Validation Study of a Predictive Algorithm to Evaluate Opioid Use Disorder in a Primary Care Setting

Overview

Journal Health Serv Res Manag Epidemiol

Publisher Sage Publications

Specialty Public Health

Date 2017 Sep 12

PMID 28890908

Citations 3

Authors

Maneesh Sharma

Chee Lee

Svetlana Kantorovich

Maria Tedtaotao

Gregory A Smith

Ashley Brenton

Affiliations

Soon will be listed here.

Abstract

Background: Opioid abuse in chronic pain patients is a major public health issue. Primary care providers are frequently the first to prescribe opioids to patients suffering from pain, yet do not always have the time or resources to adequately evaluate the risk of opioid use disorder (OUD).

Purpose: This study seeks to determine the predictability of aberrant behavior to opioids using a comprehensive scoring algorithm ("profile") incorporating phenotypic and, more uniquely, genotypic risk factors.

Methods And Results: In a validation study with 452 participants diagnosed with OUD and 1237 controls, the algorithm successfully categorized patients at high and moderate risk of OUD with 91.8% sensitivity. Regardless of changes in the prevalence of OUD, sensitivity of the algorithm remained >90%.

Conclusion: The algorithm correctly stratifies primary care patients into low-, moderate-, and high-risk categories to appropriately identify patients in need for additional guidance, monitoring, or treatment changes.

Citing Articles

Scoping review of enablers and challenges of implementing pharmacogenomics testing in the primary care settings.

Mai C, Sridhar S, Salim Karattuthodi M, Ganesan P, Shareef J, Lee E BMJ Open. 2024; 14(11):e087064.

PMID: 39500605 PMC: 11552560. DOI: 10.1136/bmjopen-2024-087064.

Individualized Prospective Prediction of Opioid Use Disorder.

Liu Y, Kiyang L, Hayward J, Zhang Y, Metes D, Wang M Can J Psychiatry. 2022; 68(1):54-63.

PMID: 35892186 PMC: 9720482. DOI: 10.1177/07067437221114094.

A Predictive Algorithm to Detect Opioid Use Disorder: What Is the Utility in a Primary Care Setting?.

Lee C, Sharma M, Kantorovich S, Brenton A Health Serv Res Manag Epidemiol. 2018; 5:2333392817747467.

PMID: 29383324 PMC: 5784544. DOI: 10.1177/2333392817747467.

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