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

MedStar author(s):
Citation: Health Services Research & Managerial Epidemiology. 4:2333392817717411, 2017 Jan-DecPMID: 28890908Institution: MedStar Good Samaritan HospitalForm of publication: Journal ArticleMedline article type(s): Journal ArticleYear: 2017ISSN:
  • 2333-3928
Name of journal: Health services research and managerial epidemiologyAbstract: 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).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.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%.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.All authors: Brenton A, Kantorovich S, Lee C, Sharma M, Smith GA, Tedtaotao MFiscal year: FY2017Digital Object Identifier: Date added to catalog: 2017-09-18
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Journal Article MedStar Authors Catalog Article 28890908 Available 28890908

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).

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.

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%.

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.

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