Economic Evaluation: A Randomized Pragmatic Trial of a Primary Care-based Cognitive Behavioral Intervention for Adults Receiving Long-term Opioids for Chronic Pain.
Journal
Medical care
ISSN: 1537-1948
Titre abrégé: Med Care
Pays: United States
ID NLM: 0230027
Informations de publication
Date de publication:
01 06 2022
01 06 2022
Historique:
pubmed:
31
3
2022
medline:
18
5
2022
entrez:
30
3
2022
Statut:
ppublish
Résumé
Chronic pain is prevalent and costly; cost-effective nonpharmacological approaches that reduce pain and improve patient functioning are needed. Report the incremental cost-effectiveness ratio (ICER), compared with usual care, of cognitive behavioral therapy aimed at improving functioning and pain among patients with chronic pain on long-term opioid treatment. Economic evaluation conducted alongside a pragmatic cluster randomized trial. Adults with chronic pain on long-term opioid treatment (N=814). A cognitive behavioral therapy intervention teaching pain self-management skills in 12 weekly, 90-minute groups delivered by an interdisciplinary team (behaviorists, nurses) with additional support from physical therapists, and pharmacists. Cost per quality adjusted life year (QALY) gained, and cost per additional responder (≥30% improvement on standard scale assessment of Pain, Enjoyment, General Activity, and Sleep). Costs were estimated as-delivered, and replication. Per patient intervention replication costs were $2145 ($2574 as-delivered). Those costs were completely offset by lower medical care costs; inclusive of the intervention, total medical care over follow-up was $1841 lower for intervention patients. Intervention group patients also had greater QALY and responder gains than did controls. Supplemental analyses using pain-related medical care costs revealed ICERs of $35,000, and $53,000 per QALY (for replication, and as-delivered intervention costs, respectively); the ICER when excluding patients with outlier follow-up costs was $106,000. Limited to 1-year follow-up; identification of pain-related utilization potentially incomplete. The intervention was the optimal choice at commonly accepted levels of willingness-to-pay for QALY gains; this finding was robust to sensitivity analyses.
Sections du résumé
BACKGROUND
Chronic pain is prevalent and costly; cost-effective nonpharmacological approaches that reduce pain and improve patient functioning are needed.
OBJECTIVE
Report the incremental cost-effectiveness ratio (ICER), compared with usual care, of cognitive behavioral therapy aimed at improving functioning and pain among patients with chronic pain on long-term opioid treatment.
DESIGN
Economic evaluation conducted alongside a pragmatic cluster randomized trial.
SUBJECTS
Adults with chronic pain on long-term opioid treatment (N=814).
INTERVENTION
A cognitive behavioral therapy intervention teaching pain self-management skills in 12 weekly, 90-minute groups delivered by an interdisciplinary team (behaviorists, nurses) with additional support from physical therapists, and pharmacists.
OUTCOME MEASURES
Cost per quality adjusted life year (QALY) gained, and cost per additional responder (≥30% improvement on standard scale assessment of Pain, Enjoyment, General Activity, and Sleep). Costs were estimated as-delivered, and replication.
RESULTS
Per patient intervention replication costs were $2145 ($2574 as-delivered). Those costs were completely offset by lower medical care costs; inclusive of the intervention, total medical care over follow-up was $1841 lower for intervention patients. Intervention group patients also had greater QALY and responder gains than did controls. Supplemental analyses using pain-related medical care costs revealed ICERs of $35,000, and $53,000 per QALY (for replication, and as-delivered intervention costs, respectively); the ICER when excluding patients with outlier follow-up costs was $106,000.
LIMITATIONS
Limited to 1-year follow-up; identification of pain-related utilization potentially incomplete.
CONCLUSION
The intervention was the optimal choice at commonly accepted levels of willingness-to-pay for QALY gains; this finding was robust to sensitivity analyses.
Identifiants
pubmed: 35352703
doi: 10.1097/MLR.0000000000001713
pii: 00005650-202206000-00005
pmc: PMC9106895
mid: NIHMS1782964
doi:
Substances chimiques
Analgesics, Opioid
0
Types de publication
Journal Article
Randomized Controlled Trial
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
423-431Subventions
Organisme : NCCIH NIH HHS
ID : UH2 AT007788
Pays : United States
Organisme : NINDS NIH HHS
ID : UH3 NS088731
Pays : United States
Informations de copyright
Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.
Déclaration de conflit d'intérêts
R.A.D. reports royalties from UpToDate for authoring topics on low back pain. The remaining authors declare no conflict of interest.
Références
Gaskin DJ, Richard P. The economic costs of pain in the United States. J Pain. 2012;13:715–724.
Manchikanti L, Singh A. Therapeutic opioids: a ten-year perspective on the complexities and complications of the escalating use, abuse, and nonmedical use of opioids. Pain Physician. 2008;11(suppl):S63–S88.
Von Korff M, Kolodny A, Deyo RA, et al. Long-term opioid therapy reconsidered. Ann Intern Med. 2011;155:325–328.
Scholl L, Seth P, Kariisa M, et al. Drug and opioid-involved overdose deaths—United States, 2013-2017. MMWR Morb Mortal Wkly Rep. 2018;67:1419–1427.
Skelly AC, Chow R, Dettori JR, et al. Integrated and comprehensive pain management programs: effectiveness and harms. comparative effectiveness review no. 251. (Prepared by the Pacific Northwest Evidence-based Practice Center under Contract No. 75Q80120D00006.) AHRQ Publication No. 22-EHC002. Rockville, MD: 2021 Oct 2021. Report No.: Contract No.: 22-EHC992.
Husereau D, Drummond M, Petrou S, et al. Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement. Value Health. 2013;16:e1–e5.
DeBar L, Mayhew M, Benes L, et al. A primary care-based cognitive behavioral therapy intervention for long-term opioid users with chronic pain: a randomized pragmatic trial. Ann Intern Med. 2022;175:46–55.
DeBar L, Benes L, Bonifay A, et al. Interdisciplinary team-based care for patients with chronic pain on long-term opioid treatment in primary care (PPACT)—protocol for a pragmatic cluster randomized trial. Contemp Clin Trials. 2018;67:91–99.
Krebs EE, Lorenz KA, Bair MJ, et al. Development and initial validation of the PEG, a three-item scale assessing pain intensity and interference. J Gen Intern Med. 2009;24:733–738.
Roland M, Morris R. A study of the natural history of back pain. Part I: development of a reliable and sensitive measure of disability in low-back pain. Spine (Phila Pa 1976). 1983;8:141–144.
Roland M, Fairbank J. The Roland-Morris Disability Questionnaire and the Oswestry Disability Questionnaire. Spine (Phila Pa 1976). 2000;25:3115–3124.
Davidson M, Keating JL. A comparison of five low back disability questionnaires: reliability and responsiveness. Phys Ther. 2002;82:8–24.
Jordan K, Dunn KM, Lewis M, et al. A minimal clinically important difference was derived for the Roland-Morris Disability Questionnaire for low back pain. J Clin Epidemiol. 2006;59:45–52.
Stratford PW, Binkley J, Solomon P, et al. Defining the minimum level of detectable change for the Roland-Morris questionnaire. Physical Ther. 1996;76:359–365; discussion 66–68.
Dworkin RH, Turk DC, McDermott MP, et al. Interpreting the clinical importance of group differences in chronic pain clinical trials: IMMPACT recommendations. Pain. 2009;146:238–244.
ICER. 2020-2023 Value Assessment Framework Online. 2020. Available at: https://icer-review.org/wp-content/uploads/2019/05/ICER_2020_2023_VAF_013120-4.pdf . Accessed October 9, 2020.
Neumann PJ, Cohen JT, Weinstein MC. Updating cost-effectiveness—the curious resilience of the $50,000-per-QALY threshold. N Engl J Med. 2014;371:796–797.
Cameron D, Ubels J, Norström F. On what basis are medical cost-effectiveness thresholds set? Clashing opinions and an absence of data: a systematic review. Glob Health Action. 2018;11:1447828.
Loudon K, Treweek S, Sullivan F, et al. The PRECIS-2 tool: designing trials that are fit for purpose. Bmj. 2015;350:h2147.
Hurst NP, Kind P, Ruta D, et al. Measuring health-related quality of life in rheumatoid arthritis: validity, responsiveness and reliability of EuroQol (EQ-5D). Br J Rheumatol. 1997;36:551–559.
Herdman M, Gudex C, Lloyd A, et al. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011;20:1727–1736.
Longworth L, Rowen D. Mapping to obtain EQ-5D utility values for use in NICE health technology assessments. Value Health. 2013;16:202–210.
van Hout B, Janssen MF, Feng YS, et al. Interim scoring for the EQ-5D-5L: mapping the EQ-5D-5L to EQ-5D-3L value sets. Value Health. 2012;15:708–715.
Smith DL, O’Keeffe-Rosetti M, Mayhew M, et al. Utility prediction in pragmatic trials: a case study in improving prediction with survey variables. International Health Economics Association; Basel; 2019.
Ahrens A, Hansen CB, Schaffer ME. lassopack: model selection and prediction with regularized regression in Stata. Stata J. 2020;20:176–235.
Frank lE, Friedman JH. A statistical view of some chemometrics regression tools. Technometrics. 1993;35:109–135.
Tibshirani R. Regression shrinkage and selection via the Lasso. J R Stat SOC Series B Stat Methodol. 1996;58:267–288.
Belloni A, Chernozhukov V. Least squares after model selection in high-dimensional sparse models. Bernoulli. 2013;19:521–547.
Gray LA, Hernandez Alava M, Wailoo AJ. Development of methods for the mapping of utilities using mixture models: mapping the AQLQ-S to the EQ-5D-5L and the HUI3 in patients with asthma. Value Health. 2018;21:748–757.
Bureau of Labor Statistics, US Department of Labor. News release: employer costs for employee compensation—June 2021 USDL-21-1647 2021. Available at: https://www.bls.gov/news.release/pdf/ecec.pdf . Accessed October 22, 2021.
Department of Labor. Labor Cost Inputs Used in the Employee Benefits Security Administration, Office of Policy and Research’s Regulatory Impact Analyses and Paperwork Reduction Act Burden Calculation. 2019. Available at: https://www.dol.gov/sites/dolgov/files/EBSA/laws-and-regulations/rules-and-regulations/technical-appendices/labor-cost-inputs-used-in-ebsa-opr-ria-and-pra-burden-calculations-june-2019.pdf . Accessed October 22, 2021.
Ross TR, Ng D, Brown JS, et al. The HMO research network virtual data warehouse: a public data model to support collaboration. EGEMS (Wash DC). 2014;2:1049.
O’Keeffe-Rosetti MC, Hornbrook MC, Fishman PA, et al. A standardized relative resource cost model for medical care: application to cancer control programs. J Natl Cancer Inst Monogr. 2013;2013:106–116.
Mayhew M, DeBar LL, Deyo RA, et al. Development and assessment of a crosswalk between ICD-9-CM and ICD-10-CM to identify patients with common pain conditions. J Pain. 2019;20:1429–1445.
Smith DH, DeBar LL, Kuntz JL, et al. Reducing opioid exposure following hip and knee surgery: results of a randomized, pragmatic, pharmacist-led intervention. P16.01 from the 23rd annual Health Care Systems Research Network Conference, March 21-23, 2017, San Diego, California. J Patient Cent Res Rev. 2017;4:197.
Hoch JS, Dewa CS. Advantages of the net benefit regression framework for economic evaluations of interventions in the workplace: a case study of the cost-effectiveness of a collaborative mental health care program for people receiving short-term disability benefits for psychiatric disorders. J Occup Environ Med. 2014;56:441–445.
Hoch JS, Rockx MA, Krahn AD. Using the net benefit regression framework to construct cost-effectiveness acceptability curves: an example using data from a trial of external loop recorders versus Holter monitoring for ambulatory monitoring of “community acquired” syncope. BMC Health Serv Res. 2006;6:68.
Hoch JS, Briggs AH, Willan AR. Something old, something new, something borrowed, something blue: a framework for the marriage of health econometrics and cost-effectiveness analysis. Health Econ. 2002;11:415–430.
Fenwick E, Byford S. A guide to cost-effectiveness acceptability curves. Br J Psychiatry. 2005;187:106–108.
Heapy AA, Higgins DM, Goulet JL, et al. Interactive voice response-based self-management for chronic back pain: the COPES noninferiority randomized trial. JAMA Intern Med. 2017;177:765–773.
Higgins DM, Buta E, Williams DA, et al. Internet-based pain self-management for Veterans: feasibility and preliminary efficacy of the pain EASE program. Pain Pract. 2020;20:357–370.
Fine PG. Long-term consequences of chronic pain: mounting evidence for pain as a neurological disease and parallels with other chronic disease states. Pain Med. 2011;12:996–1004.
Dueñas M, Ojeda B, Salazar A, et al. A review of chronic pain impact on patients, their social environment and the health care system. J Pain Res. 2016;9:457–467.