Has the Increase in Disability Insurance Participation Contributed to Increased Opioid-Related Mortality?
Bibliographic record
Abstract
Ideas and Opinions15 November 2016Has the Increase in Disability Insurance Participation Contributed to Increased Opioid-Related Mortality?Nicholas B. King, PhD, Erin Strumpf, PhD, and Sam Harper, PhDNicholas B. King, PhDFrom McGill University, Montreal, Quebec, Canada.Search for more papers by this author, Erin Strumpf, PhDFrom McGill University, Montreal, Quebec, Canada.Search for more papers by this author, and Sam Harper, PhDFrom McGill University, Montreal, Quebec, Canada.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/M16-0918 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Mortality from unintentional prescription drug overdose has increased sharply in the United States since the mid-1990s. A large proportion of these deaths have involved benzodiazepines and other sedatives, antidepressants, sleep aids, and particularly opioid analgesics. In 2013, a total of 43 982 deaths were attributed to drug poisoning; 16 235 of these involved prescription opioids, a nearly 4-fold increase since 1999 (1).Researchers have identified a broad range of possible “supply-side” determinants of increasing opioid-related mortality, including increased prescription of opioid analgesics; prescription of stronger formulations and higher dosages; and the introduction and aggressive marketing of new pharmaceuticals, particularly OxyContin (Purdue Pharma), ...References1. Chen LH, Hedegaard H, Warner M. Rates of deaths from drug poisoning and drug poisoning involving opioid analgesics—United States, 1999–2013. MMWR Morb Mortal Wkly Rep. 2015;64:32. Google Scholar2. King NB, Fraser V, Boikos C, Richardson R, Harper S. Determinants of increased opioid-related mortality in the United States and Canada, 1990–2013: a systematic review. Am J Public Health. 2014;104:e32-42. [PMID: 24922138] doi:10.2105/AJPH.2014.301966 CrossrefMedlineGoogle Scholar3. Social Security Administration. Annual Statistical Report on the Social Security Disability Insurance Program, 2014. Washington, DC: Social Security Administration, Office of Retirement and Disability Policy, Office of Research Evaluation and Statistics; 2015. Google Scholar4. Liebman JB. Understanding the increase in disability insurance benefit receipt in the United States. J Econ Perspect. 2015;29:123-50. CrossrefMedlineGoogle Scholar5. Autor DH, Duggan MG. The rise in the disability rolls and the decline in unemployment. Q J Econ. 2006;118:157-206. CrossrefGoogle Scholar6. Wamhoff S, Wiseman M. The TANF/SSI connection. Soc Secur Bull. 2005;66:21-36. [PMID: 17590982] MedlineGoogle Scholar7. Hansen H, Bourgois P, Drucker E. Pathologizing poverty: new forms of diagnosis, disability, and structural stigma under welfare reform. Soc Sci Med. 2014;103:76-83. [PMID: 24507913] doi:10.1016/j.socscimed.2013.06.033 CrossrefMedlineGoogle Scholar8. Lakdawalla DN, Bhattacharya J, Goldman DP. Are the young becoming more disabled? Health Aff (Millwood). 2004;23:168-76. [PMID: 15002639] CrossrefMedlineGoogle Scholar9. Meara E, Horwitz JR, Powell W, McClelland L, Zhou W, O'Malley AJ, et al. State legal restrictions and prescription-opioid use among disabled adults. N Engl J Med. 2016. [PMID: 27332619] CrossrefMedlineGoogle Scholar10. Pacula RL, Powell D, Taylor E. Does Prescription Drug Coverage Increase Opioid Abuse? Evidence From Medicare Part D. NBER Working Paper no. 21072. Cambridge, MA: National Bureau of Economic Research; 2015. Google Scholar Author, Article, and Disclosure InformationAffiliations: From McGill University, Montreal, Quebec, Canada.Financial Support: Drs. Strumpf and Harper were each supported by a Chercheur boursier Junior 2 from the Fonds de la Recherche en Santé du Québec.Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M16-0918.Corresponding Author: Nicholas B. King, McGill University, Biomedical Ethics Unit, 3647 Peel Street, Montreal, Quebec H3A 1X1, Canada.Current Author Addresses: Dr. King: McGill University, Biomedical Ethics Unit, 3647 Peel Street, Montreal, Quebec H3A 1X1, Canada.Dr. Strumpf: McGill University, Department of Economics, Leacock 418, 855 Sherbrooke Street West, Montreal, Quebec H3A 2T7, Canada.Dr. Harper: McGill University, Department of Epidemiology, Biostatistics, and Occupational Health, Purvis Hall, 1020 Pine Avenue West, Montreal, Quebec H3A 1A2, Canada.Author Contributions: Conception and design: N.B. King, E. Strumpf, S. Harper.Analysis and interpretation of the data: N.B. King, E. Strumpf, S. Harper.Drafting of the article: N.B. King, E. Strumpf, S. Harper.Critical revision of the article for important intellectual content: N.B. King, E. Strumpf, S. Harper.Final approval of the article: N.B. King, E. Strumpf, S. Harper.Statistical expertise: E. Strumpf, S. Harper.Collection and assembly of data: E. Strumpf, S. Harper.This article was published at www.annals.org on 30 August 2016. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetails Metrics Cited byThe effect of awarding disability benefits on opioid consumptionTrends in medical conditions and functioning in the U.S. population, 1997–2017Declining Life Expectancy in the United States: Missing the Trees for the ForestReceipt of Disability Benefits and Prescription Opioid PrevalenceEarly High-Risk Opioid Prescribing Practices and Long-Term Disability Among Injured Workers in Washington State, 2002 to 2013Increased overall and cause‐specific mortality associated with disability among workers’ compensation claimants with low back injuriesAssessment of Opioid Prescribing Practices Before and After Implementation of a Health System Intervention to Reduce Opioid Overprescribing 15 November 2016Volume 165, Issue 10Page: 729-730KeywordsAddictionAnalgesicsDisabilitiesDrugsLower back painMedicareMortalityOpioidsOxycodonePublic policy ePublished: 30 August 2016 Issue Published: 15 November 2016 Copyright & PermissionsCopyright © 2016 by American College of Physicians. 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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.068 | 0.010 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".