Trends in Opioid Use among Social Security Disability Insurance Applicants

The effect of awarding disability benefits on opioid consumption

“…This paper also has a supporting information. Section from this supporting information presents a review of the literature on opioid use and DB from the economics and public health literature (Abdulhadi, 2019; Bound, 1991; Bütikofer & Skira, 2018; Chen & Van der Klauuw, 2008; Franklin et al., 2008; Gebauer et al., 2019; Ghertner, 2020; Hollingsworth et al., 2017; Maestas, 2019; Maestas et al., 2013; Morden et al., 2014; Park & Powell, 2021; Parsons, 1980, 1991; Powell et al., 2020; Savych et al., 2019; Soni, 2018; Wettstein, 2019; Wu et al., 2019; Von Wachter et al., 2011; Zhou et al., 2018). Section presents a series of robustness and placebo tests for our main estimation, while Section discusses the effects of awarding DB on other variables of interest with the aim of identifying the most likely channels through which DB impacts opioid use.…”

Opioid Use Among Social Security Disability Insurance Applicants, 2013–2018

“…Finally, we estimate the association between the rate and the composition of disability applications and opioid prescribing rates at the community level. Our approach complements the innovative strategy developed by Wu and colleagues (2020) but contributes important additional strengths, notably the use of a much larger training sample to identify possible opioid drug names drawn from multiple years of application data; the exclusion of opioid-containing cough and cold medications to more precisely identify opioids used to treat pain; and leveraging data from other application free-text fields to refine the classification of misspelled opioid names, and to identify opioids used to treat opioid use disorder (OUD) rather than pain. Our analysis is an important step toward understanding the effects of excess opioid prescribing, and the attempts to counteract it, on disability applications.…”

“…Wu et al (2019) found that between 2007 and 2017, 40% of applicants reported their medications using both the drop-down and free-text options, while 42% used freetext entry only, illustrating the importance of examining the free-text fields. Moreover, the share of applicants entering medications into free-text fields has increased over time (Wu et al, 2019). colleagues (2019, 2020) have conducted the only other analyses examining the prevalence of opioid use among SSDI applicants using SSA administrative data.…”

“…Medications, for example, can be selected via a prepopulated drop-down list, entered as free text, or both. Wu et al (2019) found that between 2007 and 2017, 40% of applicants reported their medications using both the drop-down and free-text options, while 42% used free-text entry only, illustrating the importance of examining the free-text fields. Moreover, the share of applicants entering medications into free-text fields has increased over time (Wu et al, 2019).…”

“…Wu and colleagues (2019, 2020) have conducted the only other analyses examining the prevalence of opioid use among SSDI applicants using SSA administrative data. Using a random sample of 100,000 SSDI applicants in 2013 (4.5% of applicants in that year), they developed a natural language processing (NLP) algorithm to identify opioid medication names in the application free-text fields and drop-down menus (Wu et al, 2020). They applied this algorithm to a 30% sample of SSDI applicants from 2007 to 2017 and estimated that the prevalence of opioid use at the time of application ranged from 26% to 32% (Wu et al, 2019).…”