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The IBR is a publication of the Indiana Business Research Center at IU's Kelley School of Business

Cumulative economic damages from 15 years of opioid misuse throughout Indiana

Associate Professor of Finance, Indiana University Division of Business, Indiana University–Purdue University Columbus

Doctoral Candidate in Finance, Kelley School of Business, Indiana University Bloomington

editors note

Download tables 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)

graph

Note: Full details are available in Table 19.
Source: Authors’ calculations

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 relied on national estimates rather than state-specific estimates for three reasons:

  1. 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.
  2. A breakdown of opioid misuse by educational attainment is only available at the national level.
  3. 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 2009-2016. 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.

Table 1: Total hypothetical wages of adult opioid misusers

Misuse rates by education
2003 2004 2005 2006 2007 2008
Imputed national rate 0.69 0.86 1.00 1.16 1.33 1.49
Indiana ratio adjustment 1.04 1.04 1.04 1.04 1.04 1.04
Imputed Indiana rate, overall 0.72 0.90 1.04 1.21 1.39 1.55
2009 2010 2011 2012 2013 2014 2015 2016
Less than high school graduate 1.8 2.0 2.6 2.2 2.5 2.7 1.9 1.5
High school graduate (or equivalent) 2.4 2.1 2.0 2.0 1.9 1.6 1.9 1.7
Some college or an associate degree 4.0 3.9 1.8 2.0 1.9 1.9 1.7 1.5
College graduate 1.8 1.4 0.9 1.3 1.0 0.9 0.8 1.0

Indiana population by education
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Less than high school graduate n/a n/a n/a n/a n/a n/a 682,271 680,161 666,913 650,335 649,449 617,723 622,048 617,140
High school graduate (or equivalent) n/a n/a n/a n/a n/a n/a 1,686,220 1,722,413 1,715,928 1,707,814 1,689,178 1,699,413 1,708,182 1,685,045
Some college or an associate degree n/a n/a n/a n/a n/a n/a 1,472,206 1,476,895 1,509,188 1,528,021 1,559,263 1,571,706 1,558,172 1,563,452
College graduate n/a n/a n/a n/a n/a n/a 1,000,453 1,009,922 1,031,892 1,057,467 1,085,469 1,128,681 1,151,544 1,189,883
Total 4,615,961 4,642,277 4,491,899 4,729,189 4,758,364 4,793,040 4,841,149 4,889,391 4,923,920 4,943,636 4,983,360 5,017,524 5,039,946 5,055,520

Weekly wages by educational attainment
2003 2004 2005 2006 2007 2008
National median wages 662 683 696 718 738 761
Indiana ratio adjustment 0.89 0.89 0.89 0.89 0.89 0.89
Imputed Indiana wage, overall 587.83 606.48 618.02 637.56 655.32 675.74

2009 2010 2011 2012 2013 2014 2015 2016
Less than high school graduate 454 444 451 471 472 488 493 504
High school graduate (or equivalent) 626 626 638 652 651 668 678 692
Some college or an associate degree 726 734 739 749 748 761 762 779
College graduate 1,137 1,144 1,150 1,165 1,194 1,193 1,230 1,259

Indiana total hypothetical wages of opioid misusers (annual)
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Less than high school graduate n/a n/a n/a n/a n/a n/a 289,926,816 314,070,973 406,651,326 350,416,004 398,501,683 423,234,359 302,989,628 242,610,077
High school graduate (or equivalent) n/a n/a n/a n/a n/a n/a 1,317,355,668 1,177,427,898 1,138,552,280 1,158,034,337 1,086,459,302 944,493,033 1,144,249,627 1,030,789,208
Some college or an associate degree n/a n/a n/a n/a n/a n/a 2,223,149,386 2,198,434,559 1,043,911,483 1,190,267,160 1,152,333,107 1,181,715,666 1,049,597,125 949,984,704
College graduate n/a n/a n/a n/a n/a n/a 1,064,713,705 841,095,321 555,364,301 832,797,254 673,946,291 630,169,794 589,222,034 778,992,602
Total 1,009,498,951 1,311,656,283 1,507,857,023 1,900,654,053 2,251,373,631 2,613,779,413 4,895,145,575 4,531,028,752 3,144,479,390 3,531,514,755 3,311,240,384 3,179,612,852 3,086,058,414 3,002,376,591

Source: Authors’ calculations

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:

formula graphic.4, 5

Working-age people out of the labor force is equal to the 16+ population out of the labor force (calculated as 16+ 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.

Table 2: Annual nonemployment rates

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Labor force 3,190,517 3,166,706 3,204,515 3,235,472 3,190,005 3,231,255 3,200,147 3,175,542 3,174,345 3,159,528 3,188,622 3,226,755 3,265,106 3,328,368
Employed 3,016,338 2,999,931 3,033,858 3,067,537 3,046,716 3,047,474 2,857,771 2,847,011 2,886,110 2,897,939 2,943,870 3,036,490 3,110,813 3,177,242
Unemployed 174,179 166,775 170,657 167,935 143,289 183,781 342,376 328,531 288,235 261,589 244,752 190,265 154,293 151,126
Out of labor force 1,601,347 1,658,378 1,661,678 1,681,755 1,770,740 1,770,785 1,836,489 1,889,590 1,923,624 1,967,314 1,971,734 1,963,986 1,948,063 1,910,709
Population 16+ 4,791,864 4,825,084 4,866,193 4,917,227 4,960,745 5,002,040 5,036,636 5,065,132 5,097,969 5,126,842 5,160,356 5,190,741 5,213,169 5,239,077
Population 66+ 718,588 722,842 728,880 738,402 747,913 759,138 776,224 789,164 802,768 815,202 844,966 871,049 895,572 919,876
Population 16-65 4,073,276 4,102,242 4,137,313 4,178,825 4,212,832 4,242,902 4,260,412 4,275,968 4,295,201 4,311,640 4,315,390 4,319,692 4,317,597 4,319,201
Out of labor force, 16-65 882,759 935,536 932,798 943,353 1,022,827 1,011,647 1,060,265 1,100,426 1,120,856 1,152,112 1,126,768 1,092,937 1,052,491 990,833
Nonemployment rate 25.9% 26.9% 26.7% 26.6% 27.7% 28.2% 32.9% 33.4% 32.8% 32.8% 31.8% 29.7% 28.0% 26.4%

Source: Authors’ calculations using U.S. Census Bureau and U.S. Bureau of Labor Statistics data

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 Prevention (and republished elsewhere), in order to reflect the relative severity of opioid misuse in Indiana. We made this adjustment using drug overdose death rates rather than reported opioid-specific overdose death rates because of historical underreporting of opioid deaths, which is discussed in a later section.

We then multiplied total hypothetical wages by the marginal nonemployment rate of opioid misusers—that is, opioid misuser nonemployment minus statewide nonemployment—to calculate the wages that could hypothetically have been earned by opioid misusers who were not employed, yielding “lost wages.” In the one year (2003) where estimated opioid misuser nonemployment was lower than the Indiana state nonemployment rate, we let lost wages equal zero.

A note on retirement ages

The average retirement age in Indiana is 63 years old.6 In our analysis on GSP losses arising from lost workforce participation, we included all workforce and non-workforce participants through age 65, the traditional age of full retirement in the United States, yet the age of full benefits increases to 67 for those born after 1960, with additional incentives available to those who work until age 70.7 This is counterbalanced by excluding all non-workforce participants after age 65, although the rates of workforce participation are greater than zero among these citizens.

Step 2: Adjusting for labor market slack

Our goal in this step was to estimate how the negative effect of opioid misuse translates to GSP losses. Of course, loss of employment for anyone is tragic, and certainly that is true for opioid misusers and their dependents. However, depending on the amount of slack in a given labor market, reducing the numbers of working-age adult job seekers or workers disrupts the demand-supply balance in the labor markets, resulting in losses to economic output. The costs to GSP growth attenuation will be most severe when the economy is at full employment, while GSP opportunity costs subside as the labor market loosens. Full employment is, in theory, the maximum rate of employment an economy can sustain, given structural unemployment levels (naturally occurring and balanced unemployment rates due to frictions, such as switching jobs or being new to the workforce).8 Experts typically agree on an unemployment (U-3) range between approximately 4 and 6 percent for full (“structural” or “natural”) employment.9 The Organization for Economic Cooperation and Development (OECD) reports estimates of structural unemployment for the United States each year, up to 2015,10 and reports a historical average of around 5.1 percent (this number varies annually) with a standard error at 0.9 percent.11 We applied these estimates to bookend a baseline range of “full employment” (at the lower end) to “full slack” (at the higher end), and we used linear interpolation between the low and high bounds to factor in the GSP effect, depending on the unemployment rate for each year. Further, an adjustment, explained below, was made to this baseline range by removing opiate misusers from employment numbers.

Specifically, to begin, a labor market range has been constructed reflecting the vessel within which the opportunity cost to economic output would occur. This range is defined here by the natural unemployment rate less its standard error at the low end, ranging upward to the same natural unemployment rate plus its standard error at the higher end. Mechanically, first, we adjusted the natural (also, structural) unemployment rate range to reflect the attenuation of our labor markets arising from the opioid epidemic.

For instance, if the structural “full employment level” yields a 5.0 percent unemployment rate in a non-opioid epidemic environment, then employers would have 5.0 percent of job seekers plus workers, plus other non-employed potentials, to consider when filling positions. However, in the environment of the opioid epidemic, employers have not had the full 5.0 percent to consider for gainful employment because misusers have not always been available for gainful employment. Consequently, the structural unemployment rate would thus need to be adjusted upward by some amount to model the same numbers of viable candidates to fill vacancies. The procedure of adjusting the range each year to capture the loss of working-age participants follows, and is shown in Table 3:

  1. We considered the total number of unemployed and others out of the labor force, and divided this sum by the number of working people plus the total of unemployed and others out of the labor force. We calculated the value of this fraction.
  2. We subtracted the total number of opioid misusers from the numerator and from the denominator. Then, we recalculated the value of this fraction, which decreased.
  3. We multiplied the full (“structural” or “natural”) unemployment rate by the ratio of (a) to (b)—which is a ratio greater than 1.0—to estimate the natural unemployment rate in the presence of additional employment frictions due to opioid misuse. This yields an adjusted structural unemployment rate higher than the original structural unemployment rate.
  4. We subtracted the standard error of the opioid-adjusted structural unemployment estimate to derive the lower bound.
  5. We added the standard error of the opioid-adjusted structural unemployment estimate to derive the upper bound.
  6. Using the opioid-adjusted range of full employment levels, we modeled “capture rates” equal to one for any unemployment level at or below the lower bound of this range (when labor is very tight) and equal to zero at or above the upper bound (when labor is no longer tight). We modeled the capture rate for unemployment rates falling between the two bounds using a risk-triangular shape, as follows, and as depicted in Figure 2:
      1. When the unemployment rate for a given year was below the opioid-adjusted lower bound, the capture was 1.0 (meaning, 100 percent of the GSP effect was included in the estimate).
      2. When the unemployment rate for a given year was above the opioid-adjusted lower bound, but below the midpoint of the range, the capture rate was produced by linear interpolation, ranging from 1.0 (at low bound) to 0.75 (at midpoint of range).
      3. When the unemployment rate for a given year was above the opioid-adjusted midpoint, but below the upper bound of the range, the capture rate was produced by linear interpolation, ranging from 0.75 (at midpoint) to 0.0 (at upper bound of range).
    1. In years 2003-2008, SAMHSA survey data was not available, so adjusting the upper and lower bounds as outlined in steps a-f was not directly possible. For these years, we retrocasted the modifications to the upper and lower bounds based on the trend in the modified bounds from 2009-2016.

Table 3: Unemployment rate ranges subject to partial economic attenuation

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Unemployed 9,266,000 8,286,000 7,524,000 7,001,000 6,979,000 8,575,000 14,707,000 14,474,000 13,962,000 12,692,000 11,751,000 9,474,000 8,265,000 7,812,000
Out of labor force 78,250,629 80,428,633 81,302,584 82,102,688 83,143,097 84,555,600 86,708,041 89,064,315 91,765,477 92,409,306 93,986,648 96,367,834 97,383,351 97,777,014
Employed 137,790,000 139,174,000 141,714,000 144,353,000 146,063,000 145,737,000 140,009,000 139,141,000 139,384,000 142,391,000 143,999,000 146,267,000 148,806,000 151,164,000
Opioid Rx and heroin misusers n/a n/a n/a n/a n/a n/a 5,452,000 5,339,000 4,752,000 5,197,000 4,810,000 4,760,000 3,963,000 3,649,000
Unemployment rate (U-3) n/a n/a n/a n/a n/a n/a 9.5% 9.4% 9.1% 8.2% 7.5% 6.1% 5.3% 4.9%
STEP A - Total nonemployment n/a n/a n/a n/a n/a n/a 42.0% 42.7% 43.1% 42.5% 42.3% 42.0% 41.5% 41.1%
STEP B - Nonemployment without misusers n/a n/a n/a n/a n/a n/a 40.7% 41.4% 42.0% 41.2% 41.1% 40.8% 40.5% 40.2%
STEP C - Structural unemployment 5.3% 5.3% 5.3% 5.3% 5.3% 5.2% 5.2% 5.2% 5.1% 5.1% 5.0% 5.0% 4.9% 4.9%
STEP D - Adjusted floor 4.76% 4.71% 4.66% 4.61% 4.56% 4.52% 4.47% 4.43% 4.38% 4.35% 4.27% 4.22% 4.16% 4.16%
STEP E - Adjusted ceiling 6.55% 6.50% 6.46% 6.41% 6.36% 6.32% 6.27% 6.23% 6.18% 6.15% 6.07% 6.02% 5.96% 5.96%

Source: Authors’ calculations using data from U.S. Bureau of Labor statistics (employment statistics), Substance Abuse and Mental Health Services Administration (opioid users) and Organization for Economic Cooperation and Development (structural unemployment)

Figure 2: GSP capture rate

graph

Source: Authors’ calculations

Rationale for the triangular model of the capture rate

We lowered the capture rate at “full employment” from 100 percent to 75 percent for a given year to account for the additional slack measured by lack of wages inflation.12 We then modeled above the midpoint and below the midpoint using separate linear interpolations, resulting in the entire range forming a triangular distribution of capture rates. Over years 2003-2016, unemployment (U-3) and labor force participation rates have varied significantly, with two expansions and a severe recession. Of note, 2008-2010 saw unemployment rates rise to about 10 percent and labor force participation rates fall to about 60 percent. Of course, during these years (and years like them) with considerable slack in all or nearly all labor markets in Indiana, the capture rate would be zero, and the total GSP effect on the economy would be zero.

The economic recovery has been slow, without the inflationary effects many economists had predicted, nor have its full employment levels been met with the wage increases anticipated in an economic recovery. Nonetheless, wages are now rising, and Indiana has been at or better than full employment for going on three years, so much of the effect of lost opportunity would be felt, with the near future positioned to feel the full effects of economic damage from opioid misuse in the economy. This is seen with high capture rates in more recent years, as well as in forecasted years.

Step 3:  Converting adjusted lost wages to GSP losses

Finally, we converted the adjusted lost wages to GSP losses by applying the ratio of GSP to total state wages each year. The GSP-wages ratio ranges from a low of 2.39 in 2003 to a high of 2.65 in 2010, with a 2016 multiplier of 2.57. The final effect each year is computed as “lost wages x capture rate x GSP multiplier.” The total GSP effects calculated for each year are in Table 4.

Table 4: GSP losses arising from opioid misuse during labor shortages

Potential wages of opioid users State nonemp. rate Opioid users nonemp. rate Lost wages State unemp. rate Capture rate Multiplier Lost GSP
2003 $1,009,498,951 25.9% 24.0% $0 5.46% 80.38% 2.39 $0
2004 1,311,656,283 26.9% 29.2% 30,593,111 5.27% 84.40% 2.41 62,346,406
2005 1,507,857,023 26.7% 30.0% 50,839,988 5.33% 81.43% 2.41 99,681,226
2006 1,900,654,053 26.6% 31.7% 96,633,644 5.19% 83.87% 2.43 196,647,432
2007 2,251,373,631 27.7% 33.5% 130,667,353 4.49% 100.00% 2.48 323,749,108
2008 2,613,779,413 28.2% 36.3% 211,885,527 5.69% 52.38% 2.48 275,205,850
2009 4,895,145,575 32.9% 45.0% 589,142,073 10.70% 0.00% 2.53 0
2010 4,531,028,752 33.4% 39.5% 277,651,426 10.35% 0.00% 2.65 0
2011 3,144,479,390 32.8% 38.4% 175,870,024 9.08% 0.00% 2.63 0
2012 3,531,514,755 32.8% 37.9% 178,969,177 8.28% 0.00% 2.59 0
2013 3,311,240,384 31.8% 45.0% 437,387,085 7.68% 0.00% 2.62 0
2014 3,179,612,852 29.7% 41.5% 375,852,701 5.90% 9.94% 2.64 98,636,380
2015 3,086,058,414 28.0% 41.7% 425,497,552 4.73% 84.38% 2.58 926,801,738
2016 3,002,376,591 26.4% 51.5% 751,835,254 4.54% 89.41% 2.57 1,725,768,439

Source: Authors’ calculations

Direct costs associated with provision of products and services combating the epidemic

In this section of the study, we routinely refer to numbers of deaths attributable to opioid overdoses each year. The numbers reported up the chain by emergency responders are ultimately classified as death by heroin overdose, prescription opioid overdose or other drug overdose. The percentage of deaths attributed to overdose of “other drugs” dropped from 68 percent in 2003 to 59 percent in 2016, suggesting the reporting of specific drugs has improved over time. However, in 2003, 291 overdose deaths were attributable to “other drugs,” while that nominal number increased to 900 by 2016. Since these numbers are more than half of all drug overdose deaths in Indiana, we estimate that deaths attributed to opioid overdoses in Indiana have been consistently underreported. As such, we have made adjustments (explained in the section below) to account for the improved cause of death data over time to better reflect the cost of the epidemic.

Costs of funerals from opioid overdose deaths

The average 2012 funeral cost in Indiana was $7,045, while a “low-cost” cremation with a funeral cost between $1,500 and $4,000.13 Given these numbers, we estimated the funeral cost for the average death to be $4,897.50, using an arithmetic average. We adjusted for inflation to estimate funeral costs for other years.14

How we accounted for opioid drug overdose estimates

We pulled annual (calendar year) drug overdose data from the Indiana State Department of Health (ISDH) that logged fatal heroin and other drug overdoses since 1999 to show the trend upward started prior to the discontinuous spike that occurred in 2003 (see Table 5).15

Table 5: Number of drug overdose deaths involving opioids and other drugs by death year, Indiana residents

  Total drug overdoses All opioids  Opioid pain relievers  Heroin  Other and unspecified narcotics  Cocaine  Benzodiazepines  Psychostimulants with abuse potential, excluding cocaine  Other and unspecified drugs 
1999 184 43 25 3 15 27 7 4 99
2000 203 36 24 3 9 14 3 2 136
2001 266 57 49 4 3 17 7 3 172
2002 281 56 43 0 14 27 10 3 195
2003 426 119 92 3 26 36 21 3 291
2004 537 134 98 7 32 54 18 6 384
2005 609 157 118 13 31 46 25 4 447
2006 728 170 135 9 34 53 31 11 535
2007 771 235 195 16 32 52 45 6 559
2008 818 304 214 56 47 49 60 9 569
2009 903 323 259 65 18 41 96 13 663
2010 923 283 229 54 19 42 88 19 642
2011 957 347 250 63 46 33 90 12 712
2012 999 361 206 110 57 36 94 15 699
2013 1,049 350 168 152 51 45 74 19 703
2014 1,152 452 250 170 61 47 84 38 792
2015 1,236 529 274 239 82 67 120 55 803
2016 1,518 785 488 296 92 111 191 120 900

Note: The “total drug overdoses” column does not equal the sum across all drug categories because many deaths are traced to multiple drugs. The same is true for the “all opioids” column. Drug overdose deaths attributable to opioids are underreported by a large amount each year, which is discussed in the following section.
Source: Indiana State Department of Health

The opioid crisis accelerated by 100 percent in one year: 2003

Total drug overdose deaths increased from 281 deaths in 2002 to 426 deaths in 2003, or a one-year increase of 51.6 percent. Additionally, the “all opioids” overdose category increased from 56 deaths in 2002 to 119 in 2003, rising 112.5 percent. We estimated that many of the deaths due to “other and unspecified drugs” were attributable to opioids as well. Thus, we marked 2003 as the beginning of the epidemic in terms of economic damages for this analysis because of the dramatic increase in opioid overdose deaths in 2003, which continued to increase insidiously forward to the current unprecedented death rates. It would not have been unreasonable to have marked an earlier year as the beginning of the epidemic, because drug overdose deaths per year began rising (although not by such large amounts) a few years prior. However, we estimated 2003 as the start of the epidemic due to the precipitous spike in deaths attributable to opioid overdoses in Indiana.

In 2003, as seen in Table 5 above, the Indiana State Department of Health (ISDH) attributed 119 of the 426 total drug overdoses to opioids, or 27.9 percent. Given what we now know about the epidemic, and given that widespread use of opioids began in the mid-1990s, we now believe a large proportion of unspecified drug overdose deaths in 2003 (and throughout the historical record) arose from opioid overdoses.16 However, while we inferred the rate of opioid overdose was greater than 27.9 percent in 2003, we cannot be sure of the precise rate. Our estimate is discussed in detail below.

We can see that the number of deaths by opioid overdose was high in 2003, when it was reported to have increased by more than 112 percent from 2002 levels. From that point in time, the numbers of opioid overdose deaths accelerated into the crisis that hit national media outlets a few years ago.17 Further evidence suggests that opioid misuse in Indiana was widespread by 2009, with 110,806 total opioid misusers that year, according to national reports.18

The Philadelphia Inquirer reported that 53,000 people died from opioid overdoses out of 64,070 total drug-related overdose deaths across the United States, based on findings from the Centers for Disease Control and Prevention (CDC).19 The CDC reported 1,566 total drug-related overdose deaths in Indiana in 2016 (measured January 31, 2016, to January 31, 2017).20 Adding up all CDC categories of drugs associated with death results in 71,614 drugs associated with overdose deaths, or 1.1178 drugs listed per death. There were 53,332 total opioid drugs listed with overdose deaths. Adjusting for multiple opioids listed for each death, the total adjusted number of deaths due to opioid overdose is estimated at 47,712, or 74.5 percent of all drug overdoses. The previously cited Philadelphia Inquirer/CDC report pegged 82.7 percent of all drug overdoses in the U.S. in 2016 as attributable to opioids. Consequently, we considered this proportion range (74.5-82.7 percent) as a gauge to properly estimate the specification of opioid overdose deaths in Indiana each year, including attribution of opioid overdoses within the category the ISDH calls “other and unspecified drugs.” This calculation was necessary to capture the full effect of the epidemic, as several hundred drug poisoning deaths each year fell into this category (refer back to Table 5 for details).

For years 2003 through 2016, we estimated total opioid overdose deaths by adding the total reported annual opioid overdose death numbers (from ISDH) to an annually calculated percentage of the “other and unspecified drugs” drug overdose deaths (see Figure 3).

Figure 3: Annual opioid overdose deaths in Indiana

graph

Source: Authors’ calculations

Using the overdose death data from the ISDH each year, drugs attributed to drug poisoning deaths were grouped by drug type of the known and reported cause, to allocate the percentage within the unspecified category, to opioid overdose death. For instance, in 2003, we summed “opioid pain relievers,” “heroin” and “other and unspecified narcotics” to proxy total opioids. We then divided this sum by the sum of all known drugs involved in drug poisonings in 2003, which included (again) “opioid pain relievers,” “heroin,” “other and unspecified narcotics,” along with “cocaine,” “benzodiazepines” and “psychostimulants with abuse potential excluding cocaine.” The resultant fraction, which was 66.9 percent in 2003, provided us with a basis for attributing additional—yet not specifically reported—annual deaths by opioid poisoning, from within the “other and unspecified drugs” category. Each year throughout the crisis period (2003-2016), we calculated this ratio and added the resultant proportion of “other” deaths to the deaths reported as opioid related to estimate annual totals. The average percentage of “other and unspecified drugs” resulting in overdose deaths in Indiana throughout the period was 69.6 percent, ranging from a low of 63.7 percent in 2004 to a high of 74.0 percent in 2014. 

This adjustment resulted in a crisis-period (2003-2016) average of 82.5 percent of total drug overdoses attributable to opioid overdose deaths, which is close to the 82.7 percent number previously published by the Centers for Disease Control and Prevention. The high through the historical period was 91.7 percent (in 2016) and the low was 70.5 percent (in 2004).

Following this procedure, we calculated the numbers of deaths in Indiana due to opioid overdoses for the entire crisis period, as shown in Table 6, along with average Indiana funeral costs. The product of the estimated opioid overdoses and funeral cost per overdose death (which had been adjusted for inflation) yields the total funeral costs attributable to opioid overdoses each year.

Table 6: Deaths due to opioid overdoses with estimated funeral costs

  2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Reported opioid overdose deaths 119 134 157 170 235 304 323 283 347 361 350 452 529 785
Reported overdose deaths by "other drugs" 291 384 447 535 559 569 663 642 712 699 703 792 803 900
Estimated number of opioid overdose deaths 314 379 463 519 628 719 784 713 864 864 862 1,038 1,100 1,392
Expected funeral cost per overdose death $3,928 $4,034 $4,171 $4,305 $4,425 $4,593 $4,575 $4,648 $4,797 $4,898 $4,971 $5,050 $5,056 $5,121
U.S. inflation rate 2.3% 2.7% 3.4% 3.2% 2.8% 3.8% -0.4% 1.6% 3.2% 2.1% 1.5% 1.6% 0.1% 1.3%
Total opioid overdose death funeral costs $1,231,522 $1,527,591 $1,929,297 $2,233,309 $2,777,131 $3,300,910 $3,586,056 $3,313,572 $4,146,447 $4,233,076 $4,286,972 $5,242,821 $5,560,246 $7,130,837

Source: Authors’ calculations

Initial emergency response costs

In this section, we considered the following categories of emergency response costs: naloxone use, costs of wages to first responders and ambulance costs.

Statistics on naloxone usage by emergency services are not widely available, but are available for Marion County for years 2011-2015.21 To estimate naloxone usage statewide, we took the ratio of naloxone use to opioid deaths in Marion County and applied this ratio to the state (see Figure 4). Since Marion County data were only available for a portion of the crisis range, to estimate statewide numbers for all years, we used the 2011 Marion County ratio for years 2003-2010 and we used the Marion County 2015 ratio to estimate 2016.

Figure 4: Estimated annual naloxone use events

graph

Source: Authors’ calculations

We then multiplied the number of naloxone use events by the cost per naloxone kit to derive the total cost of naloxone in emergency events in Indiana. The cost per naloxone kit is approximately $30.22 We adjusted this number for inflation in years prior to 2016. The cost of emergency responders was estimated at $465 in 2016 (including nine responders paid an average of $35/hour plus $150/hour for ambulance use for one hour).23 This figure, too, was adjusted for inflation each year. See Table 7 for annual initial emergency response costs.

Table 7: Annual initial emergency response costs due to opioid overdoses

Naloxone use events Cost of naloxone kit Total cost of naloxone Cost of emergency responders per call Total cost of emergency responders Initial emergency response costs
2003 1,368 $22.90 $31,333 $354.96 $485,659 $516,992
2004 1,653 23.65 39,076 366.52 605,675 644,751
2005 2,018 24.45 49,359 379.04 765,063 814,422
2006 2,264 25.08 56,772 388.67 879,961 936,733
2007 2,739 26.09 71,464 404.46 1,107,684 1,179,148
2008 3,136 26.12 81,921 404.9 1,269,777 1,351,698
2009 3,421 26.83 91,787 415.92 1,422,695 1,514,482
2010 3,111 27.23 84,725 422.14 1,313,244 1,397,969
2011 3,772 28.04 105,777 434.65 1,639,548 1,745,325
2012 3,122 28.53 89,073 442.21 1,380,639 1,469,712
2013 3,671 28.96 106,303 448.85 1,647,691 1,753,993
2014 6,582 29.18 192,057 452.25 2,976,876 3,168,932
2015 6,801 29.39 199,889 455.55 3,098,281 3,298,170
2016 8,610 30.00 258,312 465.00 4,003,830 4,262,142

Source: Authors’ calculations

Acute hospitalization costs

An important distinction should be highlighted differentiating the types of requisite treatment in opioid care. Broadly, treatment requires urgent (also called “acute”) care and long-term rehabilitation. This section discusses urgent care costs, but does not address long-term drug rehabilitation costs—which are detailed in another section of this study.

According to the Indiana State Department of Health, Indiana saw total non-fatal visits to emergency rooms (ER visits) from acute opioid overdoses rise from 1,856 in 2011 to 2,977 in 2015, and then jump dramatically in 2016 to 8,297 ER visits.24, 25 ISDH tracked these numbers from 2009 through 2016. Prior to 2009, no state-level data exist on acute treatment from opioid overdoses. We estimated ER visits in Indiana from 2003 through 2008 using linear retrocasting, considering the ratio of ER visits to deaths each year for the years where both data sets were available (2009-2016).

However, a second authoritative source, the Healthcare Cost and Utilization Project (HCUP), sponsored by the federal Agency for Healthcare Research and Quality suggests the ISDH numbers are significantly too low.26 Thus, we considered both sources of information. One reason is that some hospitalizations may have occurred without initial emergency room visits, which HCUP captured, and some emergency room visits resulted in “treat and release” of opioid patients, which ISDH captured. Further, HCUP numbers likely reflect hospital visits that occurred due to complications from opioid misuses, otherwise primarily coded for non-opioid medical conditions, yet such conditions would not have materialized but for opioid misuses.

We noticed that the ratio of ER visits per year for opioid overdose has been trending upward, suggesting emergency management authorities throughout the state have become more aware of the opioid crisis as it has continued to escalate. To determine ER visits in the past, we calculated a linear trend line and estimated ER visits in this way. We excluded the 2016 figure from the backward-looking trend line number since the shift upward in 2016 was clearly nonlinear.

Acute, or urgent, hospitalization costs for short-term inpatient treatment of opioid misuse can result in three distinct outcomes:

  1. Treatment for a few hours and release.
  2. Admission into an acute care center (hospital) for treatment in a non-intensive care unit setting.
  3. Admission into an intensive care unit (ICU) within a hospital setting.

According to a news release in 2014 from Modern Medicine Network, 41 percent of U.S. opioid overdose patients who visited emergency rooms were treated and released, 55 percent were admitted to the hospital for non-ICU treatment, and 4 percent were transferred to an intensive care unit (ICU).27 This same source reported that patients treated and released accumulated costs of $3,640 in 2014, while the admitted non-ICU patients averaged costs of $29,497 per patient, averaging 3.8 days per stay that year. These are national numbers, thus we made adjustments to consider expected costs in Indiana.

In Indiana, the average cost of an inpatient day at a hospital in 2015 was $2,352 per patient day in nonprofit hospitals and $2,108 per patient day in for-profit hospitals, yielding an average of $2,230 per patient day. Across the United States, the corresponding 2015 cost was $2,289 (nonprofit) and $1,791 (for-profit), or $2,040 per patient day on average.28 We took the ratio of Indiana/U.S. per patient day costs, which is 2230/2040, or 1.093. This suggests hospital costs in Indiana in 2015 were approximately 9 percent higher than the national average.

We estimated acute hospitalization costs for opioid overdose by discovering the cost per opioid admission into a hospital and multiplying this number by the numbers of acute hospital admissions per year due to opioid overdose, considering the previously cited published rates of treat and release (41 percent), admit and treat in a non-ICU facility (55 percent), or admit to ICU (4 percent) as a baseline. We adjusted this distribution of acute care outcomes for this study, based on conditions specific to Indiana. While the opioid emergency rates of admission to ICU nationwide is 4 percent, these costs in Indiana are more common because critical care density of opioid overdoses in Indiana (and Massachusetts) were double that of other states.29 To reflect the additional ICU density in Indiana, we applied an 8 percent ICU rate, with the 4 percent reduction split pro rata between treat and release (-1.7 percent) and admit to non-ICU care (-2.3 percent), as shown in Figure 5.

Figure 5: Estimated hospitalization outcomes for Indiana opioid overdose patients

graph

Source: Authors’ calculations

Treat and release

In 2014, the national average cost for “treat and release” care at an acute care facility was $3,640.30 In Indiana, the expected cost would be about 9 percent higher, or $3,979. Using the inflation rates as reported by the U.S. Bureau of Labor Statistics and by the U.S. Inflation Calculator,31 along with reports of urgent-care cases in Indiana, we calculated annual historical costs accordingly.

Admission into non-ICU

In 2014, the national average cost for “admit into non-ICU” care at an acute care facility was $29,497.32 In Indiana, the expected cost would be 9 percent higher, or $32,244. Using the aforementioned inflation rates, along with reports of urgent care cases in Indiana, we calculated annual historical costs accordingly.

Admission into ICU

In 2009, the national cost per admission into the ICU of a hospital due to overdose of opioids was $58,517, and this cost rose to $92,408 by 2015.33 We adjusted these numbers up by 9 percent to reflect the higher-than-average acute care costs seen in Indiana, to $63,967 and $101,015, respectively. ICU cost estimates from years 2010 through 2014 were calculated using linear interpolation, with the adjusted 2009 and 2015 numbers used as bookends. For annual historical cost estimates ranging back to 2003, we applied inflation rates to calculate those costs accordingly.

Total costs by acute care type

Annual historical costs per patient and identification of the costs for acute care in the opioid crisis according to each type of care received following an opioid overdose were ultimately calculated and visualized in Figure 6.34

Figure 6: Estimated hospitalization costs resulting from non-lethal opioid overdose ER visits

graph

Source: Authors’ calculations

The summary of complete costs per year for non-lethal acute care is provided in Table 8.

Table 8: Annual cost estimates for non-lethal acute care

Year Treat & release Admission (non-ICU) ICU Total ER visits  Treat & release total costs Admission (non-ICU) total costs ICU total costs Total annual acute care costs
2003 $3,095 $25,077 $54,921 249 $302,779 $3,290,173 $1,093,866 $4,686,817
2004 3,178 25,754 56,403 398 496,556 5,395,868 1,793,935 7,686,359
2005 3,286 26,629 58,321 550 710,697 7,722,850 2,567,574 11,001,121
2006 3,391 27,481 60,187 705 939,669 10,210,992 3,394,793 14,545,454
2007 3,486 28,251 61,873 948 1,299,161 14,117,438 4,693,548 20,110,146
2008 3,619 29,325 64,224 1,193 1,696,430 18,434,395 6,128,783 26,259,608
2009 3,604 29,207 63,967 1,460 2,068,047 22,472,609 7,471,346 32,012,001
2010 3,662 29,675 70,142 1,658 2,386,085 25,928,588 9,303,591 37,618,263
2011 3,779 30,624 76,316 1,856 2,756,506 29,953,806 11,331,449 44,041,761
2012 3,858 31,267 82,491 1,969 2,985,743 32,444,829 12,993,982 48,424,555
2013 3,916 31,736 88,666 2,157 3,319,884 36,075,800 15,300,147 54,695,831
2014 3,979 32,244 94,840 2,822 4,412,894 47,953,083 21,411,154 73,777,131
2015 3,983 32,276 101,015 2,977 4,659,930 50,637,521 24,057,732 79,355,184
2016 4,035 32,696 102,328 8,297 13,156,219 142,963,161 67,921,363 224,040,742

Source: Authors’ calculations

Additional hospitalizations

In the prior sections, we calculated hospitalization costs resulting from emergency room (ER) visits reported by ISDH. The Healthcare Cost and Utilization Project reported the rate of total opioid-related hospital stays for the state of Indiana in years 2008-2016.35 We calculated the cost of these additional hospital stays by the following:

  1. We calculated the number of Indiana opioid hospitalizations as suggested by HCUP’s rate by multiplying the rate by the Indiana population each year.
  2. From the above result, we subtracted the non-ICU and ICU admissions estimated in the prior section in order to estimate total additional hospitalizations not included in the ER-visit calculations.
  3. We multiplied the number of additional hospitalizations by an average hospitalization cost to arrive at a total cost for additional hospitalizations. The average hospitalization cost was estimated as a weighted average of the ICU and non-ICU hospitalization costs from the prior section, weighted by the number of estimated ER ICU and ER non-ICU hospitalizations each year.
  4. We estimated 2003-2007 additional hospitalizations by calculating the average ratio between HCUP and ISDH reports.

These calculations are detailed in Table 9.

Table 9: Cost of additional hospitalizations

HCUP reported rate per 100,000 population Indiana population HCUP total hospitalizations ISDH non-ICU ISDH ICU Weighted average of ICU & non-ICU costs Estimate of additional hospital admissions Cost estimate for additional hospital admissions
2003 n/a 6,196,638 1,426 131 20 $29,010 1,079 $31,299,754
2004 n/a 6,233,007 2,279 210 32 29,793 1,725 51,380,117
2005 n/a 6,278,616 3,149 290 44 30,806 2,383 73,416,765
2006 n/a 6,332,669 4,037 372 56 31,792 3,055 97,118,367
2007 n/a 6,379,599 5,428 500 76 32,682 4,108 134,249,818
2008 133 6,424,806 8,513 629 95 33,924 6,851 232,414,614
2009 149 6,459,325 9,624 769 117 33,788 7,591 256,474,696
2010 157 6,490,029 10,189 874 133 35,008 7,880 275,853,694
2011 177 6,515,358 11,548 978 148 36,646 8,963 328,461,753
2012 181 6,535,665 11,797 1,038 158 38,018 9,054 344,219,798
2013 193 6,567,484 12,642 1,137 173 39,239 9,638 378,176,610
2014 197 6,593,182 12,989 1,487 226 40,494 9,058 366,774,671
2015 225 6,610,596 14,841 1,569 238 41,336 10,694 442,037,014
2016 281 6,634,007 18,664 4,373 664 41,873 7,106 297,548,111

Source: Authors’ calculations

Treatment center costs: Outpatient and inpatient

To estimate outpatient treatment center costs, we took the product of treatment center admissions due to opioids and the average cost of opioid outpatient rehabilitation treatment. We retrieved data on treatment center admissions where the primary substance abused was heroin or other opioids from the Treatment Episode Data Set (TEDS).36, 37 We based costs per patient on the cost of one year of methadone treatment plus related services in 2016 and adjusted this number for inflation in other years.38

A representative of Aim (formerly known as the Indiana Association of Cities and Towns) stated in a public presentation that out of 300 opioid treatment centers in Indiana available to treat patients, 50 are inpatient facilities.39 While in the future, we expect to see more inpatient rehabilitation centers coming online in Indiana, for now the ratio is 5:1.40 One-sixth of the facilities were thus estimated to be inpatient, and we further estimated that inpatient facilities could only treat 50 percent of the patient load versus outpatient facilities. Historical treatment center admissions are plotted in Figure 7.

Figure 7: Indiana treatment center admissions

graph

Source: Substance Abuse and Mental Health Services Administration

To estimate inpatient costs, we relied upon the Addiction Center’s estimate stating costs are typically $6,000-$12,000 per patient for a 30-day program.41 We modeled costs at $9,000 per patient for a 30-day program, and we modeled one-twelfth the number of inpatients served per year. The $9,000 cost estimate was applied for 2016 calculations, while previous years’ costs were adjusted for inflation (see Table 10).

Table 10: Costs associated with treatment in Indiana

  Outpatient admissions Cost per outpatient Total outpatient treatment costs Inpatient admissions Cost per inpatient Total inpatient treatment costs Total rehabilitation costs
2003 1,781 $5,002 $8,907,756 148 $6,870 $1,019,661 $9,927,417
2004 2,361 5,164 12,193,091 197 7,094 1,395,729 13,588,821
2005 2,683 5,341 14,329,295 224 7,336 1,640,258 15,969,553
2006 2,903 5,476 15,898,174 242 7,523 1,819,846 17,718,020
2007 2,501 5,699 14,253,189 208 7,828 1,631,546 15,884,735
2008 2,397 5,705 13,675,325 200 7,837 1,565,399 15,240,724
2009 3,057 5,860 17,915,366 255 8,050 2,050,752 19,966,118
2010 3,920 5,948 23,316,538 327 8,170 2,669,018 25,985,555
2011 5,048 6,124 30,915,486 421 8,413 3,538,861 34,454,347
2012 5,164 6,231 32,176,520 430 8,559 3,683,210 35,859,729
2013 5,684 6,325 35,948,467 474 8,688 4,114,980 40,063,447
2014 6,236 6,372 39,737,949 520 8,753 4,548,758 44,286,707
2015 5,661 6,419 36,337,016 472 8,817 4,159,457 40,496,473
2016 4,955 6,552 32,465,160 413 9,000 3,716,250 36,181,410

Source: Authors’ calculations

Neonatal abstinence syndrome costs

When expectant mothers take opioids, their infants are often born with neonatal abstinence syndrome (NAS), which essentially describes opioid addiction in infants who experience withdrawal systems after losing access to the drugs via their mothers after birth. Hospital costs for these newborns have been significantly higher than for regular newborn births—the average hospital stay for an NAS newborn costs $66,000 versus $3,500 for a healthy baby.42 To estimate the aggregate marginal cost of NAS hospital stays, we took the marginal cost per live birth ($62,500 = $66,000 - $3,500 in 2016, and adjusted for inflation in other years) and multiplied by the number of NAS births in Indiana. To estimate the latter number, we multiplied the national rate of NAS births and multiplied by the number of Indiana births each year. The national rate of NAS births was 1.5 per 1,000 births in 1999, and rose to 6 per 1,000 births in 2013.43 We linearized this trend to estimate the rate each year between 2003 and 2016, then multiplied by the number of births in Indiana each year (see Table 11).44

Table 11: Neonatal abstinence syndrome rates and cost estimates

  NAS rate per 1,000 births Total Indiana births NAS births in Indiana Marginal cost for NAS birth Total marginal costs for NAS births
2003 2.8 86,382 241 $47,710 $11,480,752
2004 3.1 87,125 271 49,263 13,336,074
2005 3.4 87,088 299 50,946 15,211,842
2006 3.8 89,404 335 52,240 17,514,372
2007 4.1 89,719 365 54,363 19,858,010
2008 4.4 88,679 390 54,422 21,200,378
2009 4.7 86,126 406 55,903 22,697,946
2010 5.0 83,867 422 56,739 23,962,731
2011 5.4 83,750 449 58,420 26,210,838
2012 5.7 83,250 473 59,437 28,098,446
2013 6.0 83,115 499 60,330 30,085,906
2014 6.3 83,927 531 60,786 32,249,457
2015 6.6 84,008 558 61,230 34,169,435
2016 7.0 83,063 578 62,500 36,154,654

Source: Authors’ calculations

A note on opioid misuse as a percentage of total drug misuse

We relied heavily upon SAMHSA for national drug consumption data from 2009-2016. We used such data to attribute drug misuse classifications across educational attainment strata and to better understand levels of misuse annually. However, while opioid drug misuse severity numbers—visits to emergency rooms and opioid overdose deaths—have been increasing, SAMHSA has reported misuse rates of opioids as declining as a fraction of total drug misuse in recent years. Based upon evidence presented throughout this report, we believe the state's opioid misuse numbers have not been declining in recent years. Rather, we believe the opioid misuse rates in Indiana have been increasing.

For calculations performed in several of the following sections, we required an estimate of opioid misuse as a proportion of overall drug misuse (“opioid misuse ratio”). To derive this ratio, we relied upon two primary sources: 1) We calculated the opioid misuse ratio suggested by SAMHSA’s estimates of the number of illicit drug users by drug category. However, as discussed in the previous paragraph, tracking this number over time would suggest a declining opioid misuse ratio, which seems inconsistent with multiple other data sources discussed in this report supporting increased opioid usage over the crisis years. Consequently, we used the opioid misuse ratio suggested by SAMHSA’s 2009 survey (24.99 percent) in concert with 2) our calculated ratio of Indiana opioid overdose deaths as a proportion of total overdose deaths each year from 2003-2016. (Those calculations are discussed in the “costs of funerals” section of this report.)

We estimated the opioid misuse ratio each year as the average of SAMHSA’s 2009 figure (24.99 percent) and the annual opioid overdose ratio each year for all years, 2009-2016. In years 2003-2008, we modeled a linear trend beginning with 25.90 percent in 2003, adding 500 basis points each year to arrive at the estimate of 55.90 percent in 2009.

Foster care costs

To estimate the foster care costs accruing to the state of Indiana due to opioid abuse, we first obtained the number of children in foster care45 and estimated the number of children in the foster care system due to opioid abuse (see Figure 8), then multiplied by the annual cost of foster care per child.

Figure 8: Number of children in Indiana foster care

graph

Source: Kids Count Data Center and authors’ calculations

NBC reported a six-fold increase in drug-related foster care cases from 2000 to 2015, and that approximately 50 percent of cases in Marion County were drug-related in 2015.46 Assuming a similar proportion statewide, this implies 8,512 drug-related cases in 2015 and 1,419 drug-related cases in 2000; we linearized the trend in order to impute the number each year from 2003-2016. We then adjusted this number to reflect opioids (rather than all drug causes) by taking the ratio of opioid misuse to total drug misuse.47 (We deemphasized marijuana use from the drug-misuse figures because of increasing acceptance of marijuana use nationwide and an associated lower probability of drug-related social costs due to its use.) We then obtained 2016-2017 foster care costs per day from the Indiana Department of Child Services,48 adjusted these rates for inflation in prior years, annualized and multiplied by the number of opioid-attributed cases each year to arrive at an annual cost figure (see Table 12).

Table 12: Estimated annual costs of foster care due to opioid misuse

Year Children in foster care Children in foster care due to parental drug misuse Opioid use/drug use ratio Children in foster care due to parental opioid misuse Cost per day Annual cost
2003 8,815 2,837 25.9% 735 $24.43 $6,552,584
2004 9,778 3,310 30.9% 1,023 25.23 9,417,378
2005 11,243 3,783 35.9% 1,358 26.09 12,931,329
2006 11,384 4,256 40.9% 1,741 26.75 16,994,945
2007 11,372 4,729 45.9% 2,170 27.84 22,052,819
2008 12,386 5,201 50.9% 2,648 27.87 26,929,770
2009 12,437 5,674 55.9% 3,172 28.63 33,141,751
2010 12,276 6,147 51.1% 3,142 29.05 33,321,391
2011 10,779 6,620 57.7% 3,817 29.91 41,678,328
2012 11,334 7,093 55.8% 3,955 30.44 43,933,116
2013 12,382 7,566 53.6% 4,055 30.89 45,728,170
2014 14,452 8,039 57.6% 4,626 31.13 52,560,766
2015 17,023 8,512 57.0% 4,851 31.35 55,509,178
2016 19,104 8,984 58.4% 5,243 32.00 61,247,789

Source: Authors’ calculations

Arrest and court costs

To estimate the cost of arrests arising due to opioid misuse, we took the product of drug-related arrests, the ratio of opioid misuse to total illicit drug use, and an estimate of cost per arrest plus court fees, to arrive at total opioid-related arrest costs in Indiana each year from 2003-2016. Drug-related arrests are based on Indiana arrest statistics published by the FBI. The number of drug-related arrests was calculated based on published attribution rates (i.e., 100 percent of drug-violation arrests are due to drug use, while 29.6 percent of larceny-theft arrests are attributed to drug use).49 In 2012, the drug-related arrest rate in Indiana was 578 per 100,000 people. Without further data on this statistic, we applied this rate across all years in the sample.

We then multiplied this rate (578 per 100,000) by the Indiana population each year to estimate the number of drug arrests; the result was multiplied by the ratio of opioid misuse to total illicit drug use to arrive at the number of arrests attributable to opioid misuse (see Figure 9). For years 2003-2008, when the ratio is not available from SAMHSA, we applied the 2009 rate.50

Figure 9: Indiana opioid-related arrests

graph

Source: Authors’ calculations

Cost per arrest was estimated at $437 per arrest in 2012, including $24 attributed to the dispatcher (two hours at $10/hour plus phone service costs), $143 for officer wages ($14.26/hour for five officers for two hours), $50 for gasoline (one tank), and $220 for jail boarding ($55/day for four days).51 We adjusted this number by inflation for other years. In 2017, Indiana court costs for criminal offenses were $185, which we also adjusted for inflation in prior years.52 The calculation results are shown in Table 13.

Table 13: Opioid-related annual arrests and costs

Indiana population  Opioid use/drug use ratio Indiana opioid arrests Cost per arrest Court cost per arrest Total drug arrest cost
2003 6,196,638 25.9% 9,277 $351 $139 $4,544,426
2004 6,233,007 30.9% 11,132 362 144 5,631,073
2005 6,278,616 35.9% 13,028 375 149 6,815,200
2006 6,332,669 40.9% 14,971 384 152 8,030,186
2007 6,379,599 45.9% 16,925 400 158 9,447,547
2008 6,424,806 50.9% 18,902 400 159 10,562,374
2009 6,459,325 55.9% 20,870 411 163 11,979,616
2010 6,490,029 51.1% 19,175 417 165 11,170,895
2011 6,515,358 57.7% 21,714 430 170 13,025,131
2012 6,535,665 55.8% 21,063 437 173 12,854,408
2013 6,567,484 53.6% 20,348 444 176 12,604,465
2014 6,593,182 57.6% 21,933 447 177 13,688,926
2015 6,610,596 57.0% 21,775 450 179 13,689,717
2016 6,634,007 58.4% 22,378 460 182 14,360,657

Note: Indiana's drug-related arrest rate was 578 per 100,000 people. Percentages include marijuana arrests, and the FBI provides no details about which drugs are involved in the arrests. SAMHSA numbers were used to estimate the percentage of opioid-related arrests.
Source: Authors’ calculations

Property losses

We estimated property losses resulting from the opioid epidemic by looking at the FBI annual crimes reports.53 Forbes reported that 2014 losses associated with theft, burglary and robberies in the U.S. totaled $14.3 billion, based on 8.2 million property crimes that year.54 These numbers suggest an average property loss cost of $1,742 per incident in 2014. Further, the FBI reported 29.6 percent of larceny-thefts have been drug related.55

Using these FBI statistics regarding interactions between drug abuse and property crimes, we estimated the total cost of property damage in Indiana each year attributable to opioid misuse. Specifically, we multiplied Indiana property crimes56 by the percentage of property crimes that are drug related (0.296), multiplied by the annual opioid misuse ratio (explicated in the earlier “note on opioid misuse” section), and then multiplied by the cost per property crime adjusted for inflation each year (see Table 14).

Table 14: Annual property damage costs

Year Indiana property crimes Percent drug related Opioid use/drug use ratio Cost per property crime Indiana opioid-related property damage costs
2003 208,034 29.6% 25.9% $1,367 $21,806,476
2004 211,929 29.6% 30.9% 1,412 27,366,055
2005 216,778 29.6% 35.9% 1,460 33,632,426
2006 221,127 29.6% 40.9% 1,497 40,078,260
2007 215,526 29.6% 45.9% 1,558 45,619,826
2008 212,715 29.6% 50.9% 1,560 49,983,643
2009 200,160 29.6% 55.9% 1,602 53,059,276
2010 197,260 29.6% 51.1% 1,626 48,529,815
2011 206,055 29.6% 57.7% 1,674 58,878,297
2012 198,032 29.6% 55.8% 1,703 55,670,606
2013 187,536 29.6% 53.6% 1,729 51,444,425
2014 174,776 29.6% 57.6% 1,742 51,866,195
2015 171,847 29.6% 57.0% 1,755 50,865,589
2016 171,759 29.6% 58.4% 1,791 53,143,010

Source: Authors’ calculations

Direct costs to newly diagnosed HIV patients from intravenous drug (opioids) use

Intravenous drug injection comes with the risk of acquiring blood-borne pathogens, including HIV. The Centers for Disease Control and Prevention (CDC) indicate that usage of intravenous drugs yielded new cases of HIV throughout the crisis period. We retrieved data on new HIV diagnoses for the state of Indiana from the ISDH for years 2004-2016, and estimated the figure for 2003 based on the trends over time.57, 58 We estimated the proportion of these new diagnoses due to opioid misuse based on attribution rates published by the CDC for the percentage of HIV cases due to intravenous drug use (IDU),59, 60 applying linear trends in years where the attribution rates were not available, in order to estimate the number of new Indiana HIV diagnoses attributable to opioids. Next, the expected lifetime cost per new HIV diagnosis for medication and services, as of 2006, was $618,000, spread across an average life expectancy of 24 years.61 We adjusted this number for inflation in other years.

The breakdown of the lifetime cost was stated as $25,750 per year (67 percent for medication and 33 percent for medical professional services) across an expected post-HIV diagnosis lifespan of 24 years. We discounted the 24-year annuity at the 10-year bond discount rate for each year to calculate the annual present value of the cost for new diagnoses.62 This number reflects the fact that newly diagnosed HIV patients are confronted with (a) taking expensive medications for the duration of their lives, or (b) yielding to the life-threatening nature of the disease. We did not model option (b). The spike in newly acquired HIV cases in 2015 resulted from the outbreak highlighted in Scott County that year.63 Results from this set of annual calculations are presented in Table 15.

Table 15: New HIV diagnoses cost calculations

New HIV diagnoses Percent attributable to opioid abuse Resultant HIV cases from IDU Lifetime cost per diagnosis Annual 10-year bond rate Annual present value of HIV costs
2003 400 14.3% 57 $567,509 4.05% $20,517,325
2004 427 14.3% 61 580,869 4.15% 22,190,661
2005 422 14.3% 60 596,988 4.22% 22,379,929
2006 539 14.3% 77 618,000 4.42% 29,000,742
2007 509 13.4% 68 635,304 4.76% 25,581,471
2008 483 12.6% 61 659,446 3.74% 26,146,684
2009 489 11.7% 57 656,808 2.52% 27,989,363
2010 514 10.9% 56 667,317 3.73% 24,332,433
2011 518 10.0% 52 688,671 3.39% 24,146,986
2012 518 9.5% 49 703,133 1.97% 27,361,396
2013 454 9.2% 42 713,680 1.91% 23,733,147
2014 515 9.0% 46 725,099 2.86% 24,077,294
2015 621 7.0% 221 725,824 1.88% 128,207,036
2016 507 5.0% 25 735,260 2.09% 14,540,230

Source: Authors’ calculations

Incarceration costs

To estimate incarceration costs, for each year, we took the product of average daily prison population, the proportion of controlled substance incarcerations, the opioid misuse ratio and annual cost per inmate. Because statistics on primary offenses are segmented by male/female and juvenile/adult, we calculated the costs for these four categories and then aggregated them. With the exception of the ratio of opioid misuse to total illicit drug use,64 we retrieved all data from the Indiana Department of Correction.65, 66

The estimates detailed in Table 16 are reflective only of direct drug arrests leading to imprisonments. Said otherwise, these numbers are not attributable to other crimes—such as property crimes, wherein opioid addicts were seeking economic means to secure more drugs. Those costs are not captured in these estimates.

Table 16: Annual incarceration costs

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Cost and population 
Adult per diem cost $55.43 $58.99 $57.69 $52.25 $52.61 $54.28 $53.96 $52.60 $50.73 $51.33 $52.20 $52.30 $51.43 $54.60
Adult avg. daily pop. 23,069 24,008 24,455 25,237 26,249 27,742 25,824 26,283 26,401 26,695 27,320 27,676 27,340 26,360
Juv. per diem cost $136.50 $173.26 $179.86 $148.50 $148.69 $160.93 $173.02 $159.98 $207.19 $215.68 $212.13 $249.63 $245.73 $249.08
Juv. avg. daily pop. 1,477 1,261 894 996 1,014 957 948 914 634 583 521 445 429 453
Adult annual prison cost $466,730,855 $516,924,651 $514,945,267 $481,301,136 $504,050,360 $549,630,052 $508,614,010 $504,607,317 $488,852,796 $500,142,838 $520,527,960 $528,321,002 $513,225,113 $525,328,440
Juv. annual prison cost $73,587,833 $79,745,514 $58,690,117 $53,985,690 $55,031,656 $56,213,654 $59,868,380 $53,370,928 $47,945,838 $45,895,626 $40,339,701 $40,546,153 $38,477,632 $41,184,133
Population breakdown by gender
% female, adults 7.6% 7.9% 7.7% 8.2% 8.3% 8.7% 8.7% 8.7% 8.6% 8.7% 9.1% 9.5% 9.3% 9.0%
% male, adults 92.4% 92.1% 92.3% 91.8% 91.7% 91.3% 91.3% 91.3% 91.4% 91.3% 90.9% 90.5% 90.7% 91.0%
% female, juv. 20.4% 17.8% 15.5% 15.2% 17.8% 12.9% 12.6% 11.5% 10.7% 9.1% 11.2% 10.5% 11.1% 10.9%
% male, juv. 79.6% 82.2% 84.5% 84.8% 82.2% 87.1% 87.4% 88.5% 89.3% 90.9% 88.8% 89.5% 88.9% 89.1%
Controlled substance (CS) offenses, by gender
% CS, adult female 29.8% 29.8% 30.0% 29.2% 30.3% 31.9% 32.7% 33.0% 36.0% 37.0% 37.5% 40.4% 41.1% 41.1%
% CS, adult male 22.8% 22.8% 23.0% 22.7% 22.6% 22.7% 22.9% 24.0% 25.0% 24.0% 24.4% 24.4% 23.4% 23.4%
% CS, juv. female 6.5% 6.5% 7.0% 5.9% 6.5% 2.4% 3.1% 5.0% 5.0% 2.0% 10.8% 9.5% 3.5% 3.5%
% CS, juv. male 6.5% 6.5% 7.4% 6.3% 5.9% 6.6% 7.2% 8.0% 8.0% 8.0% 12.1% 10.6% 7.0% 7.0%
Opioid use/drug use ratio 25.9% 30.9% 35.9% 40.9% 45.9% 50.9% 55.9% 51.1% 57.7% 55.8% 53.6% 57.6% 57.0% 58.4%
Cost calculations by gender and age group
Adult female opioid costs $2,748,322 $3,755,437 $4,272,645 $4,685,172 $5,816,740 $7,719,876 $8,032,486 $7,436,506 $8,731,270 $9,010,578 $9,526,573 $11,711,425 $11,213,088 $11,328,080
Adult male opioid costs $25,424,368 $33,499,910 $39,243,999 $41,043,813 $47,949,239 $58,059,087 $59,554,671 $56,495,640 $64,405,251 $61,082,927 $61,882,018 $67,118,123 $62,056,245 $65,290,525
Juv. female opioid costs $252,012 $283,065 $229,320 $197,505 $291,460 $89,732 $129,018 $156,562 $148,419 $46,527 $261,092 $232,538 $84,890 $91,948
Juv. male opioid costs $990,621 $1,323,949 $1,316,762 $1,180,173 $1,225,775 $1,643,251 $2,094,334 $1,931,973 $1,974,191 $1,861,096 $2,323,903 $2,214,089 $1,365,172 $1,498,558
Total opioid prison costs $29,415,323 $38,862,360 $45,062,726 $47,106,663 $55,283,213 $67,511,946 $69,810,509 $66,020,682 $75,259,131 $72,001,128 $73,993,586 $81,276,175 $74,719,395 $78,209,110

Source: Authors’ calculations

Cumulative lost GSP due to opioid overdose deaths

To account for annual historical GSP losses, we considered the number of cumulative overdose deaths per year beginning in 2003, the average age of decedents at the time of overdose, and the expected annual earnings for each decedent forward from the time of death to the end of 2016, considering the possibility of an early death not associated with opioid misuse. We accounted for the possibility of what otherwise would have been non-opioid-related nonemployment, by incorporating the annual Indiana nonemployment rate for each year.67 We accounted for future lost cumulative earnings of only past decedents in a separate section.

As in our GSP analysis, we converted the lost wages into GSP-equivalent losses for each year. Consideration was given to the likelihood of survival given the decedents were still alive and gainfully contributing to the Indiana workforce, noting the average age of the group throughout the crisis period.68, 69

We estimated wages growth from the St. Louis Federal Reserve’s report, which states that over the past 58 years, the wages growth rate in the United States has been 60 percent of the inflation rate over the same period.70

We calculated annual expected earnings for each year (2003-2016) among opioid misusers in Indiana by considering the annual numbers of deaths in Indiana per educational strata as reported by SAMHSA71 for years 2009-2016. We used the average educational strata ratio from SAMHSA from 2009-2016 to compute estimates for years 2003-2008. On average, the stratification across educational attainment reduced expected annual earnings by about 11.2 percent. The average age of death each year was established by looking at Kaiser Family Foundation information.72

Procedure

We began with the number of estimated deaths in each year. We considered the average age of decedent as the starting point for calculating lost economic contribution. In this section, the only use for average age of decedent was for the application of the actuarial survival rate for each year. We then needed to distribute the loss of life across the Indiana-specific educational strata. To do this, we used the educational strata provided by the SAMHSA database, in concert with median U.S. wages for each year. We then adjusted the U.S. wages by incorporating the relatively lower level of higher educational attainment in Indiana across all strata to arrive at the adjusted opioid annual wages for decedents for each year. Then, we estimated the total wages that would have been earned by the opioid decedents each year had they not died. To arrive at this estimate, we calculated the cumulative dead to date and multiplied by the adjusted opioid annual wages. This number was then adjusted by:

  1. Age-specific actuarial survival rates applied to the group, weighting the entire group cumulatively, throughout the period, to reflect the group was (a) overall getting older, and (b) would have experienced some non-opioid-related casualties along the way with cumulatively increasing likelihood. Actuarial data for survival rates was taken from the Social Security Administration.73
  2. The nonemployment rate, reflecting that some proportion of the decedents would be unemployed or absent from the labor force, had they survived.74 The details of calculating this rate are in the “primary losses to gross state product” section of this report.

We then adjusted lost work productivity to a GSP loss number, using a multiple for each year given total wages earned in Indiana and total GSP generated in Indiana in each year, respectively (see Table 17). Table 17 does not reflect costs associated with cash flows and resultant GSP losses associated with future earnings of past decedents, who would have yielded economic contributions going forward. These losses are presented in the next section.

It is worth mentioning that GSP losses from decedents, as described in the present section of this study, yield a direct shock to the economy apart from the level of full employment, labor force conditions or unemployment rates. In this section, we applied the likelihood for each decedent to have contributed economically—this is the nonemployment factor. We estimated that each decedent would have had the likelihood of adding to GSP at “one minus the (respective, annual) nonemployment rate” each year. In this section, we considered losses to GSP at the working-age nonemployment rate for all opioid decedents. The relatively small number of decedents (relative to total misusers) have not affected the balance of the entire labor market in Indiana. In contrast, the first section of the report estimates the attenuation of the state economy in times of full employment—which accrue because of the loss of available workers to push economic growth higher. In these instances, losses to GSP would aggregate from opioid misuse only in times of tight labor markets wherein opportunity costs of not having labor available to fill open positions is measurable. Thus, in the initial section outlining indirect GSP losses, we only added in GSP losses at times of relatively tight labor markets.

Table 17: Lost annual GSP due to opioid overdose deaths

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Number of estimated deaths 314 379 463 519 628 719 784 713 864 864 862 1,038 1,100 1,392
Average age of decedent 34.8 40.5 36.1 37.7 37.6 38.8 41.2 38.7 40.3 39.2 38.9 39.7 38.8 38.8
Median annual wages in U.S. $34,424 $35,516 $36,192 $37,336 $38,376 $39,572 $40,248 $40,664 $41,444 $42,380 $43,004 $43,628 $44,720 $46,020
Adjustment ratio per educational attainment in Indiana 88.80% 88.80% 88.80% 88.80% 88.80% 88.80% 93.81% 91.70% 86.11% 89.82% 86.70% 86.88% 86.29% 89.06%
Adjusted opioid annual wages – Indiana specific $30,567 $31,537 $32,137 $33,153 $34,076 $35,138 $37,758 $37,289 $35,688 $38,067 $37,284 $37,902 $38,587 $40,986
Inflation rate 2.3% 2.7% 3.4% 3.2% 2.8% 3.8% -0.4% 1.6% 3.2% 2.1% 1.5% 1.6% 0.1% 1.3%
GSP/wage ratio 2.393 2.414 2.408 2.426 2.478 2.48 2.533 2.655 2.63 2.586 2.622 2.641 2.581 2.567
Wage growth 1.38% 1.62% 2.04% 1.92% 1.68% 2.28% -0.24% 0.96% 1.92% 1.26% 0.90% 0.96% 0.06% 0.78%
Cumulative deaths 314 692 1,155 1,674 2,301 3,020 3,804 4,517 5,381 6,245 7,108 8,146 9,246 10,638
Unweighted cumulative survival function 99.74% 99.58% 99.42% 99.27% 99.10% 98.93% 98.75% 98.57% 98.37% 98.17% 97.96% 97.74% 97.52% 97.29%
Likely number of survivors adjusted for actuarial expectations 313 689 1,148 1,661 2,281 2,988 3,756 4,452 5,293 6,131 6,962 7,962 9,016 10,349
Annual nonemployment rate 21.7% 22.8% 22.5% 22.6% 24.3% 23.8% 24.9% 25.7% 26.1% 26.7% 26.1% 25.3% 24.4% 22.9%
Annual estimate for GSP loss $20,174,326 $45,628,829 $77,492,058 $116,519,875 $164,194,391 $223,245,680 $287,579,842 $356,888,751 $426,409,691 $492,382,685 $579,986,848 $685,179,613 $787,034,958 $942,261,944

Source: Authors’ calculations

Confirmed losses resulting from prior deaths attenuating future GSP

Throughout the crisis period, the opioid epidemic has cost thousands of Hoosiers their lives—we estimate 12,309 opioid deaths by the end of 2017. We calculate 11,953 would have remained alive given the average age of the cohort and actuarial adjustments across the entire time period (see Figure 10). The average age of this group through 2017, given they had not lost their lives, would have been 43.7 years.

Figure 10: Hoosiers who should still be alive but for opioid misuse

graph

* Given the average age of the cohort and actuarial adjustments across the time period.
Source: Authors’ calculations

Thus, we estimated that the group of those already gone had considerable working years remaining, and yet because of the opioid crisis, they will not be capable of economic contribution. The following summarized our assumptions about this group and their aggregated losses to GSP:

  1. Their collective wage growth throughout the duration of their lives would have been comprised of the average annual wage growth seen over the period moderated by the expected survival rate of 90 percent (our estimate for the increasingly aging members of the group). Prior years’ annual GSP contributions took into consideration both wage growth and actual survival rates given the average group age.
  2. We modeled that the group would have lived and contributed (aside from the already accounted for survival rates) until age 65. We selected 65, while we considered the U.S. retirement age of 65 phasing up to 67 and even 70, and the state’s average retirement age of 63.75, 76
  3. The GSP/wage ratio used for 2017 and beyond was modeled at the 2016 level.
  4. The discount rate for present valuation estimates was modeled as the average of the state GSP growth from 2003-2016. We estimated this to serve as a proxy for GSP growth through the duration of the decedents’ working lives.

Given the assumptions above, we modeled the present value of the future lost GSP that will have accrued from historical opioid-related decedents’ lost wages. We estimated the present value of the lost GSP as a growing annuity, using the growth rate described in assumption 1, which calculates to be 1.127 percent per year throughout the remaining expected working lives of the decedents.77 We use a discount rate of 3.52 percent, reflecting the average GSP growth rate as discussed in assumption 4. The annuity calculation yielded a present value of future losses equal to approximately $18.9 billion ($18,920,951,684, specifically). Importantly, this number does not include any deaths beyond December 31, 2017.

Estimates for calendar year 2017

The opioid crisis continues to accelerate.78 Indications from national and local sources suggest communities across the country and within Indiana continue to experience worsening outcomes and increasing numbers of misuse cases. Early indications in 2018 from conversations with mayors of the Indiana cities of Frankfort, Greenwood and Columbus reflect that emergency management resources are stretched completely out, resulting in currently inadequate resources for property and casualty protection. For instance, in the city of Greenwood, Mayor Mark Myers reports that police protection is no longer able to be provided in cases where non-violent criminal conversion cases are reported. Peggy Welch, Chief Advocacy Officer for Indiana's Family and Social Services Administration, has discussed the need, which has now become an emergency-level problem, to develop a solution set that can attack the opioid crisis at its root in Indiana. Maureen Hayden, Director of Intergovernmental Relations, has expressed an interest in understanding the financial impact at each local level within all communities in Indiana that are affected by the worsening opioid crisis. Mayor Chris McBarnes of Frankfort suggested educational efforts at the medical-school level would be welcome and could only add to the comprehensive solution that Indiana communities—and communities across the country—need right now.79

Given the discussion referenced above, as well as the trajectory of national opioid deaths shown in Figure 11, we modeled economic damages from the epidemic to have accelerated 20 percent in 2017 over 2016 figures.

Figure 11: U.S. drug overdose deaths

graph

Source: PBS NewsHour, using National Center for Health Statistics data

Aggregation of losses and calculation of total economic damages to date

This section presents the findings from all prior sections in this study. Initially, numbers are presented without finance adjustments (i.e., costs shown are in unchained, historical values each year for all categories). These annual aggregate costs are shown in Table 18.

Table 18: Aggregated historical annual losses

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Funerals $1,231,522 $1,527,591 $1,929,297 $2,233,309 $2,777,131 $3,300,910 $3,586,056 $3,313,572 $4,146,447 $4,233,076 $4,286,972 $5,242,821 $5,560,246 $7,130,837 $8,557,004
First response 516,992 644,751 814,422 936,733 1,179,148 1,351,698 1,514,482 1,397,969 1,745,325 1,469,712 1,753,993 3,168,932 3,298,170 4,262,142 5,114,570
Acute hospitalization 35,986,571 59,066,476 84,417,887 111,663,820 154,359,964 258,674,221 288,486,697 313,471,957 372,503,514 392,644,353 432,872,441 440,551,802 521,392,198 521,588,854 625,906,625
Long-term treatment 9,927,417 13,588,821 15,969,553 17,718,020 15,884,735 15,240,724 19,966,118 25,985,555 34,454,347 35,859,729 40,063,447 44,286,707 40,496,473 36,181,410 43,417,692
Neonatal abstinence syndrome 11,480,752 13,336,074 15,211,842 17,514,372 19,858,010 21,200,378 22,697,946 23,962,731 26,210,838 28,098,446 30,085,906 32,249,457 34,169,435 36,154,654 43,385,585
Foster care 6,552,584 9,417,378 12,931,329 16,994,945 22,052,819 26,929,770 33,141,751 33,321,391 41,678,328 43,933,116 45,728,170 52,560,766 55,509,178 61,247,789 73,497,347
Arrest and court cost 4,544,426 5,631,073 6,815,200 8,030,186 9,447,547 10,562,374 11,979,616 11,170,895 13,025,131 12,854,408 12,604,465 13,688,926 13,689,717 14,360,657 17,232,788
Property losses 21,806,476 27,366,055 33,632,426 40,078,260 45,619,826 49,983,643 53,059,276 48,529,815 58,878,297 55,670,606 51,444,425 51,866,195 50,865,589 53,143,010 63,771,612
Incarceration 29,415,323 38,862,360 45,062,726 47,106,663 55,283,213 67,511,946 69,810,509 66,020,682 75,259,131 72,001,128 73,993,586 81,276,175 74,719,395 78,209,110 93,850,932
HIV 20,517,325 22,190,661 22,379,929 29,000,742 25,581,471 26,146,684 27,989,363 24,332,433 24,146,986 27,361,396 23,733,147 24,077,294 128,207,036 14,540,230 17,448,276
Total direct damages 141,979,387 191,631,241 239,164,611 291,277,051 352,043,864 480,902,348 532,231,814 551,507,000 652,048,343 674,125,971 716,566,551 748,969,076 927,907,437 826,818,692 992,182,430
Lost GSP from deaths 20,174,326 45,628,829 77,492,058 116,519,875 164,194,391 223,245,680 287,579,842 356,888,751 426,409,691 492,382,685 579,986,848 685,179,613 787,034,958 942,261,944 1,130,714,333
Indirect lost GSP (labor markets) 0 62,346,406 99,681,226 196,647,432 323,749,108 275,205,850 0 0 0 0 0 98,636,380 926,801,738 1,725,768,439 2,070,922,127
Total annual cost (direct and indirect) 162,153,714 299,606,476 416,337,894 604,444,358 839,987,364 979,353,878 819,811,656 908,395,751 1,078,458,034 1,166,508,656 1,296,553,399 1,532,785,068 2,641,744,133 3,494,849,075 4,193,818,890

Source: Authors’ calculations

Time value of money principles were applied to arrive at a present value for each historical year of accumulated GSP losses, generating current equivalent values for all years’ losses. For instance, we brought 2003 losses forward to December 31, 2017. All years’ losses were brought forward in the same way. Specifically, valuations were calculated each year by considering that all losses were (a) accrued each year at mid-year, and (b) by forwarding the losses using annualized, actual, historical GSP rates.

Results

Table 19 presents these losses in three general categories:

  1. Direct economic losses.
  2. GSP losses accruing from opioid-related deaths.
  3. GSP losses during times of tight labor markets.

Table 19: Total present value of economic damages from opioid misuse in Indiana, as of December 31, 2017

Direct costs (excluding lost wages) Lost GSP from deaths Losses to GSP (labor markets) Total nominal cost Nominal GSP growth Factor Cumulative PV factor Total present value of economic damages (Dec. 31, 2017)
2003 $141,979,387 $20,174,326 $0 $162,153,714 5.89% 105.89% 1.649 $267,435,306
2004 191,631,241 45,628,829 62,346,406 299,606,476 2.78% 102.78% 1.580 473,504,756
2005 239,164,611 77,492,058 99,681,226 416,337,894 4.58% 104.58% 1.525 634,747,475
2006 291,277,051 116,519,875 196,647,432 604,444,358 5.39% 105.39% 1.452 877,870,567
2007 352,043,864 164,194,391 323,749,108 839,987,364 1.20% 101.20% 1.406 1,180,957,299
2008 480,902,348 223,245,680 275,205,850 979,353,878 -4.17% 95.83% 1.428 1,398,504,284
2009 532,231,814 287,579,842 0 819,811,656 7.70% 107.70% 1.406 1,152,852,127
2010 551,507,000 356,888,751 0 908,395,751 3.30% 103.30% 1.330 1,207,964,184
2011 652,048,343 426,409,691 0 1,078,458,034 2.89% 102.89% 1.292 1,393,829,290
2012 674,125,971 492,382,685 0 1,166,508,656 3.72% 103.72% 1.251 1,459,516,812
2013 716,566,551 579,986,848 0 1,296,553,399 4.74% 104.74% 1.201 1,556,569,767
2014 748,969,076 685,179,613 98,636,380 1,532,785,068 3.01% 103.01% 1.156 1,771,279,264
2015 927,907,437 787,034,958 926,801,738 2,641,744,133 3.43% 103.43% 1.120 2,957,569,487
2016 826,818,692 942,261,944 1,725,768,439 3,494,849,075 4.86% 104.86% 1.075 3,757,545,567
2017 992,182,430 1,130,714,333 2,070,922,127 4,193,818,890 4.97% 104.97% 1.025 4,297,994,441
Total present value of historical damages: 24,388,140,627
Total present value of future losses from past decedents: 18,920,951,684
Total economic damages accrued through December 31, 2017, arising from opioid misuse in Indiana: 43,309,092,311

Source: Authors’ calculations

Ongoing economic damages—Looking into 2018

2016 damages grew by 27.5 percent from 2015 levels. We estimated that 2017 damages grew by another 20 percent over 2016 levels, and we expect to see damages from opioids rise yet again in 2018 by about 10 percent over 2017 levels—barring successful widespread intervention.

Direct costs are expected to top more than $1 billion in 2018, while GSP losses from the accrual of deaths in Indiana will likely exceed $1.25 billion. With continued tight labor market conditions across the state, the GSP losses will likely surpass $1.75 billion this year. This brings us to a total beyond $4 billion in comprehensive costs in 2018, or in the neighborhood of $11 million per day.

Limitations

Our annual estimates of deaths driven by opioid misuse exclude damages from deaths caused by opioid-related hepatitis C (HCV), HIV and other blood-borne infections. We did include estimates of economic loss from opioid-fueled HIV infections as the lifelong annual costs for infections is significant. While it is likely that not many deaths have occurred thus far from blood-borne pathogens spreading through intravenous drug use since 2003, we are certain that if we had a way to measure these effects, they would add damages to our totals. Further, deaths and corresponding economic losses from these illnesses are likely to mount in the future as affected misusers age.

Early in the epidemic, categorization of drug overdose poisoning was not terribly accurate. We see this with our 20-20 hindsight, in looking at the drug overdose death data from ISDH. Once the Scott County HIV outbreak hit news media outlets in early 2015, reporting of opioid overdose deaths improved. Realizing the numbers in the early years were incomplete, we did make scientific adjustments to more accurately capture much of the underreporting attributable to opioid overdoses. However, given the extent to which underreporting likely occurred in the early years of the epidemic, we suspect not all opioid-related deaths have been modeled in our analysis. Given we had perfect historical data, we believe our number would, again, climb somewhat higher. Sensitivity analysis yields the possibility that anywhere from $200 to $400 million in additional aggregate losses may better reflect the overdose death costs from this epidemic. However, given the data we have had available, we are confident that the estimates of losses we calculated and present in this study are as accurate and complete as has been reasonably possible.

This study addressed many of the direct and indirect costs associated with the ongoing epidemic.  However, additional costs will be necessary to repair the problem at hand.  These costs, which are likely to be considerable in their amounts, were not included as a component of the present study.

Discussion

Opioids have been commonly prescribed medications in Indiana throughout the study period. However, it took more than a decade of the crisis quietly taking root within our society before the epidemic was placed front-and-center in spring 2015 with the news of the Scott County outbreak resulting in nearly 200 new cases of HIV—striking loudly the clear acknowledgement of the severity of the problem, which has inflamed Indiana and plagues the entire country.

While it is true the entire nation has been mired in the crisis, only a handful of states—including Indiana—have been struggling with the epidemic while also facing an increasingly tight labor market, aggravating our hopes of realizing strong post-recessionary growth in an economy where labor is increasingly difficult to find.

Recommendations

This is an economics study. However, due to unprecedented damages presented by the crisis, the authors thought it warranted to present our own thoughts on the matter in terms of future actions.

  1. Sentiment among community leaders, including elected officials, business professionals, organizational leaders, members of law enforcement, educators and others, must remain unbiased in their appreciation for human life and consciously make efforts to avoid stigmatizing our fellow citizens afflicted by this epidemic.
  2. The American Medical Association, American Dental Association, medical schools and dental schools across the country might want to revisit pedagogical strategy for the development of new physicians and oral surgeons. In particular, schools in the region may want to consider additional curricula that cover updated and improved considerations on risks for prescribing pharmaceuticals.
  3. Indiana is a leading state in the bio-sciences industry. A concerted effort—including funding, engineering and scientific investments—leading to the development and commercialization of effective, non-addictive, powerful pain relievers would prove useful in leading our country out of this crisis, while bringing positive economic attention to Indiana.
  4. Educational leaders from pre-K through college may wish to expand curricula on gaining better understanding of the risks associated with the misuse of pharmaceuticals, as well as learn methods to identify at-risk students so intervention can happen early.
  5. Mayors, sheriffs, congressional representatives, doctors, hospital executives and other leaders may wish to form a task force combining local-level resources across jurisdictions for the potential of developing a more comprehensive solution in greater regions of the state that might be more severely affected. Analysis in the following article illuminates opioid severity by county, over time, within Indiana.
  6. An open mind toward development of any solution may prove beneficial.

These steps are certainly not exhaustive, and we provide these thoughts only to stimulate further conversation in an attempt to develop a solution for this national problem.

Notes

  1. Brewer, R. (2017). The economic impact of opioid misuse in Indiana. Indiana Business Review, 92(4). Retrieved from www.ibrc.indiana.edu/ibr/2017/outlook/opioid.html
  2. Population data/NSUDH. Substance Abuse and Mental Health Services Administration (SAMHSA). See “Results from National Survey on Drug Use and Health: Detailed Tables” for years 2009-2016. Retrieved from www.samhsa.gov/data/population-data-nsduh/reports?tab=38. Note: For years 2015-2016, we used SAMHSA’s “opioid misuse” statistics, which encapsulate heroin misuse and nonmedical use of prescription painkillers. In years 2009-2014, SAMHSA only reports misuse statistics by educational attainment and employment status for nonmedical use of prescription painkillers, so we used these rates for our estimates.
  3. Data retrieval: Labor force statistics (CPS). U.S. Bureau of Labor Statistics. Retrieved from www.bls.gov/webapps/legacy/cpswktab5.htm
  4. Labor force time series (SA). STATS Indiana. Retrieved from www.stats.indiana.edu/laus_sa/laus_view3.html
  5. Intercensal estimates of the resident population by single year of age, sex, race, and Hispanic origin for the United States: April 1, 2000 to July 1, 2010. U.S. Census Bureau. Retrieved from www.census.gov/data/datasets/time-series/demo/popest/intercensal-2000-2010-national.html
  6. Dixon, A. (2017, March 29). The average retirement age in every state in 2016. SmartAsset. Retrieved from https://smartasset.com/retirement/average-retirement-age-in-every-state-2016
  7. What is the Social Security retirement age? National Academy of Social Insurance. Retrieved from www.nasi.org/learn/socialsecurity/retirement-age
  8. What full employment really means. (2017, January 29). The Economist. Retrieved from www.economist.com/blogs/economist-explains/2017/01/economist-explains-19
  9. What is the lowest level of unemployment that the U.S. economy can sustain? (2017, December 13). The Federal Reserve. Retrieved from www.federalreserve.gov/faqs/economy_14424.htm
  10. Organization for Economic Cooperation and Development. (2017, November). Economic outlook no. 102 – November 2017: Structural unemployment, forecasts. OECD.Stat. Retrieved from http://stats.oecd.org/Index.aspx?QueryId=61365#
  11. Revised OECD measures of structural unemployment. (2000). Organization for Economic Cooperation and Development. Retrieved from www.oecd.org/social/labour/2086120.pdf
  12. Hartman, M. (2015, September 4). Does 5.1% = full employment? Marketplace.org. Retrieved from www.marketplace.org/2015/09/04/economy/does-51-percent-full-employment
  13. US Funerals Online (2015, February 24). Arranging a funeral or cremation in Indiana. Retrieved from www.us-funerals.com/funeral-articles/funerals-and-cremations-in-indiana.html
  14. Historical inflation rates: 1914-2018. US Inflation Calculator. Retrieved from www.usinflationcalculator.com/inflation/historical-inflation-rates/
  15. Indiana State Department of Health. Stats Explorer Database. Retrieved from https://gis.in.gov/apps/isdh/meta/stats_layers.htm
  16. Moghe, S. (2016, October 14). Opioid history: From ‘wonder drug’ to abuse epidemic. CNN. Retrieved from www.cnn.com/2016/05/12/health/opioid-addiction-history/index.html
  17. Kenning, C. (2015, July 22). Indiana HIV outbreak has peaked, officials say. Indianapolis Star. Retrieved from www.indystar.com/story/news/2015/07/22/indiana-hiv-outbreak-has-peaked-officials-say/30524621/
  18. Population data/NSUDH. Substance Abuse and Mental Health Services Administration (SAMHSA). See “Results from National Survey on Drug Use and Health: Detailed Tables” for years 2009-2016. Retrieved from www.samhsa.gov/data/population-data-nsduh/reports?tab=38. Note: Authors multiplied the Indiana state total population in each year by the SAMHSA national heroin and opioid misuse rates, arriving at 110,806 Hoosiers estimated to be misusing given the national rates held in Indiana. Some evidence suggests the national rate may not be high enough to capture the full extent of the problem in Indiana.
  19. Wood, S. (2017, October 19). Victims of opioid overdoses stack up for coroners, costing taxpayers dearly. The Philadelphia Inquirer. Retrieved from www.philly.com/philly/health/addiction/bodies-opioid-ods-coroners-oxycontin-marino-trump-cdc-cadavers-philadelphia-pathologists-autopsies-norristown-toxicology-20171018.html
  20. Centers for Disease Control and Prevention. Provisional counts of drug overdose deaths as of 8/6/2017. Retrieved from www.cdc.gov/nchs/data/health_policy/monthly-drug-overdose-death-estimates.pdf
  21. IU Richard M. Fairbanks School of Public Health. (2016, September). Report on the toll of opioid use in Indiana and Marion County, p. 60. Retrieved from www.inphilanthropy.org/sites/default/files/Richard%20M.%20Fairbanks%20Opioid%20Report%20September%202016.pdf
  22. Naloxone (Narcan®) fact sheet. Stop Overdose IL. Retrieved from http://stopoverdoseil.org/assets/naloxone-fact-sheet.pdf
  23. Avery, B. (2016, June 27). The cost of an overdose. MetroWest Daily News. Retrieved from www.metrowestdailynews.com/news/20160521/cost-of-overdose
  24. Indiana State Department of Health (2017). County profiles of opioid use and related outcomes, p. 10. Retrieved from www.in.gov/isdh/files/CountyProfilesOfOpioidUse2017.pdf
  25. Indiana State Department of Health. Stats Explorer Database. Retrieved from https://gis.in.gov/apps/isdh/meta/stats_layers.htm
  26. Healthcare Cost and Utilization Project (2017). HCUP fast stats – Opioid-related hospital use. Agency for Healthcare Research and Quality. Retrieved from www.hcup-us.ahrq.gov/faststats/OpioidUseServlet?location1=IN&characteristic1=01&setting1=IP&location2=&characteristic2=01&setting2=IP&expansionInfoState=hide&dataTablesState=hide&definitionsState=hide&exportState=hide
  27. Lowery, M. (2014, November 4). Opioid overdoses straining hospital ERs. Modern Medicine Network. Retrieved from http://drugtopics.modernmedicine.com/managed-healthcare-executive/news/opioid-overdoses-straining-hospital-ers?page=full
  28. Rappleye, E. (2015, May 19). Average cost per inpatient day across 50 states. Becker’s Hospital CFO Report. Retrieved from www.beckershospitalreview.com/finance/average-cost-per-inpatient-day-across-50-states.html
  29. Stevens, J. P., Wall, M. J., Novack, L., Marshall, J., Hsu, D. J., & Howell, M. D. (2017). The critical care crisis of opioid overdoses in the United States, p. 12. Retrieved from www.thoracic.org/about/newsroom/press-releases/resources/opioid-crisis-and-icus.pdf
  30. Lowery, M. (2014, November 4). Opioid overdoses straining hospital ERs. Modern Medicine Network. Retrieved from http://drugtopics.modernmedicine.com/managed-healthcare-executive/news/opioid-overdoses-straining-hospital-ers?page=full
  31. Historical inflation rates: 1914-2018. US Inflation Calculator. Retrieved from www.usinflationcalculator.com/inflation/historical-inflation-rates/
  32. Lowery, M. (2014, November 4). Opioid overdoses straining hospital ERs. Modern Medicine Network. Retrieved from http://drugtopics.modernmedicine.com/managed-healthcare-executive/news/opioid-overdoses-straining-hospital-ers?page=full
  33. Ross, C. (2017, August 11). The cost of treating opioid overdose victims is skyrocketing. STAT News: Hospitals. Retrieved from www.statnews.com/2017/08/11/opioid-overdose-costs/
  34. Lawry, M. (2018). Indiana State Department of Health. Conversation and dialogue from the Indiana University Addictions and Grand Challenges Scoping Session, held on March 2, 2018 at Franklin Hall, Indiana University Bloomington. “ER visits reported by ISDH as attributable to opioid overdose spiked in 2016.  Prior years’ were likely underreported due to lack of focus on the opioid crisis, whereas by 2016, local communities were more appropriately apprised of the ongoing, statewide opioid epidemic.”
  35. Healthcare Cost and Utilization Project (2017). HCUP fast stats – Opioid-related hospital use. Agency for Healthcare Research and Quality. Retrieved from www.hcup-us.ahrq.gov/faststats/OpioidUseServlet?location1=IN&characteristic1=01&setting1=IP&location2=&characteristic2=01&setting2=IP&expansionInfoState=hide&dataTablesState=hide&definitionsState=hide&exportState=hide
  36. Substance Abuse and Mental Health Services Administration (SAMHSA). Treatment episode data set (TEDS) 2003-2013, pp. 64 & 76. Retrieved from https://wwwdasis.samhsa.gov/dasis2/teds_pubs/2013_teds_rpt_st.pdf
  37. Substance Abuse and Mental Health Services Administration (SAMHSA). Indiana TEDS admission tables. Retrieved from https://wwwdasis.samhsa.gov/webt/tedsweb/tabYearDotChooseYearWebTable?t_state=IN
  38. How much does opioid treatment cost?” (2018, January). National Institute on Drug Abuse. Retrieved from www.drugabuse.gov/publications/research-reports/medications-to-treat-opioid-addiction/how-much-does-opioid-treatment-cost
  39. Aim. (2018, February 15). Leadership council on the opioid epidemic in Indiana. Ritz Charles, Carmel, IN. Note: The Aim website can be accessed at https://aimindiana.org/.
  40. Rudavsky, S. (2017, July 5). Indiana to start covering methadone treatment for Medicaid recipients. Indianapolis Star. Retrieved from www.indystar.com/story/news/2017/07/05/indiana-expand-treatment-opioid-addictions/448920001/
  41. Understanding the cost of drug and alcohol rehab. (2018, February 5). AddictionCenter. Retrieved from www.addictioncenter.com/rehab-questions/cost-of-drug-and-alcohol-treatment/
  42. Goudie, C., & Tressel, C. (2017, August 8). As opioid epidemic grows, so does number of babies born addicted. ABC7 News. Retrieved from http://abc7chicago.com/as-opioid-epidemic-grows-so-does-number-of-babies-born-addicted/2231437/
  43. Ko, J. Y., Patrick, S. W., Tong, V. T., Patel, R., Lind, J. N., & Barfield, W. D. (2016, August 12). Incidence of Neonatal Abstinence Syndrome – 28 States, 1999-2013. Centers for Disease Control and Prevention. Retrieved from www.cdc.gov/mmwr/volumes/65/wr/mm6531a2.htm?s_cid=mm6531a2_w
  44. Vital Statistics. STATS Indiana. Retrieved from www.stats.indiana.edu/vitals/
  45. “Children in foster care.” Kids count data center. Retrieved from http://datacenter.kidscount.org/data/tables/6243-children-in-foster-care?loc=1&loct=2#detailed/2/16/false/573/any/12987. Note: We imputed the number in 2016 by applying the average growth rate over the past four years.
  46. Associated Press. (2017, December 12). Opioid crisis straining foster system as kids pried from homes. NBC News. Retrieved from www.nbcnews.com/storyline/americas-heroin-epidemic/opioid-crisis-strains-foster-system-kids-pried-homes-n828831
  47. Substance Abuse and Mental Health Services Administration (SAMHSA). Indiana TEDS admission tables. Retrieved from https://wwwdasis.samhsa.gov/webt/tedsweb/tabYearDotChooseYearWebTable?t_state=IN
  48. Ryan, T. (2016, December 15). Memo to foster parents. Indiana Department of Child Services. Retrieved from www.in.gov/dcs/files/FPPerDiemRates2017.pdf
  49. Alcohol and drug related arrest data. Indiana Prevention Resource Center (IPRC). See “Link to the Data Table” at bottom of page. Retrieved from http://drugs.indiana.edu/main/GIS_table.php?page_group=21&tablenum=Intro2.2
  50. Population data/NSUDH. Substance Abuse and Mental Health Services Administration (SAMHSA). See “Results from National Survey on Drug Use and Health: Detailed Tables” for years 2009-2016. Retrieved from www.samhsa.gov/data/population-data-nsduh/reports?tab=38
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  56. Crime in the U.S. (2017). Federal Bureau of Investigation. Retrieved from https://ucr.fbi.gov/crime-in-the-u.s. Note: For each year, see Table 5 for state total property crimes.
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  58. Reports & statistics (HIV/STD/Viral hepatitis). Indiana State Department of Health. Retrieved from www.in.gov/isdh/23266.htm. See “EPI Profiles” for years 2006-2010.
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  60. Kooreman, H., & Green, M. (2016, January). Injection drug use in Indiana: A major risk for HIV transmission. Retrieved from https://fsph.iupui.edu/doc/research-centers/Injection%20Drug%20Use%20in%20Indiana%202016.pdf
  61. Associated Press. (2006, November 10). HIV patients will spend $600K for lifetime care. NBC News. Retrieved from www.nbcnews.com/id/15655257/ns/health-aids/t/hiv-patients-will-spend-k-lifetime-care/
  62. US Treasury rates (2018) supplied by Multpl.com. Taken on February 19, 2018 from www.multpl.com/10-year-treasury-rate/table/by-year
  63. Rudavsky, Shari (2015). CDC: Indiana has one of the worst HIV outbreaks. The Indianapolis Star. April 28, 2015. Taken on February 20, 2018 from www.usatoday.com/story/news/nation/2015/04/28/indiana-hiv-outbreak/26498117/
  64. Population data/NSUDH. Substance Abuse and Mental Health Services Administration (SAMHSA). See “Results from National Survey on Drug Use and Health: Detailed Tables” for years 2009-2016. Retrieved from www.samhsa.gov/data/population-data-nsduh/reports?tab=38
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  66. Data and statistics. Indiana Department of Correction. Retrieved from www.in.gov/idoc/2374.htm. See “offender population statistical reports” for years 2009-2016.
  67. The “nonemployment rate” incorporates the unemployment rate each year, as well as the labor force participation rate each year, for Indiana, adjusted for working-age adults.
  68. Survival to age 65 (male and female). The World Bank. Retrieved from https://data.worldbank.org/indicator/SP.DYN.TO65.MA.ZS?locations=US
  69. Actuarial life table. Social Security Administration. Retrieved from www.ssa.gov/oact/STATS/table4c6.html
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  77. The present value of lost future earnings was converted to a GSP equivalent. It is uncertain whether these losses would have materialized as the decedents may have died from other causes at any time up through their points of respective anticipated retirement. However, we incorporated as much actuarial science as is reasonable to account for their lifetime lost earnings and corresponding GSP.
  78. Santhanam, L. (2017, December 21). The opioid crisis is driving down U.S. life expectancy, new data shows. PBS NewsHour. Retrieved from www.pbs.org/newshour/health/the-opioid-crisis-is-driving-down-u-s-life-expectancy-new-data-shows.
  79. Conversations with these professionals at Aim’s leadership council on the opioid epidemic in Indiana on February 15, 2018, at the Ritz Charles, Carmel, IN, resulted in the commentary discussed in the referenced paragraph. The Aim website can be accessed at https://aimindiana.org/.