The prescribed opioids difficulties scale: a patient-centered assessment of problems and concerns

Caleb J Banta-Green, Michael Von Korff, Mark D Sullivan, Joseph O Merrill, Suzanne R Doyle, Kathleen Saunders, Caleb J Banta-Green, Michael Von Korff, Mark D Sullivan, Joseph O Merrill, Suzanne R Doyle, Kathleen Saunders

Abstract

Objectives: Chronic opioid therapy for chronic noncancer pain has increased dramatically in recent years. Research on associated risks has typically focused on opioid abuse and dependence, and opioid misuse or aberrant drug use behaviors, but these risks have been defined from the providers' perspective. The aim of this article was to develop a psychometrically sound method for assessing difficulties patients attribute to chronic opioid therapy.

Methods: A cross-sectional, observational study of patients prescribed opioids for chronic noncancer pain was conducted in a large integrated service delivery network in Washington State. Data were obtained from a phone interview and electronic health records including pharmacy data. Exploratory and confirmatory factor analyses were conducted using a split sample design.

Results: The interview response rate was 56.5% and a total of 1144 patients were included in analyses. A 2 factor solution was obtained and replicated with excellent fit statistics. Two correlated factors were identified-opioid control concerns and psychosocial problems-with 50% of the sample reporting difficulties with prescribed opioids: 24% reported elevated psychosocial problems and 36% reported elevated concerns about controlling their use of prescribed opioids.

Discussion: The Prescribed Opioid Difficulties Scale identifies common difficulties that patients ascribe to chronic opioid therapy. This scale may provide both an entry point and a framework for a patient-centered clinical dialog about the pros and cons of use of opioid medicines for managing chronic pain.

Figures

FIGURE 1
FIGURE 1
Distribution of scores on Problems, Concerns, and Combined Scales.

References

    1. Von Korff M, Saunders K, Ray GT, et al. De facto long-term opioid therapy for noncancer pain. Clin J Pain. 2008;24:521–527.
    1. Boudreau D, Von Korff M, Rutter CM, et al. Trends in long-term opioid therapy for chronic non-cancer pain. Pharmacoepidemiol Drug Safe. 2009;18:1166–1175.
    1. Sullivan 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;138:440–449.
    1. Weisner CM, Campbell CI, Ray GT, et al. Trends in prescribed opioid therapy for non-cancer pain for individuals with prior substance use disorders. Pain. 2009;145:287–293.
    1. Hall AJ, Logan JE, Toblin RL, et al. Patterns of abuse among unintentional pharmaceutical overdose fatalities. JAMA. 2008;300:2613–2620.
    1. Paulozzi LJ, Xi Y. Recent changes in drug poisoning mortality in the United States by urban-rural status and by drug type. Pharmacoepidemiol Drug Safe. 2008;17:997–1005.
    1. McCabe SE, Cranford JA, West BT. Trends in prescription drug abuse and dependence, co-occurrence with other substance use disorders, and treatment utilization: results from two national surveys. Addict Behav. 2008;33:1297–1305.
    1. American Psychiatric Institute. Diagnostic and Statistical Manual of Mental Disorder. 4. Washington DC: American Psychiatric Institute; 1994.
    1. Compton W, Volkow N. Major increases in opioid analgesic abuse in the United States: concerns and strategies. Drug Alcohol Depend. 2006;81:103–107.
    1. Sees KL, Clark HW. Opioid use in the treatment of chronic pain: assessment of addiction. J Pain Symptom Manage. 1993;8:257–264.
    1. Banta-Green CJ, Merrill JO, Doyle SR, et al. Measurement of opioid problems among chronic pain patients in a general medical population. Drug Alcohol Depend. 2009;104:43–49.
    1. Banta-Green CJ, Merrill JO, Doyle SR, et al. Opioid use behaviors, mental health and pain—development of a typology of chronic pain patients. Drug Alcohol Depend. 2009;104:34–42.
    1. Compton P, Darakjian J, Miotto K. Screening for addiction in patients with chronic pain and “problematic” substance use: evaluation of a pilot assessment tool. J Pain Symptom Manage. 1998;16:355–363.
    1. Morasco BJ, Dobscha SK. Prescription medication misuse and substance use disorder in VA primary care patients with chronic pain. Gen Hosp Psychiatry. 2008;30:93–99.
    1. Chabal C, Erjavec MK, Jacobson L, et al. Prescription opiate abuse in chronic pain patients: clinical criteria, incidence, and predictors. Clin J Pain. 1997;13:150–155.
    1. Fleming MF, Davis J, Passik SD, et al. Reported lifetime aberrant drug-taking behaviors are predictive of current substance use and mental health problems in primary care patients. Pain Med. 2008;9:1098–1106.
    1. Chelminski PR, Ives TJ, Felix KM, et al. A primary care, multi-disciplinary disease management program for opioid-treated patients with chronic non-cancer pain and a high burden of psychiatric comorbidity. BMC Health Serv Res. 2005;5:3.
    1. Reid MC, Engles-Horton LL, Weber MB, et al. Use of opioid medications for chronic noncancer pain syndromes in primary care. J Gen Intern Med. 2002;17:173–179.
    1. Fleming MF, Balousek SL, Klessig CL, et al. Substance use disorders in a primary care samples receiving daily opioid therapy. J Pain. 2007;8:573–582.
    1. Sullivan MD, Edlund MJ, Zhang L, et al. Association between mental health disorders, problem drug use, and regular prescription opioid use. Arch Intern Med. 2006;23:2087–2093.
    1. Rubin DB. Inference and missing data. Biometrika. 1976;63:581–592.
    1. Rubin DB. Multiple Imputation for Nonresponse in Surveys. New York: John Wiley and Sons, Inc; 1987.
    1. Yates A. Multivariate Exploratory Data Analysis: A Perspective on Exploratory Factor Analysis. Albany: State University of New York Press; 1988.
    1. Browne MW. An overview of analytic rotation in exploratory factor analysis. Multivariate Behav Res. 2001;36:111–150.
    1. Tucker LR. Personnel Research Section Report No. 984. Washington, DC: Department of the Army; 1951. A Method of Synthesis of Factor Analysis Studies.
    1. Wrigley CS, Neuhaus JO. The matching of two sets of factors. Am Psychol. 1955;10:418–419.
    1. MacCallum RC, Widaman KF, Zhang S, et al. Sample size in factor analysis. Psychol Methods. 1999;4:84–99.
    1. Muthén LK, Muthén BO. Mplus User’s Guide. Los Angeles, CA: Muthén & Muthén; 1998–2008.
    1. Hayton JC, Allen DG, Scarpello V. Factor retention decisions in exploratory factor analysis: a tutorial on parallel analysis. Organ Res Methods. 2004;7:191–205.
    1. Horn JL. A rationale and test for the number of factors in factor analysis. Psychometrika. 1965;30:179–185.
    1. O’Connor BP. SPSS and SAS programs for determining the number of components using parallel analysis and Velicer’s MAP test. Behav Res Methods Instrum Comput. 2000;32:396–402.
    1. Bentler PM. Comparative fit indices in structural models. Psychol Bull. 1990;107:238–246.
    1. Tucker LR, Lewis C. A reliability coefficient for maximum likelihood factor analysis. Psychometrika. 1973;38:1–10.
    1. Steiger JH, Lind JM. Statistically based tests for the number of common factors. Paper presented at the annual meeting of the Psychometric Society; Iowa City, IA. 1980.
    1. Bentler PM. EQS Structural Equations Program Manual. Encino, CA: Multivariate Software Inc; 1995.
    1. Muthén K, Muthén BO. Mplus User’s Guide. Los Angeles, CA: Muthén & Muthén; 1998–2001.
    1. Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model. 1999;6:1–55.
    1. Yu C, Muthén BO. Evaluation of Model Fit Indices for Latent Variable Models with Categorical and Continuous Outcomes. Paper presented at the annual conference of the American Educational Research Association; New Orleans. 2002.
    1. Yu C. Evaluating Cutoff Criteria of Model Fit Indices for Latent Variable Models With Binary and Continuous Outcomes. Los Angeles: Dissertation, University of California; 2002.
    1. Jöreskog KG. How large can a standardized coefficient be? 1999 [see ]
    1. Cronbach LJ. Coefficient alpha and the internal structure of tests. Psychometrika. 1951;16:297–334.
    1. Turk DC, Swanson KS, Gatchel RJ. Predicting opioid misuse by chronic pain patients: a systematic review and literature synthesis. Clin J Pain. 2008;24:497–508.
    1. Passik S, Kirsh KL, Casper D. Addiction-related assessment tools and pain management: instruments for screening, treatment planning and monitoring compliance. Pain Med. 2008;9(suppl 2):S145–S166.
    1. Chou R, Fanciullo GJ, Fine PG, et al. Opioids for chronic noncancer pain: prediction and identification of aberrant drugrelated behaviors: a review of the evidence for an American Pain Society and American Academy of Pain Medicine clinical practice guideline. J Pain. 2009;10:131–146.
    1. Sullivan MD, Von Korff M, Banta-Green C, et al. Problems and concerns of patients receiving chronic opioid therapy for chronic non-cancer pain. Pain. 2010;149:345–353.
    1. Boudreau DM, Doescher MP, Jackson JE, et al. Impact of healthcare delivery system on where HMO-enrolled seniors purchase medications. Ann Pharmacother. 2004;38:1317–1318.

Source: PubMed

3
Subscribe