Cumulative economic damages from 15 years of opioid misuse throughout Indiana

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)

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.

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:

.^{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.

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).
7. 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.

Figure 2: GSP capture rate

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.

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

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

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.

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

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.

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

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

Source: Authors’ calculations

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

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.

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

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).

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

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

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).

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

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.

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).

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.

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.

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.

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

* 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

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.

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.

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.