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Hasin DS, Shmulewitz D, Stohl M, Greenstein E, Aharonovich E, Petronis KR, Von Korff M, Datta S, Sonty N, Ross S, Inturrisi C, Weinberger ML, Scodes J, Wall MM. Diagnosing Prescription Opioid Use Disorder in Patients Using Prescribed Opioids for Chronic Pain. Am J Psychiatry 2022; 179:715-725. [PMID: 35702830 DOI: 10.1176/appi.ajp.21070721] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Abstract
OBJECTIVE The diagnostic criteria for opioid use disorder, originally developed for heroin, did not anticipate the surge in prescription opioid use and the resulting complexities in diagnosing prescription opioid use disorder (POUD), including differentiation of pain relief (therapeutic intent) from more common drug use motives, such as to get high or to cope with negative affect. The authors examined the validity of the Psychiatric Research Interview for Substance and Mental Disorders, DSM-5 opioid version, an instrument designed to make this differentiation. METHODS Patients (N=606) from pain clinics and inpatient substance treatment who ever received a ≥30-day opioid prescription for chronic pain were evaluated for DSM-5 POUD (i.e., withdrawal and tolerance were not considered positive if patients used opioids only as prescribed, per DSM-5 guidelines) and pain-adjusted POUD (behavioral/subjective criteria were not considered positive if pain relief [therapeutic intent] was the sole motive). Bivariate correlated-outcome regression models indicated associations of 10 validators with DSM-5 and pain-adjusted POUD measures, using mean ratios for dimensional measures and odds ratios for binary measures. RESULTS The prevalences of DSM-5 and pain-adjusted POUD, respectively, were 44.4% and 30.4% at the ≥2-criteria threshold and 29.5% and 25.3% at the ≥4-criteria threshold. Pain adjustment had little effect on prevalence among substance treatment patients but resulted in substantially lower prevalence among pain treatment patients. All validators had significantly stronger associations with pain-adjusted than with DSM-5 dimensional POUD measures (ratios of mean ratios, 1.22-2.31). For most validators, pain-adjusted binary POUD had larger odds ratios than DSM-5 measures. CONCLUSIONS Adapting POUD measures for pain relief (therapeutic intent) improved validity. Studies should investigate the clinical utility of differentiating between therapeutic and nontherapeutic intent in evaluating POUD diagnostic criteria.
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Affiliation(s)
- Deborah S Hasin
- Department of Psychiatry, Columbia University Medical Center (Hasin, Shmulewitz, Aharonovich, Scodes, Wall) and New York State Psychiatric Institute (Hasin, Shmulewitz, Stohl, Greenstein, Aharonovich, Scodes, Wall), New York; Epidemiology, Pfizer, Inc., New York (Petronis); Kaiser Permanente Washington Health Research Institute, Seattle (Von Korff); Department of Anesthesiology, Rutgers University, Newark, N.J. (Datta); Department of Anesthesiology, Columbia University Medical Center, New York (Sonty, Weinberger); Department of Psychiatry, New York University, New York (Ross); Cornell University Medical College, New York (Inturrisi)
| | - Dvora Shmulewitz
- Department of Psychiatry, Columbia University Medical Center (Hasin, Shmulewitz, Aharonovich, Scodes, Wall) and New York State Psychiatric Institute (Hasin, Shmulewitz, Stohl, Greenstein, Aharonovich, Scodes, Wall), New York; Epidemiology, Pfizer, Inc., New York (Petronis); Kaiser Permanente Washington Health Research Institute, Seattle (Von Korff); Department of Anesthesiology, Rutgers University, Newark, N.J. (Datta); Department of Anesthesiology, Columbia University Medical Center, New York (Sonty, Weinberger); Department of Psychiatry, New York University, New York (Ross); Cornell University Medical College, New York (Inturrisi)
| | - Malka Stohl
- Department of Psychiatry, Columbia University Medical Center (Hasin, Shmulewitz, Aharonovich, Scodes, Wall) and New York State Psychiatric Institute (Hasin, Shmulewitz, Stohl, Greenstein, Aharonovich, Scodes, Wall), New York; Epidemiology, Pfizer, Inc., New York (Petronis); Kaiser Permanente Washington Health Research Institute, Seattle (Von Korff); Department of Anesthesiology, Rutgers University, Newark, N.J. (Datta); Department of Anesthesiology, Columbia University Medical Center, New York (Sonty, Weinberger); Department of Psychiatry, New York University, New York (Ross); Cornell University Medical College, New York (Inturrisi)
| | - Eliana Greenstein
- Department of Psychiatry, Columbia University Medical Center (Hasin, Shmulewitz, Aharonovich, Scodes, Wall) and New York State Psychiatric Institute (Hasin, Shmulewitz, Stohl, Greenstein, Aharonovich, Scodes, Wall), New York; Epidemiology, Pfizer, Inc., New York (Petronis); Kaiser Permanente Washington Health Research Institute, Seattle (Von Korff); Department of Anesthesiology, Rutgers University, Newark, N.J. (Datta); Department of Anesthesiology, Columbia University Medical Center, New York (Sonty, Weinberger); Department of Psychiatry, New York University, New York (Ross); Cornell University Medical College, New York (Inturrisi)
| | - Efrat Aharonovich
- Department of Psychiatry, Columbia University Medical Center (Hasin, Shmulewitz, Aharonovich, Scodes, Wall) and New York State Psychiatric Institute (Hasin, Shmulewitz, Stohl, Greenstein, Aharonovich, Scodes, Wall), New York; Epidemiology, Pfizer, Inc., New York (Petronis); Kaiser Permanente Washington Health Research Institute, Seattle (Von Korff); Department of Anesthesiology, Rutgers University, Newark, N.J. (Datta); Department of Anesthesiology, Columbia University Medical Center, New York (Sonty, Weinberger); Department of Psychiatry, New York University, New York (Ross); Cornell University Medical College, New York (Inturrisi)
| | - Kenneth R Petronis
- Department of Psychiatry, Columbia University Medical Center (Hasin, Shmulewitz, Aharonovich, Scodes, Wall) and New York State Psychiatric Institute (Hasin, Shmulewitz, Stohl, Greenstein, Aharonovich, Scodes, Wall), New York; Epidemiology, Pfizer, Inc., New York (Petronis); Kaiser Permanente Washington Health Research Institute, Seattle (Von Korff); Department of Anesthesiology, Rutgers University, Newark, N.J. (Datta); Department of Anesthesiology, Columbia University Medical Center, New York (Sonty, Weinberger); Department of Psychiatry, New York University, New York (Ross); Cornell University Medical College, New York (Inturrisi)
| | - Michael Von Korff
- Department of Psychiatry, Columbia University Medical Center (Hasin, Shmulewitz, Aharonovich, Scodes, Wall) and New York State Psychiatric Institute (Hasin, Shmulewitz, Stohl, Greenstein, Aharonovich, Scodes, Wall), New York; Epidemiology, Pfizer, Inc., New York (Petronis); Kaiser Permanente Washington Health Research Institute, Seattle (Von Korff); Department of Anesthesiology, Rutgers University, Newark, N.J. (Datta); Department of Anesthesiology, Columbia University Medical Center, New York (Sonty, Weinberger); Department of Psychiatry, New York University, New York (Ross); Cornell University Medical College, New York (Inturrisi)
| | - Samyadev Datta
- Department of Psychiatry, Columbia University Medical Center (Hasin, Shmulewitz, Aharonovich, Scodes, Wall) and New York State Psychiatric Institute (Hasin, Shmulewitz, Stohl, Greenstein, Aharonovich, Scodes, Wall), New York; Epidemiology, Pfizer, Inc., New York (Petronis); Kaiser Permanente Washington Health Research Institute, Seattle (Von Korff); Department of Anesthesiology, Rutgers University, Newark, N.J. (Datta); Department of Anesthesiology, Columbia University Medical Center, New York (Sonty, Weinberger); Department of Psychiatry, New York University, New York (Ross); Cornell University Medical College, New York (Inturrisi)
| | - Nomita Sonty
- Department of Psychiatry, Columbia University Medical Center (Hasin, Shmulewitz, Aharonovich, Scodes, Wall) and New York State Psychiatric Institute (Hasin, Shmulewitz, Stohl, Greenstein, Aharonovich, Scodes, Wall), New York; Epidemiology, Pfizer, Inc., New York (Petronis); Kaiser Permanente Washington Health Research Institute, Seattle (Von Korff); Department of Anesthesiology, Rutgers University, Newark, N.J. (Datta); Department of Anesthesiology, Columbia University Medical Center, New York (Sonty, Weinberger); Department of Psychiatry, New York University, New York (Ross); Cornell University Medical College, New York (Inturrisi)
| | - Stephen Ross
- Department of Psychiatry, Columbia University Medical Center (Hasin, Shmulewitz, Aharonovich, Scodes, Wall) and New York State Psychiatric Institute (Hasin, Shmulewitz, Stohl, Greenstein, Aharonovich, Scodes, Wall), New York; Epidemiology, Pfizer, Inc., New York (Petronis); Kaiser Permanente Washington Health Research Institute, Seattle (Von Korff); Department of Anesthesiology, Rutgers University, Newark, N.J. (Datta); Department of Anesthesiology, Columbia University Medical Center, New York (Sonty, Weinberger); Department of Psychiatry, New York University, New York (Ross); Cornell University Medical College, New York (Inturrisi)
| | - Charles Inturrisi
- Department of Psychiatry, Columbia University Medical Center (Hasin, Shmulewitz, Aharonovich, Scodes, Wall) and New York State Psychiatric Institute (Hasin, Shmulewitz, Stohl, Greenstein, Aharonovich, Scodes, Wall), New York; Epidemiology, Pfizer, Inc., New York (Petronis); Kaiser Permanente Washington Health Research Institute, Seattle (Von Korff); Department of Anesthesiology, Rutgers University, Newark, N.J. (Datta); Department of Anesthesiology, Columbia University Medical Center, New York (Sonty, Weinberger); Department of Psychiatry, New York University, New York (Ross); Cornell University Medical College, New York (Inturrisi)
| | - Michael L Weinberger
- Department of Psychiatry, Columbia University Medical Center (Hasin, Shmulewitz, Aharonovich, Scodes, Wall) and New York State Psychiatric Institute (Hasin, Shmulewitz, Stohl, Greenstein, Aharonovich, Scodes, Wall), New York; Epidemiology, Pfizer, Inc., New York (Petronis); Kaiser Permanente Washington Health Research Institute, Seattle (Von Korff); Department of Anesthesiology, Rutgers University, Newark, N.J. (Datta); Department of Anesthesiology, Columbia University Medical Center, New York (Sonty, Weinberger); Department of Psychiatry, New York University, New York (Ross); Cornell University Medical College, New York (Inturrisi)
| | - Jennifer Scodes
- Department of Psychiatry, Columbia University Medical Center (Hasin, Shmulewitz, Aharonovich, Scodes, Wall) and New York State Psychiatric Institute (Hasin, Shmulewitz, Stohl, Greenstein, Aharonovich, Scodes, Wall), New York; Epidemiology, Pfizer, Inc., New York (Petronis); Kaiser Permanente Washington Health Research Institute, Seattle (Von Korff); Department of Anesthesiology, Rutgers University, Newark, N.J. (Datta); Department of Anesthesiology, Columbia University Medical Center, New York (Sonty, Weinberger); Department of Psychiatry, New York University, New York (Ross); Cornell University Medical College, New York (Inturrisi)
| | - Melanie M Wall
- Department of Psychiatry, Columbia University Medical Center (Hasin, Shmulewitz, Aharonovich, Scodes, Wall) and New York State Psychiatric Institute (Hasin, Shmulewitz, Stohl, Greenstein, Aharonovich, Scodes, Wall), New York; Epidemiology, Pfizer, Inc., New York (Petronis); Kaiser Permanente Washington Health Research Institute, Seattle (Von Korff); Department of Anesthesiology, Rutgers University, Newark, N.J. (Datta); Department of Anesthesiology, Columbia University Medical Center, New York (Sonty, Weinberger); Department of Psychiatry, New York University, New York (Ross); Cornell University Medical College, New York (Inturrisi)
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Gewandter JS, Smith SM, Dworkin RH, Turk DC, Gan TJ, Gilron I, Hertz S, Katz NP, Markman JD, Raja SN, Rowbotham MC, Stacey BR, Strain EC, Ward DS, Farrar JT, Kroenke K, Rathmell JP, Rauck R, Brown C, Cowan P, Edwards RR, Eisenach JC, Ferguson M, Freeman R, Gray R, Giblin K, Grol-Prokopczyk H, Haythornthwaite J, Jamison RN, Martel M, McNicol E, Oshinsky M, Sandbrink F, Scholz J, Scranton R, Simon LS, Steiner D, Verburg K, Wasan AD, Wentworth K. Research approaches for evaluating opioid sparing in clinical trials of acute and chronic pain treatments: Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials recommendations. Pain 2021; 162:2669-2681. [PMID: 33863862 PMCID: PMC8497633 DOI: 10.1097/j.pain.0000000000002283] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 03/23/2021] [Indexed: 11/26/2022]
Abstract
ABSTRACT Randomized clinical trials have demonstrated the efficacy of opioid analgesics for the treatment of acute and chronic pain conditions, and for some patients, these medications may be the only effective treatment available. Unfortunately, opioid analgesics are also associated with major risks (eg, opioid use disorder) and adverse outcomes (eg, respiratory depression and falls). The risks and adverse outcomes associated with opioid analgesics have prompted efforts to reduce their use in the treatment of both acute and chronic pain. This article presents Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT) consensus recommendations for the design of opioid-sparing clinical trials. The recommendations presented in this article are based on the following definition of an opioid-sparing intervention: any intervention that (1) prevents the initiation of treatment with opioid analgesics, (2) decreases the duration of such treatment, (3) reduces the total dosages of opioids that are prescribed for or used by patients, or (4) reduces opioid-related adverse outcomes (without increasing opioid dosages), all without causing an unacceptable increase in pain. These recommendations are based on the results of a background review, presentations and discussions at an IMMPACT consensus meeting, and iterative drafts of this article modified to accommodate input from the co-authors. We discuss opioid sparing definitions, study objectives, outcome measures, the assessment of opioid-related adverse events, incorporation of adequate pain control in trial design, interpretation of research findings, and future research priorities to inform opioid-sparing trial methods. The considerations and recommendations presented in this article are meant to help guide the design, conduct, analysis, and interpretation of future trials.
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Affiliation(s)
| | | | | | | | - Tong Joo Gan
- Stony Brook School of Medicine, Stony Brook, NY, USA
| | - Ian Gilron
- Queens University, Kingston, Ontario, Canada
| | - Sharon Hertz
- (Formally) U.S. Food and Drug Administration, Silver Spring, MD, USA
| | | | | | | | | | | | | | - Denham S. Ward
- University of Rochester Medical Center, Rochester, NY, USA
| | | | - Kurt Kroenke
- Indiana University School of Medicine, Indianapolis, IN, USA
| | - James P. Rathmell
- Brigham and Women’s Hospital / Harvard Medical School, Boston, MA, USA
| | | | | | - Penney Cowan
- American Chronic Pain Association, Rocklin, CA, USA
| | - Robert R. Edwards
- Brigham and Women’s Hospital / Harvard Medical School, Boston, MA, USA
| | | | | | - Roy Freeman
- Brigham and Women’s Hospital / Harvard Medical School, Boston, MA, USA
| | - Roy Gray
- GW Pharmaceuticals, Carlsbad, CA, USA
| | | | | | | | - Robert N. Jamison
- Brigham and Women’s Hospital / Harvard Medical School, Boston, MA, USA
| | | | | | | | - Friedhelm Sandbrink
- U.S. Department of Veterans Affairs / George Washington University, Washington, DC, USA
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7
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Carrell DS, Albertson-Junkans L, Ramaprasan A, Scull G, Mackwood M, Johnson E, Cronkite DJ, Baer A, Hansen K, Green CA, Hazlehurst BL, Janoff SL, Coplan PM, DeVeaugh-Geiss A, Grijalva CG, Liang C, Enger CL, Lange J, Shortreed SM, Von Korff M. Measuring problem prescription opioid use among patients receiving long-term opioid analgesic treatment: development and evaluation of an algorithm for use in EHR and claims data. J Drug Assess 2020; 9:97-105. [PMID: 32489718 PMCID: PMC7241518 DOI: 10.1080/21556660.2020.1750419] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Accepted: 03/17/2020] [Indexed: 11/04/2022] Open
Abstract
Objective Opioid surveillance in response to the opioid epidemic will benefit from scalable, automated algorithms for identifying patients with clinically documented signs of problem prescription opioid use. Existing algorithms lack accuracy. We sought to develop a high-sensitivity, high-specificity classification algorithm based on widely available structured health data to identify patients receiving chronic extended-release/long-acting (ER/LA) therapy with evidence of problem use to support subsequent epidemiologic investigations. Methods Outpatient medical records of a probability sample of 2,000 Kaiser Permanente Washington patients receiving ≥60 days’ supply of ER/LA opioids in a 90-day period from 1 January 2006 to 30 June 2015 were manually reviewed to determine the presence of clinically documented signs of problem use and used as a reference standard for algorithm development. Using 1,400 patients as training data, we constructed candidate predictors from demographic, enrollment, encounter, diagnosis, procedure, and medication data extracted from medical claims records or the equivalent from electronic health record (EHR) systems, and we used adaptive least absolute shrinkage and selection operator (LASSO) regression to develop a model. We evaluated this model in a comparable 600-patient validation set. We compared this model to ICD-9 diagnostic codes for opioid abuse, dependence, and poisoning. This study was registered with ClinicalTrials.gov as study NCT02667262 on 28 January 2016. Results We operationalized 1,126 potential predictors characterizing patient demographics, procedures, diagnoses, timing, dose, and location of medication dispensing. The final model incorporating 53 predictors had a sensitivity of 0.582 at positive predictive value (PPV) of 0.572. ICD-9 codes for opioid abuse, dependence, and poisoning had a sensitivity of 0.390 at PPV of 0.599 in the same cohort. Conclusions Scalable methods using widely available structured EHR/claims data to accurately identify problem opioid use among patients receiving long-term ER/LA therapy were unsuccessful. This approach may be useful for identifying patients needing clinical evaluation.
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Affiliation(s)
- David S Carrell
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | | | - Arvind Ramaprasan
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Grant Scull
- Kaiser Permanente Washington, Seattle, WA, USA
| | | | - Eric Johnson
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - David J Cronkite
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | | | - Kris Hansen
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Carla A Green
- Kaiser Permanente Center for Health Research Northwest Region, Portland, OR, USA
| | - Brian L Hazlehurst
- Kaiser Permanente Center for Health Research Northwest Region, Portland, OR, USA
| | - Shannon L Janoff
- Kaiser Permanente Center for Health Research Northwest Region, Portland, OR, USA
| | | | | | | | | | | | - Jane Lange
- The Fred Hutchison Cancer Research Center, Seattle, WA, USA
| | - Susan M Shortreed
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Michael Von Korff
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
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