The Opioid Risk Tool: Can this Validated Tool Predict Post-Operative Opioid Dependence Following Arthroscopic Rotator Cuff Repair?

Document Type : RESEARCH PAPER


1 Rowan University School of Osteopathic Medicine, Department of Orthopedic Surgery, Stratford, NJ, USA

2 The Rothman Institute at Jefferson University, Philadelphia, PA, USA


Background: Numerous attempts have been made to decrease the incidence of opioid dependence after orthopedic surgeries. However, no effective means of preoperative risk stratification currently exists. The purpose of this study was to determine the ability of the Opioid Risk Tool (ORT) to predict the rate of opioid dependence 2 years after arthroscopic rotator cuff repair (ARCR). Methods: We prospectively evaluated all patients undergoing primary ARCR at a single institution over a 1.5 year period with a minimum of 2-year follow-up. All patients completed the ORT prior to surgery and were stratified into Low, Moderate, and High risk categories. The primary outcome was postoperative opioid dependence, defined as receiving a minimum of 6 opioid prescriptions within 2 years following surgery. Secondary outcomes included the total number of morphine milligram equivalents prescribed, total number of opioid prescriptions filled, and total number of opioid pills prescribed during this time interval. All outcome variables were compared amongst Low, Moderate, and High risk groups. Assessment of a statistical correlation between each outcome variable and individual numerical ORT scores (1-9) was performed. Results: A total of 137 patients were included for analysis. No statistically significant difference was noted in any primary or secondary outcome variable when compared between Low, Moderate, and High risk groups. The total cohort demonstrated a 19% rate of post-operative opioid dependence. No correlation was identified between any outcome variable and individual numerical ORT scores. A greater rate of dependence and quantity of opioids prescribed was noted amongst patients with a history of prior opioid use. Conclusion: The ORT was not predictive of the risk of opioid dependence or quantity of opioids prescribed after ARCR. Attention should be focused on alternative means of identification and management of patients at risk for opioid dependence after orthopedic procedures, including those with a history of prior opioid use. Level of evidence: III


1 . Sethi PM, Brameier DT, Mandava NK, Miller SR. Liposomal bupivacaine reduces opiate consumption after rotator cuff repair in a randomized controlled trial. J Shoulder Elbow Surg. 2019 May;28(5):819–27 .
2 . Syed UAM, Aleem AW, Wowkanech C, Weekes D, Freedman M, Tjoumakaris F, et al. Neer Award 2018: the effect of preoperative education on opioid consumption in patients undergoing arthroscopic rotator cuff repair: a prospective, randomized clinical trial. J Shoulder Elbow Surg. 2018 Jun;27(6):962–7 .
3 . Hah JM, Sturgeon JA, Zocca J, Sharifzadeh Y, Mackey SC. Factors associated with prescription opioid misuse in a cross-sectional cohort of patients with chronic non-cancer pain. J Pain Res. 2017 May 3;10:979–87 .
4 . Manchikanti L, Giordano J, Boswell MV, Fellows B, Manchukonda R, Pampati V. Psychological factors as predictors of opioid abuse and illicit drug use in chronic pain patients. J Opioid Manag. 2007 Apr;3(2):89–100 .
5 . Clarke H, Soneji N, Ko DT, Yun L, Wijeysundera DN. Rates and risk factors for prolonged opioid use after major surgery: population based cohort study. BMJ. 2014 Feb 11;348:g1251 .
6 . Stark N, Kerr S, Stevens J. Prevalence and predictors of persistent post-surgical opioid use: a prospective observational cohort study. Anaesth Intensive Care. 2017;45(6):700–6 .
7 . Sun EC, Darnall BD, Baker LC, Mackey S. Incidence of and Risk Factors for Chronic Opioid Use Among Opioid-Naive Patients in the Postoperative Period. JAMA Intern Med. 2016 01;176(9):1286–93 .
8 . Butler SF, Budman SH, Fernandez K, Jamison RN. Validation of a screener and opioid assessment measure for patients with chronic pain. Pain. 2004 Nov;112(1–2):65–75 .
9 . Jones T, Lookatch S, Moore T. Validation of a new risk assessment tool: the Brief Risk Questionnaire. J Opioid Manag. 2015 Apr;11(2):171–83 .
10 . Webster LR, Webster RM. Predicting aberrant behaviors in opioid-treated patients: preliminary validation of the Opioid Risk Tool. Pain Med. 2005 Dec;6(6):432–42 .
11 . Jones T, Moore T, Levy JL, Daffron S, Browder JH, Allen L, et al. A comparison of various risk screening methods in predicting discharge from opioid treatment. Clin J Pain. 2012 Feb;28(2):93–100 .
12 . Moore TM, Jones T, Browder JH, Daffron S, Passik SD. A comparison of common screening methods for predicting aberrant drug-related behavior among patients receiving opioids for chronic pain management. Pain Med. 2009 Nov;10(8):1426–33 .
13 . Dowell D, Haegerich TM, Chou R. CDC Guideline for Prescribing Opioids for Chronic Pain - United States, 2016. MMWR Recomm Rep. 2016 Mar 18;65(1):1–49 .
14 . Weekes DG, Feldman JA, Campbell RE, DeFrance M, Tjoumakaris FP, Austin L. The Incidence of Chronic Opioid Use Following Arthroscopic Rotator Cuff Repair and Patient Opioid Education. Orthopaedic Journal of Sports Medicine. 2019 Jul;7(7_suppl5):2325967119S0025 .
15 . Williams BT, Redlich NJ, Mickschl DJ, Grindel SI. Influence of preoperative opioid use on postoperative outcomes and opioid use after arthroscopic rotator cuff repair. J Shoulder Elbow Surg. 2019 Mar;28(3):453–60 .
16 . National Academies of Sciences E, Division H and M, Policy B on HS, Abuse C on PM and RS to APO, Phillips JK, Ford MA, et al. Trends in Opioid Use, Harms, and Treatment [Internet]. National Academies Press (US); 2017 [cited 2020 Jan 25]. Available from: