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

Authors
  • Cochran, Gerald1
  • Brown, Jennifer2
  • Yu, Ziji3
  • Frede, Stacey4
  • Bryan, M Aryana5
  • Ferguson, Andrew6
  • Bayyari, Nadia7
  • Taylor, Brooke8
  • Snyder, Margie E9
  • Charron, Elizabeth10
  • Adeoye-Olatunde, Omolola A11
  • Ghitza, Udi E12
  • Winhusen, T13
  • 1 University of Utah, Department of Internal Medicine, 295 Chipeta Way Salt Lake City, UT 84132, USA. Electronic address: [email protected]
  • 2 University of Cincinnati, Department of Psychiatry and Behavioral Neuroscience, 260 Stetson Street Cincinnati, OH 45267-0559, USA; Center for Addiction Research, University of Cincinnati College of Medicine, 3230 Eden Avenue, Cincinnati, OH 45267, USA. Electronic address: [email protected]
  • 3 University of Utah, Department of Internal Medicine, 295 Chipeta Way Salt Lake City, UT 84132, USA. Electronic address: [email protected]
  • 4 Kroger Pharmacy, 1014 Vine Street, Cincinnati, OH 45202, USA. Electronic address: [email protected]
  • 5 University of Utah, Department of Internal Medicine, 295 Chipeta Way Salt Lake City, UT 84132, USA. Electronic address: [email protected]
  • 6 University of Cincinnati, Department of Psychiatry and Behavioral Neuroscience, 260 Stetson Street Cincinnati, OH 45267-0559, USA. Electronic address: [email protected]
  • 7 University of Cincinnati, Department of Psychiatry and Behavioral Neuroscience, 260 Stetson Street Cincinnati, OH 45267-0559, USA. Electronic address: [email protected]
  • 8 Kroger Pharmacy, 1014 Vine Street, Cincinnati, OH 45202, USA. Electronic address: [email protected]
  • 9 Purdue University, College of Pharmacy, 575 Stadium Mall Drive West Lafayette, IN 47907, USA. Electronic address: [email protected]
  • 10 University of Utah, Department of Internal Medicine, 295 Chipeta Way Salt Lake City, UT 84132, USA. Electronic address: [email protected]
  • 11 Purdue University, College of Pharmacy, 575 Stadium Mall Drive West Lafayette, IN 47907, USA. Electronic address: [email protected]
  • 12 National Institute on Drug Abuse, Center for Clinical Trials Network, 3 White Flint North MSC 6022, 301 North Stonestreet Avenue, North Bethesda, MD 20852, USA. Electronic address: [email protected]
  • 13 University of Cincinnati, Department of Psychiatry and Behavioral Neuroscience, 260 Stetson Street Cincinnati, OH 45267-0559, USA; Center for Addiction Research, University of Cincinnati College of Medicine, 3230 Eden Avenue, Cincinnati, OH 45267, USA. Electronic address: [email protected]
Type
Published Article
Journal
Drug and alcohol dependence
Publication Date
Sep 24, 2021
Volume
228
Pages
109067–109067
Identifiers
DOI: 10.1016/j.drugalcdep.2021.109067
PMID: 34610516
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

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. 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. 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). 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. Copyright © 2021 Elsevier B.V. All rights reserved.

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