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Assessing risk of opioid misuse in the treatment of chronic pain: Building a practical actuarial approach

David M. Erekson, PhD, Liliana Bautista, Dallin Albright


Objective: Opioid misuse risk assessment has been highlighted as an important part of clinical practice, but there is a paucity of research identifying an effective approach to assessment. Currently, practitioners use patient history, interviews, and formal questionnaires, and these data are weighed clinically to assign risk. The authors propose the use of an actuarial method—the Bayesian nomogram—as a simple, standard, evidence-based approach to opioid misuse risk assessment.

Interventions: The Bayesian nomogram relies solely on empirically established relationships between risk factors and risk and has been found in other fields to be both more efficient and more consistent than clinical judgment. The authors performed a comprehensive search of the literature to identify empirically established risk factors for opioid misuse in the treatment of noncancer chronic pain.

Results: As the Bayesian nomogram requires both base rates of the predicted event (opioid misuse) and odds ratios for risk factors, the authors reported the most current evidence available in the literature. The authors also included the nomogram itself for easy clinical application of base rates and risk factors in the predictive model. Finally, the authors provided examples to help illustrate practical application.

Conclusions: The authors call for research comparing this methodology to “assessment as usual” to better predict risk of opioid misuse and to aid decision making for medical providers treating chronic-pain patients.


opioid misuse, risk assessment, chronic pain

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Ballantyne JC, LaForge KS: Opioid dependence and addiction during treatment of chronic pain. Pain. 2007; 129(3): 235-255.

Højsted J, Sjøgren P: Addiction to opioids in chronic pain patients: A literature review. Eur J Pain. 2007; 11(5): 490-518.

Katz NP, Adams EH, Benneyan JC, et al.: Foundations of opioid risk management. Clin J Pain. 2007; 23(2): 103-118.

Sinatra R: Opioid analgesics in primary care: Challenges and new advances in the management of noncancer pain. J Am Board Fam Med. 2006; 19(2): 165-177.

Chou R, Fanciullo GJ, Fine PG, et al.: Clinical guidelines for the use of chronic opioid therapy in chronic noncancer pain. J Pain. 2009; 10(2): 113-130.

Setnik B, Roland CL, Sommerville KW, et al.: A multicenter, primary care-based, open-label study to identify behaviors related to prescription opioid misuse, abuse, and diversion in opioid-experienced patients with chronic moderate-to-severe pain. J Pain Res. 2015; 8: 361-373.

Passik SD, Kirsh KL, Casper D: Addiction-related assessment tools and pain management: Instruments for screening, treatment planning, and monitoring compliance. Pain Med. 2008; 9(S2): S145-S166.

Butler SF, Fernandez K, Benoit C, et al.: Validation of the revised Screener and Opioid Assessment for Patients with Pain (SOAPP-R). J Pain. 2008; 9(4): 360-372.

Butler SF, Budman SH, Fernandez KC, et al.: Cross-validation of a screener to predict opioid misuse in chronic pain patients (SOAPP-R). J Addict Med. 2009; 3(2): 66-73.

Webster LR, Webster RM: Predicting aberrant behaviors in opioid-treated patients: Preliminary validation of the opioid risk tool. Pain Med. 2005; 6(6): 432-442.

Juurlink DN, Dhalla IA: Dependence and addiction during chronic opioid therapy. J Med Toxicol. 2012; 8(4): 393-399.

Belgrade MJ, Schamber CD, Lindgren BR: The DIRE score: Predicting outcomes of opioid prescribing for chronic pain. J Pain. 2006; 7(9): 671-681.

Lawrence R, Mogford D, Colvin L: Systematic review to determine which validated measurement tools can be used to assess risk of problematic analgesic use in patients with chronic pain. Br J Anaesthesia, 2017; 119(6): 1092-1109.

Adams LL, Gatchel RJ, Robinson RC, et al.: Development of a self-report screening instrument for assessing potential opioid medication misuse in chronic pain patients. J Pain Sympt Manag. 2004; 27(5): 440-459.

Holmes CP, Gatchel RJ, Adams LL, et al.: An opioid screening instrument: Long-term evaluation of the utility of the pain medication questionnaire. Pain Pract. 2006; 6(2): 74-88.

Chou R, Fanciullo GJ, Fine PG, et al.: Opioids for chronic noncancer pain: Prediction and identification of aberrant drug-related behaviors: A review of the evidence for an American Pain Society and American Academy of Pain Medicine clinical practice guideline. J Pain. 2009; 10(2): 131-146.

Turk DC, Swanson KS, Gatchel RJ: Predicting opioid misuse by chronic pain patients: A systematic review and literature synthesis. Clin J Pain. 2008; 24(6): 497-508.

Dawes RM, Faust D, Meehl PE: Clinical versus actuarial judgment. Science. 1989; 243(4899): 1668-1674.

Grove WM, Meehl PE: Comparative efficiency of informal (subjective, impressionistic) and formal (mechanical, algorithmic) prediction procedures: The clinical–statistical controversy. Psychol Public Policy Law. 1996; 2(2): 293-323.

Wasan AD, Butler SF, Budman SH, et al.: Psychiatric history and psychologic adjustment as risk factors for aberrant drug-related behavior among patients with chronic pain. Clin J Pain. 2007; 23(4): 307-315.

Fagan TJ: Letter: Nomogram for Bayes theorem. N Engl J Med. 1975; 293(5): 257-257.

Vowles KE, McEntee ML, Julnes PS, et al.: Rates of opioid misuse, abuse, and addiction in chronic pain: A systematic review and data synthesis. Pain. 2015; 156(4): 569-576.

Campbell CI, Bahorik AL, Van Velduisen P, et al.: Use of a prescription opioid registry to examine opioid misuse and overdose in an integrated health system. Prev Med. 2018; 110: 31-37.

Hylan TR, Von Korff M, Saunders K, et al.: Automated prediction of risk for problem opioid use in a primary care setting. J Pain. 2015; 16(4): 380-387.

Haller IV, Renier CM, Juusola M, et al.: Enhancing risk assessment in patients receiving chronic opioid analgesic therapy using natural language processing. Pain Med. 2017; 18(10): 1952-1960.

Ives TJ, Chelminski PR, Hammett-Stabler CA, et al.: Predictors of opioid misuse in patients with chronic pain: A prospective cohort study. BMC Health Serv Res. 2006; 6(1): 36-46.

Katz C, El-Gabalawy R, Keyes KM, et al.: Risk factors for incident nonmedical prescription opioid use and abuse and dependence: Results from a longitudinal nationally representative sample. Drug Alcohol Depend. 2013; 132(1): 107-113.

Khalid L, Liebschutz JM, Xuan Z, et al.: Adherence to prescription opioid monitoring guidelines among residents and attending physicians in the primary care setting. Pain Med. 2015; 16(3): 480-487.

Tetrault JM, Desai RA, Becker WC, et al.: Gender and nonmedical use of prescription opioids: Results from a national US survey. Addiction. 2008; 103(2): 258-268.

Zale EL, Dorfman ML, Hooten WM, et al.: Tobacco smoking, nicotine dependence, and patterns of prescription opioid misuse: Results from a nationally representative sample. Nicotine Tob Res. 2014; 17(9): 1096-1103.

Ford JA, Rigg KK: Racial/ethnic differences in factors that place adolescents at risk for prescription opioid misuse. Prev Sci. 2014; 16(5): 633-641.

Grattan A, Sullivan MD, Saunders KW, et al.: Depression and prescription opioid misuse among chronic opioid therapy recipients with no history of substance abuse. Ann Fam Med. 2012; 10(4): 304-311.

Jenkins MM, Youngstrom EA, Washburn JJ, et al.: Evidence-based strategies improve assessment of pediatric bipolar disorder by community practitioners. Prof Psychol Res Pr. 2011; 42(2): 121-129.

Grove WM, Zald DH, Lebow BS, et al.: Clinical versus mechanical prediction: A meta-analysis. Psychol Assess. 2000; 12(1), 19-30.

Youngstrom EA, Duax J, Hamilton J: Evidence-based assessment of pediatric bipolar disorder, part 1: Base rate and family history. J Am Acad Child Adolesc Psychiatr. 2005; 44(7): 712-717.

Youngstrom EA, Freeman AJ, & Jenkins MM: The assessment of bipolar disorder in children and adolescents. Child Adolesc Psychiatr Clin N Am. 2009; 18(2): 353-390.

Jenkins MM, Youngstrom EA, Youngstrom JK, et al.: Generalizability of evidence-based assessment recommendations for pediatric bipolar disorder. Psychol Assess. 2012; 24(2): 269-281.



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