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Estimated Costs to the Pennsylvania Criminal Justice System Resulting From the Opioid Crisis
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Estimated Costs to the Pennsylvania Criminal Justice System Resulting From the Opioid Crisis

Gary Zajac, PhD; Samaan Aveh Nur, BA; Derek A. Kreager, PhD; and Glenn Sterner, PhD
The opioid crisis has made financial impacts across all levels of the public sector. This report focuses on costs related to the criminal justice system (CJS) in Pennsylvania. Costs impacting 3 principal areas of the CJS are examined: opioid-related arrests, court costs, and incarceration. Analysis of the state-level CJS is our main focus; no local-level costs are included. Through this examination, costs of the opioid crisis for the period of 2007 to 2016 were estimated using opioid costs for 2006 as a baseline. Total costs to the Pennsylvania CJS during this period were over $526 million, with most of that accounted for by state corrections. Opioid-related trends in arrests, court proceedings, and incarceration were not sufficiently well documented to allow for rigorous analysis in earlier periods, and this was the primary limitation to our analysis.
Am J Manag Care. 2019;25:-S0
Background And Existing Research

The current opioid epidemic in the United States has forced nearly every institution within the criminal justice system (CJS) to adapt rapidly to the much-increased ranks of illicit opioid users. Opioid use disorder (OUD) costs the CJS a considerable amount of money each year, ranging from the costs of arrests of opioid distributers to the medical and carceral costs of individuals with OUD who are imprisoned for substance-related offenses. Although the literature monetizing the damages of prescription opioids has typically been sparse,1 the OUD epidemic has motivated researchers to explore the issue in greater depth. These studies utilize a “cost of illness” approach in figuring costs, operationalizing the societal illness costs associated with OUD.

An early analysis of the economic impact of OUD2 compared individuals who had been diagnosed with OUD with a non-OUD control group. The results indicated that those with OUD had a mean annual health cost that was 8 times greater than that of the controls. Birnbaum et al (2006) expanded this analysis by extending their research into areas outside of private insurers and analyzing the impact of OUD on different social services.3 Estimates were calculated by multiplying the relevant number of prescription OUD cases (on the basis of national surveys) by the estimated per-person cost, or, alternately, taking overall costs of OUD for a particular component, such as police costs, and apportioning the OUD share on the basis of the prevalence of prescription OUD relative to overall drug misuse. Data were collected from the following sources: the National Survey on Drug Use and Health; Treatment Episode Data Sets; the Drug Abuse Warning Network; a database of private insurance claims of 600,000 individuals from 1998 to 2001; the database of the Bureau of Justice Statistics (BJS) on Criminal Justice Expenditures and Employment Extracts; the Federal Bureau of Investigation’s Uniform Crime Reports (UCR); the National Forensic Laboratory Information System; the BJS’s Prison and Jail Inmates at Mid-Year report; the Office of National Drug Control Policy’s (ONDCP) Drug Enforcement Administration Budget Summary for 2001; the ONDCP’s Budget Strategy for 2003; the National Association of State Alcohol and Drug Abuse Directors’ Analysis Report of State Alcohol and Drug Abuse for 1998 and 1999; and the Substance Abuse and Mental Health Services Administration’s Office of Applied Studies. Many of these data sources remain central to subsequent studies analyzing economic impacts of prescription OUD, especially the Uniform Crime Reports and Criminal Justice Expenditures and Extracts.3

The limitations of available data caused Birnbaum et al (2006) to assume that the costs of prescription and nonprescription OUD were the same.3 Furthermore, they stated that many costs associated with the CJS were omitted due to lack of data, such as fraudulent prescriptions, pharmacy theft, selling of prescription drugs by patients for whom they were prescribed, private legal defense, and property crime involving OUD. The estimated CJS-specific costs amounted to $438.4 million for policing, $221.2 million for courts, $201.6 million for county incarceration, $499.2 million for state incarceration, and $70.5 million for federal incarceration. Total costs incurred by the CJS were $1.4 billion in 2001, which amounts to 17% of the total costs of prescription OUD in the United States.3

Birnbaum et al conducted another analysis in 2011, evaluating impacts of OUD upon various social services nationally. Prescription OUD in 2007 accounted for $2.3 billion in correctional costs, two-thirds of which occurred at the state level. Policing costs were calculated at $1.5 billion, court costs at $726 million, and property damage at $625 million. In total, $5.1 billion was incurred by the CJS, amounting to 9.2% of total US societal costs of prescription OUD in 2007.1 Although this analysis is an extension of a previously conducted study, data sets were used with various methodologies and definitions, making comparisons and calculations among data sets difficult.3 The study also utilized the  same apportionment approach as the 2006 study, which has garnered heavy criticism.4,5 Birnbaum et al (2006) also noted that the conflation of heroin and prescription opioids into the same category created uncertainty in their final analysis.3

In an earlier study, Hansen et al tallied direct CJS expenditures and capital outlays made in 2003.6 This cost was then stratified into drug law expenditures versus expenditures for all other crimes. Expenses for prescription opioids were based on the relative percentage of confiscations compared with all other drugs that had been seized that year. Using this method, the authors found that in 2006, nonmedical prescription OUD costs were $3.4 billion for policing, $1.7 billion for courts, and $2.5 billion for incarceration, with a cost to victims at $618 million.6 Another analysis, from Florence et al, quantified the economic effects of prescription OUD and its impact on the CJS.7 As with past studies, a major source of data used in figuring CJS costs was the Justice Expenditure and Employment Extracts Primary report. The methodology was based on the 2011 apportionment method of Birnbaum et al, in which total CJS expenditures on drug crimes were tallied and then multiplied by the share of cases represented by prescription opioids, as reported from National Survey on Drug Use and Health.1,7 Investigators did not attribute costs to specific drugs if multiple drugs were used. The calculation summarizing the economic burden of prescription OUD on the CJS for 2013 was $7.7 billion, with $7.3 billion of the costs borne by agencies within local and state governments.7 The most recent evaluation of CJS costs associated with OUD, published in 2018, calculated an annual national cost of $2.9 billion for policing, $1.3 billion for courts, $3.3 billion for corrections, and $300 million in property losses associated with OUD—a collective $7.8 billion in 2016.8 Results of an analysis by Rhyan suggest that annual costs associated with combating the opioid epidemic will have approximately doubled across all sectors, including the CJS, by 2020.9

The results of the study from Hansen et al point to inflation and increased opioid misuse for the increased cost found in their analysis, compared with the 2011 analysis by Birnbaum et al.1,6 Hansen et al found greater costs than that suggested by subsequent studies.6,7,9 This discrepancy may be due to the inclusion by Hansen et al of lost productivity costs from incarceration or polydrug users in their CJS costs analysis.6

Several analyses utilize the apportionment method to calculate percentages of each major crime due to OUD. This method received criticism from Reuter, who cited previous findings arguing that it is impossible to calculate the amount of homicides for which drugs have been responsible, as homicide detectives themselves could not determine whether drugs were a factor in one-third of the cases investigated in New York City.5,10 The uncertainty of nonmedical prescription OUD is further compounded by the lack of current data, as several studies must rely on data sets that go as far back as 1996.6 For example, the last Drug Abuse Warning Network survey conducted was in 2011 and was then discontinued. The lack of recent data is complicated further by the conflation of natural and synthetic opioids merged into the same category that is used to measure OUD.1

Although the research mandate of literature reviewed in this article is limited to estimating costs related to the operations of state government, much of this literature examines the broader range of state and local costs (often combining them) and also extends into the estimation of broader societal costs, including some costs to individuals. Thus, the approach here is more parsimonious and may, to some extent, underestimate the full range of costs.

Conceptual Framework

Our estimate of the costs attributable to the opioid crisis uses data from 2006 (which is the earliest year for which reliable opioid-specific data were available) to establish a baseline of opioid-related costs, and to be compared with changes that occurred between 2007 to 2016. The counterfactual baseline shown in the figures below was estimated by projecting the trend and accounting for inflation. The difference between baseline projections from 2007 to 2016 and the actual observed costs for that period were interpreted to represent yearly changes in opioid-related cases and attendant costs associated with the opioid crisis. Yearly differences were summed over the years following 2006 and multiplied by the cost-per-case estimates (adjusted for inflation) to calculate total state funds associated with the crisis.

Estimation of costs incurred in policing were based upon opioid-related drug arrests by the Pennsylvania State Police (PSP) from 2007 to 2016, against the baseline year of 2006, following the analytical approach discussed above. The expense associated with what the PSP considers a “typical” drug arrest was used as the unit of cost. It should be noted that the per-arrest unit cost supplied by PSP represents a “bare minimum” arrest cost, approximating the cost for an uncomplicated arrest by a trooper for simple possession of opioids for personal use. Costs for arrests resulting in more intensive investigation activities would undoubtedly be higher, but are at this point unknown. Thus, the arrest costs calculated are likely underestimated. Again, arrest costs incurred by local law enforcement agencies are excluded.

Estimation of increased costs incurred by the courts is based upon court hearings and proceedings related to OUD at the Court of Common Pleas and Magisterial District Court levels from 2007 to 2016, against baseline. These courts were selected for analysis because they are the primary adjudicators of cases relating to OUD and are state-funded. Total convictions relating to OUD are compared with the total convictions, drug-related and not drug-related, adjudicated by the courts for the period being examined to estimate the proportion of all convictions, and thus of the total state court budgets, associated specifically with OUD. Conviction and court costs, along with related information, were collected from the Pennsylvania Commission on Sentencing and the Administrative Office of Pennsylvania Courts. Future analyses may be able to rely on a per-case unit cost derived from fees assessed to those convicted of drug crimes, which in theory represent the cost of such a case, but these fees are complex and beyond the scope of the current project.

Estimation of increased costs incurred by state corrections is based upon the estimated number of inmate commitments related to opioid-related drug convictions and the average length of stay of such inmates from 2007 to 2016, against the baseline year of 2006. The unit of cost used was the average annual prison expenditure per inmate (which includes costs related to treatment programs) multiplied by the average length of stay for the opioid-related crimes. This information was collected from the Pennsylvania Department of Corrections (PADOC).

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