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Abstract

In this article, we examine the relationship between self-reported opioid use and employment outcomes among Social Security Disability Insurance (SSDI) applicants who applied to SSDI in 2009. We use a machine learning method to identify opioids recorded in text fields on SSDI applications. Studying outcomes for 4 years after the U.S. Social Security Administration (SSA) determined the application outcome, we find a negative and statistically significant association between self-reported opioid use at application and post-determination employment-related outcomes. Notably, opioid use at the time of application was associated with a 3% point decline in the likelihood of employment in the first 4 years after determination and represents a 7.5% decline relative to the mean employment rate for the period. Results from a reduced-form model estimating the relationship between local opioid prescribing patterns and employment outcomes suggest that a 10% increase in the local opioid prescribing rate is associated with employment that is, at most, 0.3% points lower, which is similar to the documented association among the broader U.S. population. However, the potential implications for SSDI applicants are particularly notable because opioid use is about 50% higher among SSDI applicants.

Keywords

economics/social security pharmacology employment

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References

Aliprantis

D. K.

Fee

M. E.

Schweitzer . (2019). Opioids and the labor market (Federal Reserve Bank of Cleveland, working paper no. 18–07R). https://doi.org/10.26509/frbc-wp-201807r

Bound

(1989). The health and earnings of rejected disability insurance applicants. American Economic Review, 79(3), 482–503.

Center for Behavioral Health Statistics and Quality. (2015). 2014 National Survey on Drug Use and Health: Methodological summary and definitions. Rockville, MD: Substance Abuse and Mental Health Services Administration. https://www.samhsa.gov/data/sites/default/files/NSDUH-MethodSummDefs2014/NSDUH-MethodSummDefs2014.htm

Centers for Disease Control and Prevention. (2016). CDC guideline for prescribing opioids for chronic pain: United States, 2016. https://www.cdc.gov/mmwr/volumes/65/rr/rr6501e1.htm

Centers for Disease Control and Prevention. (2018). Annual surveillance report of drug-related risks and outcomes, 2018. https://www.cdc.gov/drugoverdose/pdf/pubs/2018-cdc-drug-surveillance-report.pdf

Centers for Disease Control and Prevention. (2019). Opioid basics: Understanding the epidemic. https://www.cdc.gov/drugoverdose/epidemic/index.html

Centers for Disease Control and Prevention. (2020.). U.S. opioid prescribing rate maps. https://www.cdc.gov/drugoverdose/maps/rxrate-maps.html

Chen

S. W.

van der Klaauw . (2008). The work disincentive effects of the disability insurance program in the 1990s. Journal of Econometrics, 142(2), 757–784.

Currie

J. J.

Jin

Schnell . (2019). US employment and opioids: Is there a connection? In Polachek

S. W.

Tatsiramos

(Eds.), Health and labor markets (Vol. 47, pp. 253–280). Emerald.

10.

Cutler

D. E.

Meara

Stewart . (2017). Has wider availability of prescription drugs for pain relief affected SSDI and SSI enrollment? (Working paper no. NB 17–14). National Bureau of Economic Research, Disability Research Center.

11.

Fendrich

M. T. P.

Johnson

J. S.

Wislar

Hubbell

Sipehler . (2004). The utility of drug testing in epidemiological research: Results from a general population survey. Addiction, 9(2), 197–208.

12.

French

E. J.

Song . (2014). The effect of disability insurance receipt on labor supply. American Economic Journal: Economic Policy, 6(2), 291–337.

13.

Frienden

T. R. D.

Houry . (2016). Reducing the risks of relief: The CDC’s opioid-prescribing guideline. New England Journal of Medicine, 374(16), 1501–1504.

14.

Garthwaite

C. L.

(2012). The economic benefits of pharmaceutical innovations: The case of Cox-2 inhibitors. American Economic Journal: Applied Economics, 4(3), 116–137. https://doi.org/10.1257/app.4.3.116

15.

Harris

M. C. L. M.

Kessler

M. N.

Murray

Glenn . (2019). Prescription opioids and labor market pains: The effect of schedule II opioids on labor force participation and unemployment. The Journal of Human Resources, 55(4), 1319–1364.

16.

Kilby

(2015). Opioids for the masses: Welfare tradeoffs in the regulation of narcotic pain medications [Working paper]. Northeastern University.

17.

Krueger

(2017). Where have all the workers gone? An inquiry into the decline of the U.S. labor force participation rate Brookings papers on economic activity, 2017(2), 1–87.

18.

Kuo

Y.-F. M. A.

Raji

J. S.

Goodwin . (2019). Association of disability with mortality from opioid overdose among U.S. Medicare adults. Journal of the American Medical Association Network Open, 2(11), Article e1915638.

19.

Maestas

N. K. J.

Mullen

Strand . (2013). Does disability insurance receipt discourage work? Using examiner assignment to estimate causal effects of SSDI receipt. The American Economic Review, 103(5), 1797–1829.

20.

Mathieson

S. G.

Wertheimer

C. G.

Maher

C. W.

Lin

A. J.

McLachlan

Buchbinder

S. A.

Pearson

Underwood . (2020). What proportion of patients with chronic noncancer pain are prescribed an opioid medicine? Systematic review and meta-regression of observational studies. Journal of Internal Medicine, 287(5), 458–474.

21.

Morden

N. E. J. C.

Munson

C. H.

Colla

J. S.

Skinner

J. P. W.

Bynum

Zhou

E. R.

Meara . (2014). Prescription opioid use among disabled Medicare beneficiaries: Intensity, trends, and regional variation. Medical Care, 52, 852–859.

22.

Mytelka

Kuester

Gray

Everheart

(2018) How Changing Opioid Prescribing Patterns Can Impact Risk Scores. Seattle, WA: Milliman.

23.

Patra

B. G. M. M.

Sharma

Vekaria

Adekkanattu

O. V.

Patterson

Glicksberg

L. A.

Lepow

Ryu

J. M.

Biernacka

Furmanchuk

T. J.

Geroge

Hogan

Yang

Bian

Weissman

Wickramarante

J. J.

Mann

Olfson

T. R.

Pathak , . (2021). Extracting social determinants of health from electronic health records using natural language processing: A systematic review. Journal of the American Medical Informatics Association, 28(12), 2716–2727. https://doi.org/10.1093/jamia/ocab170

24.

Savych

B. D.

Neumark

Lea . (2018). The impact of opioid prescriptions on duration of temporary disability [Working paper]. Workers’ Compensation Research Institute.

25.

Scherrer

J. F. J.

Salas

L. A.

Copeland

E. M.

Stock

B. K.

Ahmedani

M. D.

Sullivan

Burroughs

Schneider

K. K.

Bucholz

P. J.

Lustman . (2016). Prescription opioid duration, dose, and increased risk of depression in three large patient populations. Annals of Family Medicine, 14(1), 54–62.

26.

Schiltenwolf

M. M.

Akbar

Hug

Pfuller

Gantz

Neubauer

Flor

Wang . (2014). Evidence of specific cognitive deficits in patients with chronic low back pain under long-term substitution treatment of opioids. Pain Physician, 17(1), 9–20.

27.

Schimmel

J. D. C.

Stapleton

J. G.

Song . (2011). How common is parking among Social Security Disability Insurance beneficiaries? Evidence from the 1999 change in the earnings level of substantial gainful activity. Social Security Bulletin, 71(4), 77–92.

28.

Schopf

T. D.

Braun

D. F.

Matthes . (2022). Evaluating unsupervised text classification: Zero-shot and similarity-based approaches. Arxiv. https://doi.org/10.48550/ARXIV.2211.16285

29.

Singleton

J. C.

P. D.

Akpunonu

E. L.

Abner

A. M.

Kucharska-Newton . (2023). Using natural language processing to identify opioid use disorder in electronic health record data. International Journal of Medical Informatics, 170, Article 104963. https://doi.org/10.1016/j.ijmedinf.2022.104963

30.

Social Security Administration. (2020). Annual statistical supplement, 2020. https://www.ssa.gov/policy/docs/statcomps/supplement/2020/6c.pdf

31.

Social Security Administration. (2019). Annual performance report fiscal years 2018–2020. https://www.ssa.gov/agency/performance/materials/2019/SSA_FYs_2018-2020_APR_2019.03.18_FINAL_508_Certified.pdf

32.

U.S. Department of Health and Human Services. (2019, September). What is the U.S. opioid epidemic? https://www.hhs.gov/opioids/about-the-epidemic/index.html

33.

von Wachter

T. J.

Song

Manchester . (2011). Trends in employment and earnings of allowed and rejected applicants to the Social Security Disability Insurance program. American Economic Review, 101(7), 3308–3329.

34.

Vowles

E. M. L.

McEntee

P. S.

Julnes

Frohe

J. P.

Ney

D. N.

van der Goes . (2015). Rates of opioid misuse, abuse, and addiction in chronic pain: A systematic review and data synthesis. Pain, 156(4), 569–576. https://doi.org/10.1097/01.j.pain.0000460357.01998.f1

35.

A. Y. D.

Hoffman

O’Leary . (2020). Trends in opioid use among Social Security Disability Insurance applicants [Working paper]. Center for Retirement Research at Boston College.

36.

A. Y. P.

Mariani

Hurwitz . (2019). New statistics of opioid use among SSDI applicants and their policy implications [Working paper]. Center for Retirement Research at Boston College.

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Employment Outcomes for Social Security Disability Insurance Applicants Who Use Opioids

Abstract

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