View Item 

Show simple item record

Development of a Risk Index for Serious Prescription Opioid‐Induced Respiratory Depression or Overdose in Veterans’ Health Administration Patients
dc.contributor.authorZedler, Barbaraen_US
dc.contributor.authorXie, Linen_US
dc.contributor.authorWang, Lien_US
dc.contributor.authorJoyce, Andrewen_US
dc.contributor.authorVick, Catherineen_US
dc.contributor.authorBrigham, Janeten_US
dc.contributor.authorKariburyo, Furahaen_US
dc.contributor.authorBaser, Onuren_US
dc.contributor.authorMurrelle, Lennen_US
dc.date.accessioned2015-09-01T19:31:01Z
dc.date.available2016-09-06T15:43:59Zen
dc.date.issued2015-08en_US
dc.identifier.citationZedler, Barbara; Xie, Lin; Wang, Li; Joyce, Andrew; Vick, Catherine; Brigham, Janet; Kariburyo, Furaha; Baser, Onur; Murrelle, Lenn (2015). "Development of a Risk Index for Serious Prescription Opioid‐Induced Respiratory Depression or Overdose in Veterans’ Health Administration Patients." Pain Medicine 16(8): 1566-1579.en_US
dc.identifier.issn1526-2375en_US
dc.identifier.issn1526-4637en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/113174
dc.description.abstractObjectiveDevelop a risk index to estimate the likelihood of life‐threatening respiratory depression or overdose among medical users of prescription opioids.Subjects, Design, and MethodsA case‐control analysis of administrative health care data from the Veterans’ Health Administration identified 1,877,841 patients with a pharmacy record for an opioid prescription between October 1, 2010 and September 30, 2012. Overdose or serious opioid‐induced respiratory depression (OSORD) occurred in 817. Ten controls were selected per case (n = 8,170). Items for an OSORD risk index (RIOSORD) were selected through logistic regression modeling, with point values assigned to each predictor. Modeling of risk index scores produced predicted probabilities of OSORD; risk classes were defined by the predicted probability distribution.ResultsFifteen variables most highly associated with OSORD were retained as items, including mental health disorders and pharmacotherapy; impaired drug metabolism or excretion; pulmonary disorders; specific opioid characteristics; and recent hospital visits. The average predicted probability of experiencing OSORD ranged from 3% in the lowest risk decile to 94% in the highest, with excellent agreement between predicted and observed incidence across risk classes. The model's C‐statistic was 0.88 and Hosmer–Lemeshow goodness‐of‐fit statistic 10.8 (P > 0.05).ConclusionRIOSORD performed well in identifying medical users of prescription opioids within the Veterans’ Health Administration at elevated risk of overdose or life‐threatening respiratory depression, those most likely to benefit from preventive interventions. This novel, clinically practical, risk index is intended to provide clinical decision support for safer pain management. It should be assessed, and refined as necessary, in a more generalizable population, and prospectively evaluated.en_US
dc.publisherNational Center for Health Statisticsen_US
dc.publisherWiley Periodicals, Inc.en_US
dc.subject.otherIndexen_US
dc.subject.otherRespiratory Depressionen_US
dc.subject.otherOverdoseen_US
dc.subject.otherRisken_US
dc.subject.otherOpioiden_US
dc.subject.otherQuestionnaireen_US
dc.titleDevelopment of a Risk Index for Serious Prescription Opioid‐Induced Respiratory Depression or Overdose in Veterans’ Health Administration Patientsen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelMedicine (General)en_US
dc.subject.hlbtoplevelHealth Sciencesen_US
dc.description.peerreviewedPeer Revieweden_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/113174/1/pme12777.pdf
dc.identifier.doi10.1111/pme.12777en_US
dc.identifier.sourcePain Medicineen_US
dc.identifier.citedreferenceHall AJ, Logan JE, Toblin RL, et al. Patterns of abuse among unintentional pharmaceutical overdose fatalities. JAMA 2008; 300 ( 22 ): 2613 – 20.en_US
dc.identifier.citedreferenceBraden JB, Russo J, Fan MY, et al. Emergency department visits among recipients of chronic opioid therapy. Arch Intern Med 2010; 170 ( 16 ): 1425 – 32.en_US
dc.identifier.citedreferenceLanier WA, Johnson EM, Rolfs RT, Friedrichs MD, Grey TC. Risk factors for prescription opioid‐related death, Utah, 2008‐2009. Pain Med 2012; 13 ( 12 ): 1580 – 89.en_US
dc.identifier.citedreferenceNuckols TK, Anderson L, Popescu I, et al. Opioid prescribing: A systematic review and critical appraisal of guidelines for chronic pain. Ann Intern Med 2013; 160 ( 1 ): 38 – 47.en_US
dc.identifier.citedreferencePaulozzi LJ, Logan JE, Hall AJ, et al. A comparison of drug overdose deaths involving methadone and other opioid analgesics in West Virginia. Addiction 2009; 104 ( 9 ): 1541 – 48.en_US
dc.identifier.citedreferenceWarner M, Chen LH, Makuc DM, Anderson RN, Minino AM. Drug poisoning deaths in the United States, 1980‐2008. NCHS Data Brief 2011;( 81 ): 1 – 8.en_US
dc.identifier.citedreferenceWebster LR, Cochella S, Dasgupta N, et al. An analysis of the root causes for opioid‐related overdose deaths in the United States. Pain Med 2011; 12(suppl2): S26 – 35.en_US
dc.identifier.citedreferencePaulozzi LJ, Kilbourne EM, Shah NG, et al. A history of being prescribed controlled substances and risk of drug overdose death. Pain Med 2012; 13 ( 1 ): 87 – 95.en_US
dc.identifier.citedreferenceJCAHO. Safe use of opioids in hospitals. The Joint Commission Sentinel Event Alert. 2012; 49: 1 – 5.en_US
dc.identifier.citedreferenceMorasco BJ, Duckart JP, Carr TP, Deyo RA, Dobscha SK. Clinical characteristics of veterans prescribed high doses of opioid medications for chronic non‐cancer pain. Pain 2010; 151 ( 3 ): 625 – 32.en_US
dc.identifier.citedreferenceEdlund MJ, Sullivan M, Steffick D, Harris KM, Wells KB. Do users of regularly prescribed opioids have higher rates of substance use problems than nonusers? Pain Med 2007; 8 ( 8 ): 647 – 56.en_US
dc.identifier.citedreferenceSeal KH, Shi Y, Cohen G, et al. Association of mental health disorders with prescription opioids and high‐risk opioid use in US veterans of Iraq and Afghanistan. JAMA 2012; 307 ( 9 ): 940 – 7.en_US
dc.identifier.citedreferenceHasegawa K, Brown DF, Tsugawa Y, Camargo CA Jr. Epidemiology of emergency department visits for opioid overdose: A population‐based study. Mayo Clin Proc 2014; 89 ( 4 ): 462 – 71.en_US
dc.identifier.citedreferenceLeppert W, Luczak J. The role of tramadol in cancer pain treatment—A review. Support Care Cancer 2005; 13 ( 1 ): 5 – 17.en_US
dc.identifier.citedreferenceFine PG, Portenoy RK. A Clinical Guide to Opioid Analgesia. Minneapolis, MN: McGraw Hill; 2004.en_US
dc.identifier.citedreferenceVieweg WV, Lipps WF, Fernandez A. Opioids and methadone equivalents for clinicians. Prim Care Companion J Clin Psychiatry 2005; 7 ( 3 ): 86 – 8.en_US
dc.identifier.citedreferenceVon Korff M, Saunders K, Ray GT, et al. Defacto long‐term opioid therapy for non‐cancer pain. Clin J Pain 2008; 24 ( 6 ): 521 – 7.en_US
dc.identifier.citedreferenceAPS. Opioid analgesics. In: Miaskowski C, Bair M, Chou R, D'Arcy Y, Hartwick C, Huffman L, Maleki J, Manworren R, eds. Principles of Analgesic Use in the Treatment of Acute Pain and Cancer Pain, 6th edition. Glenview, IL: American Pain Society; 2008: 19 – 38.en_US
dc.identifier.citedreferenceIOM. Relieving Pain in America: A Blueprint for Transforming Prevention, Care, Education, and Research. Washington, DC: The National Academies Press; 2011.en_US
dc.identifier.citedreferenceNIDA. Prescription Drugs: Abuse and Addiction. Older Adults. Updated 2011. Available at http://www.drugabuse.gov/publications/research‐reports/prescription‐drugs/trends‐in‐prescription‐drug‐abuse/older‐adults (accessed May 30, 2014).en_US
dc.identifier.citedreferenceCDC. Prescription Drug Overdoses ‐ A US Epidemic. MMWR Morb Mort Wkly Rep 2012;61(1):10–3.en_US
dc.identifier.citedreferencePaulozzi LJ, Zhang K, Jones CM, Mack KA. Risk of adverse health outcomes with increasing duration and regularity of opioid therapy. J Am Board Fam Med 2014; 27 ( 3 ): 329 – 38.en_US
dc.identifier.citedreferenceAlbert S, Brason FW 2nd, Sanford CK, et al. Project Lazarus: Community‐based overdose prevention in rural North Carolina. Pain Med 2011; 12(suppl2): S77 – 85.en_US
dc.identifier.citedreferenceBeletsky L, Rich JD, Walley AY. Prevention of fatal opioid overdose. JAMA 2012; 308 ( 18 ): 1863 – 64.en_US
dc.identifier.citedreferenceKim D, Irwin KS, Khoshnood K. Expanded access to naloxone: Options for critical response to the epidemic of opioid overdose mortality. Am J Public Health 2009; 99 ( 3 ): 402 – 7.en_US
dc.identifier.citedreferenceCDC. Community‐based opioid overdose prevention programs providing naloxone ‐ United States, 2010. MMWR Morb Mortal Wkly Rep 2012; 61( 6 ): 101 – 5.en_US
dc.identifier.citedreferenceFDA. FDA Approves New Hand‐Held Auto‐Injector to Reverse Opioid Overdose. 2014. Available at http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm391465.htm (accessed April 4, 2014).en_US
dc.identifier.citedreferenceFDA. FDA Commissioner Margaret A. Hamburg Statement on Prescription Opioid Abuse. 2014. Available at http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm391590.htm (accessed April 4, 2014).en_US
dc.identifier.citedreferenceWHO. Community Management of Opioid Overdose. 2014. Available at http://www.who.int/substance_abuse/publications/management_opioid_overdose/en/ (accessed January 25, 2015).en_US
dc.identifier.citedreferenceChen LH, Hedegaard H, Warner M. Drug‐Poisoning Deaths Involving Opioid Analgesics: United States, 1999–2011. NCHS Data Brief, No 166. Hyattsville, MD: National Center for Health Statistics; 2014.en_US
dc.identifier.citedreferenceCDC. Vital signs: Overdoses of prescription opioid pain relievers—United States, 1999–2008. MMWR Morb Mortal Wkly Rep 2011; 60 ( 43 ): 1487 – 92.en_US
dc.identifier.citedreferenceCDC. Wide‐ranging OnLine Data for Epidemiologic Research (WONDER); 2014. Available at: http://wonder.cdc.gov/mortSQL.html (Accessed October 7, 2014).en_US
dc.identifier.citedreferenceCDC. Vital signs: Risk for overdose from methadone used for pain relief—United States, 1999–2010. MMWR Morb Mort Wkly Rep 2012; 61 ( 26 ): 493 – 7.en_US
dc.identifier.citedreferenceBoudreau D, Von Korff M, Rutter CM, et al. Trends in long‐term opioid therapy for chronic non‐cancer pain. Pharmacoepidemiol Drug Saf 2009; 18 ( 12 ): 1166 – 75.en_US
dc.identifier.citedreferenceManchikanti L, Fellows B, Ailinani H, Pampati V. Therapeutic use, abuse, and nonmedical use of opioids: A ten‐year perspective. Pain Physician 2010; 13 ( 5 ): 401 – 35.en_US
dc.identifier.citedreferenceParsells Kelly J, Cook SF, Kaufman DW, et al. Prevalence and characteristics of opioid use in the US adult population. Pain 2008; 138 ( 3 ): 507 – 13.en_US
dc.identifier.citedreferenceSullivan MD, Edlund MJ, Fan MY, et al. Trends in use of opioids for non‐cancer pain conditions 2000‐2005 in commercial and medicaid insurance plans: The TROUP study. Pain 2008; 138 ( 2 ): 440 – 9.en_US
dc.identifier.citedreferenceSullivan MD, Edlund MJ, Steffick D, Unutzer J. Regular use of prescribed opioids: Association with common psychiatric disorders. Pain 2005; 119 ( 1–3 ): 95 – 103.en_US
dc.identifier.citedreferenceMosher HJ, Krebs EE, Carrel M, et al. Trends in prevalent and incident opioid receipt: An observational study in Veterans Health Administration 2004‐2012. J Gen Intern Med 2014.en_US
dc.identifier.citedreferenceJungquist CR, Karan S, Perlis ML. Risk factors for opioid‐induced excessive respiratory depression. Pain Manag Nurs 2011; 12 ( 3 ): 180 – 7.en_US
dc.identifier.citedreferenceStephens E, Louden M, Van De Voort J. Opioid toxicity. Medscape 2012. Available at: http://emedicine.medscape.com/article/815784 (accessed December 17, 2013).en_US
dc.identifier.citedreferenceSAMHSA. SAMHSA Opioid Overdose Prevention Toolkit: Information for Prescribers. HHS Publication No. (SMA) 13‐4742. Rockville, MD: Substance Abuse and Mental Health Services Administration; 2013.en_US
dc.identifier.citedreferenceBohnert AS, Valenstein M, Bair MJ, et al. Association between opioid prescribing patterns and opioid overdose‐related deaths. JAMA 2011; 305( 13 ): 1315 – 21.en_US
dc.identifier.citedreferenceZedler B, Xie L, Wang L, et al. Risk factors for serious prescription opioid‐related toxicity or overdose among Veterans Health Administration patients. Pain Med 2014; 15: 1911 – 29.en_US
dc.identifier.citedreferenceDunn KM, Saunders KW, Rutter CM, et al. Opioid prescriptions for chronic pain and overdose: A cohort study. Ann Intern Med 2010; 152 ( 2 ): 85 – 92.en_US
dc.identifier.citedreferenceGomes T, Juurlink DN, Dhalla IA, et al. Trends in opioid use and dosing among socio‐economically disadvantaged patients. Open Med 2011; 5 ( 1 ): e13 – 22.en_US
dc.identifier.citedreferenceWhittemore AS. Evaluating health risk models. Stat Med 2010; 29 ( 23 ): 2438 – 52.en_US
dc.identifier.citedreferenceLeung YW, Li M, Devins G, et al. Routine screening for suicidal intention in patients with cancer. Psychooncology 2013; 22 ( 11 ): 2537 – 45.en_US
dc.identifier.citedreferenceNakayama M, Osaki S, Shimokawa H. Validation of mortality risk stratification models for cardiovascular disease. Am J Cardiol 2011; 108 ( 3 ): 391 – 6.en_US
dc.identifier.citedreferenceWang L, Porter B, Maynard C, et al. Predicting risk of hospitalization or death among patients with heart failure in the Veterans Health Administration. Am J Cardiol 2012; 110 ( 9 ): 1342 – 49.en_US
dc.identifier.citedreferenceStone NJ, Robinson J, Lichtenstein AH, et al. 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: A report of the American college of cardiology/American heart association task force on practice guidelines. Circulation 2014; 129: S1 – S45.en_US
dc.identifier.citedreferenceArozullah AM, Khuri SF, Henderson WG, Daley J. Development and validation of a multifactorial risk index for predicting postoperative pneumonia after major noncardiac surgery. Ann Intern Med 2001; 135 ( 10 ): 847 – 57.en_US
dc.identifier.citedreferenceGupta H, Gupta PK, Fang X, et al. Development and validation of a risk calculator predicting postoperative respiratory failure. Chest 2011; 140 ( 5 ): 1207 – 15.en_US
dc.identifier.citedreferenceBatzlaff CM, Karpman C, Afessa B, Benzo RP. Predicting 1‐year mortality rate for patients admitted with an acute exacerbation of chronic obstructive pulmonary disease to an intensive care unit: an opportunity for palliative care. Mayo Clin Proc 2014; 89 ( 5 ): 638 – 43.en_US
dc.identifier.citedreferenceWebster LR, Webster RM. Predicting aberrant behaviors in opioid‐treated patients: Preliminary validation of the opioid risk tool. Pain Med 2005; 6 ( 6 ): 432 – 42.en_US
dc.identifier.citedreferenceButler SF, Fernandez K, Benoit C, Budman SH, Jamison RN. Validation of the revised screener and opioid assessment for patients with pain (SOAPP‐R). J Pain 2008; 9 ( 4 ): 360 – 72.en_US
dc.identifier.citedreferenceHolmes 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.en_US
dc.identifier.citedreferenceBrown RL, Leonard T, Saunders LA, Papasouliotis O. The prevalence and detection of substance use disorders among inpatients ages 18 to 49: An opportunity for prevention. Prev Med 1998; 27 ( 1 ): 101 – 10.en_US
dc.identifier.citedreferenceFriedman R, Li V, Mehrotra D. Treating pain patients at risk: Evaluation of a screening tool in opioid‐treated pain patients with and without addiction. Pain Med 2003; 4 ( 2 ): 182 – 5.en_US
dc.identifier.citedreferenceCoambs R, Jarry J, Santhiapillai A. The SISAP: A new screening instrument for identifying potential opioid abuse in the management of chronic nonmalignant pain in general medical practice. Pain Res Manag 1995; 1 ( 3 ): 155 – 62.en_US
dc.identifier.citedreferenceChou 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 – 30.en_US
dc.identifier.citedreferenceRothman KJ, Greenland S. Modern Epidemiology, 2nd edition. Philadelphia, PA: Lippincott‐Raven; 1998.en_US
dc.identifier.citedreferenceWacholder S, McLaughlin JK, Silverman DT, Mandel JS. Selection of controls in case‐control studies. I. Principles. Am J of Epidemiol 1992; 135 ( 9 ): 1019 – 28.en_US
dc.identifier.citedreferenceWacholder S, Silverman DT, McLaughlin JK, Mandel JS. Selection of controls in case‐control studies. II. Types of controls. Am J of Epidemiol 1992; 135 ( 9 ): 1029 – 41.en_US
dc.identifier.citedreferenceCharlson ME, Charlson RE, Peterson JC, et al. The Charlson comorbidity index is adapted to predict costs of chronic disease in primary care patients. J Clin Epidemiol 2008; 61 ( 12 ): 1234 – 40.en_US
dc.identifier.citedreferenceCharlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis 1987; 40 ( 5 ): 373 – 83.en_US
dc.identifier.citedreferenceDeyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD‐9‐CM administrative databases. J Clin Epidemiol 1992; 45 ( 6 ): 613 – 9.en_US
dc.identifier.citedreferenceBaser O, Xie L, Mardekian J, et al. Prevalence of diagnosed opioid abuse and its economic burden in the Veterans Health Administration. Pain Pract 2014; 14 (5): 437 – 45.en_US
dc.identifier.citedreferenceXie L, Joshi AV, Schaaf D, et al. Differences in healthcare utilization and associated costs between patients prescribed vs. nonprescribed opioids during an inpatient or emergency department visit. Pain Pract 2014; 14 (5): 446 – 56.en_US
dc.identifier.citedreferenceFleming MF, Balousek SL, Klessig CL, Mundt MP, Brown DD. Substance use disorders in a primary care sample receiving daily opioid therapy. J Pain 2007; 8 ( 7 ): 573 – 82.en_US
dc.identifier.citedreferenceWalker JM, Farney RJ, Rhondeau SM, et al. Chronic opioid use is a risk factor for the development of central sleep apnea and ataxic breathing. JCSM 2007; 3 ( 5 ): 455 – 61.en_US
dc.identifier.citedreferencePrescription Drug Monitoring Program Training and Technical Assistance Center. Technical Assistance Guide No. 01‐13: Calculating Daily Morphine Milligram Equivalents; 2013. Available at: http://www.pdmpassist.org/pdf/BJA_performance_measure_aid_MME_conversion.pdf (accessed March 31, 2014).en_US
dc.identifier.citedreferencePrescription Drug Monitoring Program Training and Technical Assistance Center. Technical Assistance Guide No. 02‐13: Daily Morphine Milligram Equivalents Calculator and Guide. May 1, 2013. Available at: http://www.pdmpassist.org/pdf/bja_performance_measure_aid_mme_conversion_tool.pdf (accessed March 31, 2014 ).en_US
dc.identifier.citedreferenceLe Gall JR, Lemeshow S, Saulnier F. A new simplified acute physiology score (SAPS II) based on a European/North American multicenter study. JAMA 1993; 270 ( 24 ): 2957 – 63.en_US
dc.identifier.citedreferenceCook NR. Use and misuse of the receiver operating characteristic curve in risk prediction. Circulation 2007; 115 ( 7 ): 928 – 35.en_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Name:
pme12777.pdf
Size:
174.5KB
Format:
PDF
View/Open

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.