Validation and threshold identification of a prescription drug monitoring program clinical opioid risk metric with the WHO alcohol, smoking, and substance involvement screening test. (1st November 2021)

• Record Type: Journal Article
• Authors: Cochran, Gerald; Brown, Jennifer; Yu, Ziji; Frede, Stacey; Bryan, M. Aryana; Ferguson, Andrew; Bayyari, Nadia; Taylor, Brooke; Snyder, Margie E.; Charron, Elizabeth; Adeoye-Olatunde, Omolola A.; Ghitza, Udi E.; Winhusen, T.
• Is Part Of: Drug and alcohol dependence. Volume 228(2021)
• Publication Date: 2021-11-01
• Subjects: Community pharmacy -- Prescription drug monitoring program -- And risky opioid use; Drug abuse -- Periodicals; Alcoholism -- Periodicals; 616.86
• DOI: 10.1016/j.drugalcdep.2021.109067
• Languages: English
• ISSNs: 0376-8716

Abstract

Abstract: Background: Prescription drug monitoring programs (PDMPs) are critical for pharmacists to identify risky opioid medication use. We performed an independent evaluation of the PDMP-based Narcotic Score (NS) metric . Methods: This study was a one-time, cross-sectional health assessment within 19 pharmacies from a national chain among adults picking-up opioid medications. The NS metric is a 3-digit composite indicator. The WHO Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) was the gold-standard to which the NS metric was compared. Machine learning determined optimal risk thresholds; Receiver Operating Characteristic curves and Spearman (P) and Kappa (K) coefficients analyzed concurrent validity. Regression analyses evaluated participant characteristics associated with misclassification. Results: The NS metric showed fair concurrent validity (area under the curve≥0.70; K=0.35; P = 0.37, p < 0.001). The ASSIST and NS metric categorized 37% of participants as low-risk (i.e., not needing screening/intervention) and 32.3% as moderate/high-risk (i.e., needing screening/intervention). Further, 17.2% were categorized as low ASSIST risk but moderate/high NS metric risk, termed false positives. These reported disability (OR=3.12), poor general health (OR=0.66), and/or greater pain severity/interference (OR=1.12/1.09; all p < 0.05; i.e., needing unmanaged-pain screening/intervention). A total of 13.4% were categorized as moderate/high ASSIST risk but low NS metric risk, termed false negatives. These reported greater overdose history (OR=1.24) and/or substance use (OR=1.81–12.66; all p < 0.05). Conclusions: The NS metric could serve as a useful initial universal prescription opioid-risk screener given its: 1) low-burden (i.e., no direct assessment); 2) high accuracy (86.5%) of actionable data identifying low-risk patients and those needing opioid use/unmanaged pain screening/intervention; and 3) broad availability. Highlights: Community pharmacies are underutilized settings to address the opioid epidemic. Clinically useful risk thresholds and the concurrent validity of Narcotic Score metric have not been established. Rhe Narcotic Score metric is a screening tool with fair discriminative accuracy and fair to moderate concurrent validity. The Narcotic Score metric could serve as a clinically useful universal prescription opioid-risk screener.