number of distinct prescribers visited (adjusted MR = 1.07, 95% CI = 1.02–1.11) were associated with increased NMPOU severity. ConclusionsWe observed significant, positive associations between average daily MME and visits to multiple pharmacies/prescribers with any NMPOU and severity of use. This study demonstrates self-report clinical measures of substance use can be cross-walked to PDMP data and translated into clinically interpretable information.
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More From: Research in social & administrative pharmacy : RSAP
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