Cumulative economic damages from 15 years of opioid misuse throughout Indiana.

Author:Brewer, Ryan M.


Due to the number of large tables in this article, we are providing a downloadable Excel spreadsheet containing all of the tables as a service to our readers.

The United States continues to be mired in a longstanding and growing opioid epidemic born out of the pain management industry, dating to the 1990s. Several states across the country have sustained considerable losses in both life and livelihood, which continue to mount as the epidemic has continued to yield casualties. The losses measured in this study include the direct costs, indirect costs, and estimates of loss of life and opportunity. Each region of the country has been affected, but the epidemic has produced among the most severe outcomes in Indiana.

Our study presents a comprehensive estimate of the total damages experienced in the state of Indiana to date, as well as insights about additional damages reasonably expected in the future. Key findings include estimates of:

* Direct costs (losses associated with products and services required to combat the epidemic).

* Indirect costs (losses to gross state product resulting from lost work productivity) to the citizens of Indiana.

* A methodological structure that could be used to calculate total losses in other states, counties and metro areas around the nation.

Key findings

Indiana has sustained $43.3 billion in economic damages to date arising from opioid misuse, comprised of three distinct areas of loss:

* Damages accruing from GSP opportunity costs driven by reductions in labor supply.

* Damages accruing from direct products and services expended to combat the crisis each year for each misuser.

* Damages accruing from economic contributions lost through opioid-related deaths.

A fourth area of loss is the portfolio of expenditures necessary to repair damages. This category, which will likely include investments from federal, state and local governments, as well as private industry and nonprofit organizations, is not included in the present study.

Ongoing economic damages for calendar-year 2018 are expected to eclipse $4 billion in Indiana, with damages continuing to derive from misuse rates, overdose rates, emergency response consumption and labor market tightness.

Figure 1 presents the comprehensive damages to Indiana, from the beginning of the epidemic in 2003 through the end of 2017 (full details are found later in Table 19).

Figure 1: Annual economic damages stemming from Indiana's opioid epidemic (in billions of 2017 dollars) 2003 0.3 2004 0.5 2005 0.6 2006 0.9 2007 1.2 2008 1.4 2009 1.2 2010 1.2 2011 1.4 2012 1.5 2013 1.6 2014 1.8 2015 3.0 2016 3.8 2017 4.3 Total present value of historical damages $24,388,140,627 + Total present value of future losses from past decendents $18,920,951,684 Total econimic damages accured through December 31, 2017, arising from opioid misuse in Indiana $43,309,092,311 Note: Full details are available in Table 19. Source: Authors' calculations Note: Table made from bar graph. Losses to gross state product via labor market conditions

Opioid addiction can hinder or utterly prevent misusers from finding employment or participating in the labor market. In times when the labor market is tight and it is difficult for employers to find workers, any people absent from the workforce can constrain productive output if there is a shortage of workers. Hindered productivity leads to reduced gross state product (GSP). (1) Of course, in situations wherein employers may easily find willing employees, people incapable of participating in the workforce place less of a strain on the economy. Thus, while opioid misuse often prevents users from participating in the labor force, the extent to which this affects GSP will vary based on the tightness of the labor market. In this section, we estimated the impact of opioid misuse on GSP by the following steps:

  1. We calculated the "lost wages" of opioid misusers in Indiana, by estimating the hypothetical additional wages that opioid misusers could have earned had they participated in the labor market at rates equal to the rates of the overall state.

  2. Before estimating the effect of lost wages on GSP, we adjusted the lost wages according to the tightness of the labor market: In an economic environment where labor is scarce, every lost worker translates to lost GSP, whereas when labor is plentiful, lost workers are easy to replace and likely have a small (if any) impact on GSP.

  3. We converted the adjusted lost wages to GSP losses by applying a ratio reflecting the extent to which wages convert to gross productive output for the state.

    Step 1: Calculating the lost wages of opioid misusers

    To calculate lost wages, we first estimated the number of opioid misusers in Indiana. We relied on the Substance Abuse and Mental Health Services Administration's (SAMHSA) national survey results on the prevalence of opioid misuse by educational attainment for years 2009-2016; in particular, we used the prevalence of opioid misuse in the last month as a proxy for current opioid misusers (as opposed to using the prevalence rate of opioid misuse over the past year or across one's lifetime). (2) We rehed on national estimates rather than state-specific estimates for three reasons:

  4. At the state level, SAMHSA only reports prevalence rates of misuse over the past year, whereas misuse over the past month is a more meaningful means of estimating the number of current (and habitual) opioid misusers.

  5. A breakdown of opioid misuse by educational attainment is only available at the national level.

  6. A breakdown of opioid misuse by employment status--important for our calculation of lost wages--is also only available at the national level. In years 2009-2016, we used opioid misuse prevalence rates by educational attainment level, then applied these rates to the 18+ Indiana population in that year, segmented by educational attainment. Thus, we estimated the number of opioid misusers in Indiana each year by educational attainment (less than high school, high school graduate, some college/associate degree, and bachelor's degree or higher). We calculated the "total hypothetical wages" of this entire group of individuals, assuming all were employed and earning wages commensurate with their educational attainment. We collected median wages by educational attainment for each year from the U.S. Bureau of Labor Statistics' wage data. (3)

    In years 2003-2008, SAMHSA survey results were not available. To estimate the prevalence rate of opioid misuse in Indiana for those years, we first imputed a national overall opioid misuse rate by applying a ratio from years 2009-2016 of opioid misuse rates to overdose deaths due to opioids; and then we adjusted this number by the average ratio of Indiana's opioid misuse ratio implied by the educational strata applied for years 2009-2016 to the overall national opioid misuse rate in years 2009-2016. For these years where opioid misuse rates were imputed, we used an overall average rather than segmenting misuse rates by educational attainment. Correspondingly, when calculating total hypothetical wages, we used median wages (rather than wages stratified by educational attainment), then adjusted this wage by the ratio of Indiana misuser wages implied by the educational strata applied for years 2009-2016 to overall median wages in years 20092016. Accordingly, we applied median wages for the entire population, rather than by educational attainment strata, when calculating total hypothetical wages. Table 1 details the calculations behind the total hypothetical wages calculation.

    The next step in our GSP analysis was to estimate "lost wages" due to opioid misuse among working-age adults. While many working-age opioid misusers have been employed, many more have been either unemployed or out of the labor force. In our estimates of lost wages, workers unemployed due to opioids and workers out of the labor force due to opioids were relevant. To look at both groups, we estimated a "working-age nonemployment rate" for both the general Indiana population and the group of Indiana opioid misusers separately. We then estimated marginal working-age nonemployment due to opioid misuse by calculating the difference in the statewide working-age nonemployment rate and the opioid misuser nonemployment rate. We calculated the statewide working-age nonemployment rate as follows:

    [mathematical expression not reproducible]

    Working-age people out of the labor force is equal to the 16+ population out of the labor force (calculated as 16-1- population minus unemployed minus employed) minus the population 66+. We excluded all individuals over 65, as this is a standard retirement age, and thus individuals over this age cannot be considered part of the potential labor pool. Similarly, the total working-age population is the Indiana population of 16 to 65 year olds. Thus, the working-age nonemployment rate is essentially a labor force participation rate adjusted to remove the retirement-age population. As shown in Table 2, Indiana's working-age nonemployment rate decreased from 33.4 percent in 2010 to 26.4 percent in 2016.

    We mirrored this calculation for opioid misusers by using SAMHSA's estimates of opioid misusers by employment status, adjusted to reflect the severity of the Indiana opioid crisis. Specifically, first, we calculated the ratio of (unemployed misusers + misusers out of labor force) to the total number of misusers. Between 2009 and 2016, the ratio ranged from 31.0 percent in 2012 to 42.5 percent in 2016. As previously discussed, SAMHSA data was not available prior to 2009. We estimated this ratio in years 2003-2008 by the average ratio of national opioid misuser nonemployment to statewide nonemployment in years 2009-2016 (1.161). We adjusted these annual figures by the corresponding annual ratios of the Indiana drug overdose death rates to the U.S. drug overdose death rates as published by the Centers for Disease Control and


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