Monetary Conversion Factors for Economic Evaluations of Substance Use Disorders

Abstract

Aims

Estimating the economic consequences of substance use disorders (SUDs) is important for evaluating existing programs and new interventions. Policy makers in particular must weigh program effectiveness with scalability and sustainability considerations in deciding which programs to fund with limited resources. This study provides a comprehensive list of monetary conversion factors for a broad range of consequences, services, and outcomes, which can be used in economic evaluations of SUD interventions (primarily in the United States), including common co-occurring conditions such as HCV and HIV.

Methods

Economic measures were selected from standardized clinical assessment instruments that are used in randomized clinical trials and other research studies (e.g., quasi-experimental community-based projects) to evaluate the impact of SUD interventions. National datasets were also reviewed for additional SUD-related consequences, services, and outcomes. Monetary conversion factors were identified through a comprehensive literature review of published articles as well as targeted searches of other sources such as government reports.

Results

Eight service/consequence/outcome domains were identified containing more than sixty monetizable measures of medical and behavioral health services, laboratory services, SUD treatment, social services, productivity outcomes, disability outcomes, criminal activity and criminal justice services, and infectious diseases consequences. Unit-specific monetary conversion factors are reported, along with upper and lower bound estimates, whenever possible.

Conclusions

Having an updated and standardized source of monetary conversion factors will facilitate and improve future economic evaluations of interventions targeting SUDs and other risky behaviors. This exercise should be repeated periodically as new sources of data become available to maintain the timeliness, comprehensiveness, and quality of these estimates.

1. Introduction

Substance use disorders (SUDs) represent major challenges to the healthcare sector, criminal justice systems, all types of workplaces, and other sectors of the economy. In the United States, the annual societal cost of SUDs amounts to about $740 billion in medical care spending and productivity losses, and SUDs are listed among the top ten non-genetic causes of death globally (Mokdad, Marks, Stroup, & Gerberding, 2004; National Institute on Drug Abuse, 2017; Yach, Hawkes, Gould, & Hofman, 2004). Opioid use disorders (OUDs), in particular, have attained epidemic status in the U.S. and have become a major focus of clinical interventions and public policy initiatives (Florence, Zhou, Luo, & Xu, 2016; Harris, 2016). Among individuals with OUDs, rates of HIV and viral hepatitis are substantially higher than in the general population, implying significantly higher costs to society for individuals with these co-occurring conditions (Hagan, Pouget, & Des Jarlais, 2011; Hess, Hu, Lansky, Mermin, & Hall, 2017). As the healthcare system in the U.S. continues to reassess commitments to disease prevention, parity for substance use and mental health services, and the creation of more patient-centered systems of care, estimating the economic consequences of SUDs is important for evaluating existing programs and new interventions, as well as for assessing the overall efficiency of health services delivery.

Understanding the economic consequences of SUD programs is also important for those policy makers who must weigh program effectiveness with scalability and sustainability considerations in deciding which programs to fund with limited taxpayer dollars (George, Harris, & Mitchell, 2001; Hutubessy, Baltussen, Torres-Edejer, & Evans, 2002; Tan-Torres Edejer et al., 2003). Consistent with these considerations, the Second Panel on Cost-Effectiveness in Health and Medicine recently released new recommendations for conducting rigorous and standardized cost effectiveness analyses (CEAs), which emphasize the importance of incorporating economic consequences occurring outside of the health sector into the calculation of cost-effectiveness ratios (Neumann, Sanders, Russell, Siegel, & Ganiats, 2017; Sanders et al., 2016). The Second Panel outlines two reference cases for CEA; one representing the health care sector and the second including society as a whole. The Second Panel recommends using an impact inventory to identify non-health sector consequences such as patient/family time costs, criminal justice and social services costs, and productivity losses. In both reference cases, the ability to assign values to nonpecuniary outcomes is essential.

Successful integration of economic analyses into randomized clinical trials and quasi-experimental studies of SUD interventions has produced a number of CEAs and cost-benefit analyses (CBAs), which largely show support for SUD interventions, especially those that reduce criminal activity along with substance use (Ettner et al., 2006; French, Salome, Sindelar, & McLellan, 2002; McCollister & French, 2003; Zarkin et al., 2015). Other economic studies, however, have evaluated programs where the cost of providing services outweighed the benefits (Alexandre, Salome, French, Rivers, & McCoy, 2002; Aos, Miller, & Drake, 2006). Additional economic evaluations are needed as behavioral health services become more integrated with primary care. Under integrated service delivery models, the streams of costs and benefits are likely to be quite different from conventional programs that operate more independently as silos of behavioral health care (Buntin, Burke, Hoaglin, & Blumenthal, 2011; Hutubessy et al., 2002; Mechanic, 2012; Tan-Torres Edejer et al., 2003; Woltmann et al., 2012).

The continued importance of CEA and CBA in SUD research notwithstanding, measurement challenges remain because the consequences of SUD-related interventions are measured across several distinct and independent outcomes such as robberies, emergency department visits, reliance on public assistance programs, days of homelessness, and workplace absenteeism. Monetary conversion factors (MCFs), sometimes referred to as unit prices or unit costs, are necessary for estimating the economic consequences and costs of services across these disparate measures.

The primary objective of the present study is to provide a comprehensive and updated list of MCFs that can be used to estimate the economic value of services, consequences, and outcomes associated with SUDs in the United States, including co-occurring conditions such as HCV and HIV. This list of MCFs can serve as an important tool for clinicians, researchers, and policy makers seeking to quantify the economic impact of SUD treatment and related interventions that are proven to be clinically effective. We build on a previous study by French and Martin (1996) (French & Martin, 1996), now more than two decades old, to present an updated set of measures and MCFs that can be used in a variety of program and policy evaluations. The Materials and Methods section outlines our approach to assembling relevant service/consequence/outcome domains and measures, and describes the data sources for the MCFs. The overarching goal is to promote and expand the use of CEA and CBA in evaluating programs and interventions targeting SUDs and other risky behaviors, while at the same time fostering an appreciation for the significant limitations analysts face when monetizing items across multiple domains.

2. Materials and methods

Our approach to defining domains, measures, and MCFs was designed to align closely with some of the more common clinical assessment instruments used in SUD treatment evaluations as well as national surveys containing substance use measures. This implies that the list of measures and MCFs is not exhaustive, but instead is meant to complement SUD-related research studies using a standard set of variables. Five assessment instruments were examined in detail: the Global Assessment of Individual Needs (GAIN) (Dennis, Titus, White, Unsicker, & Hodgkins, 2008), the Addiction Severity Index (ASI) (McLellan et al., 1992), Nonmedical Services (NMS) (Chandler et al., 2015), EconForm 90 (Bray et al., 2007), and the Phenx Toolkit (Hamilton et al., 2011), all of which are frequently used in randomized clinical trials and other research studies to evaluate the impact of SUDs and related clinical interventions across multiple outcome domains. In addition, we reviewed the National Longitudinal Survey of Adolescent to Adult Health (Add Health) and the National Survey on Drug Use and Health (NSDUH) for additional measures that can be used to identify the economic consequences of SUDs (Center for Behavioral Health Statistics and Quality, 2015; Chantala & Tabor, 1999).

Once appropriate measures were identified, we categorized them into eight broad domains: (1) medical and behavioral health services, (2) laboratory services, (3) substance use disorder treatment, (4) social services, (5) productivity outcomes, (6) disability outcomes, (7) criminal activity and criminal justice services, and (8) infectious diseases consequences. Although some domains include measures that are not necessarily direct or immediate consequences of substance use or dependence (e.g. Hepatitis B), we nonetheless include them here because they have been linked with SUDs (Centers for Disease Control and Prevention, 2012; Rosenberg, Drake, Brunette, Wolford, & Marsh, 2005). In addition, many of these domains are featured in existing studies of the economic burden of SUDs (Bouchery, Harwood, Sacks, Simon, & Brewer, 2011; Florence et al., 2016; Nicosia, Pacula, Kilmer, Lundberg, & Chiesa, 2009; Sacks, Gonzales, Bouchery, Tomedi, & Brewer, 2015; US Department of Justice National Drug Intelligence Center, 2011), and are considered the major drivers of the social costs of SUDs, including alcohol use disorders and smoking.

2.1 Literature Search and Cost Data Abstraction Process

A comprehensive literature review and targeted searches of sources were conducted to identify economic data for the MCFs. We searched PubMed, Web of Science, EBSCOhost, and Google Scholar using the following keywords: “substance use disorder” or “substance abuse” combined with “cost,” “economic consequences,” “economic burden,” or “social costs.” For each service/consequence/outcome measure, we followed the same process, searching the literature by combining “outcome” with the cost-related keywords (e.g., “emergency department visits” and “cost”). We were initially interested in identifying systematic reviews and meta-analyses looking broadly at the economic consequences of SUDs to verify our selection of outcome measures and categorization by domain. Key to the inclusion criteria, studies had to have been published within the past 20 years, written in English, and provide cost estimates per unit of outcome, consequence, or service. In our selection of MCFs, we specifically sought data from US nationally representative sources, multi-site randomized controlled trials, or micro-costing studies. For some measures, government reports and reputable websites (e.g., Centers for Medicare and Medicaid Services) were identified as the best source of economic data. In other cases, a single study was selected based on representativeness and recency, and methodology used to estimate costs. A total of 17,653 studies were identified across all domains and cost estimates were abstracted from 34 studies and online sources. Appendix Table A1 provides additional details on the results of the search strategy and the selection process for MCFs.

Specific measures and MCFs are presented in Tables 1 – 5. Domains with only two or three individual measures were combined into one table (e.g., Table 3 reports social services, productivity loss, and disability measures). Results tables also show the MCFs in the original year reported and the range, whenever possible and appropriate, to facilitate sensitivity analyses. Sensitivity analysis is necessary when MCFs have a high degree of uncertainty. For example, the estimated lifetime cost of Hepatitis B treatment will depend on a number of factors such as age of the patient, existing comorbidities, and response to first line treatment. Depending on these factors, Hepatitis B may be more or less expensive than the reported value. Thus, it is necessary to have a range of estimates to account for wide variability in costs. By providing upper and lower limits of MCFs, analysts can evaluate the sensitivity of their model to these assumptions.

Table 1. Monetary Conversion Factors for Medical and Behavioral Health Services.

Service	Original Value	2016 Value	Minimum	Maximum	Reference
Medical (Physical Health) Services
Inpatient Hospital Day – For-profit Hospital	$1,831 (2015 dollars)	$1,937	--	--	(Kaiser Family Foundation, 2015)
Inpatient Hospital Day – Non-profit hospital	$2,413 (2015 dollars)	$2,553	--	--	(Kaiser Family Foundation, 2015)
Inpatient Hospital Day - State/local hospital	$2,013 (2015 dollars)	$2,130	--	--	(Kaiser Family Foundation, 2015)
Emergency Department Visit (treat and release, unintentional injury)	$2,314 (2010 dollars)	$2,996	--	--	(Centers for Disease Control and Prevention, 2010)
Physician visit (new patient, 30 minutes)	$109 (2015 dollars)	$115	--	--	(Centers of Medicare and Medicaid Services, 2016)
Physician visit (new patient, 45 minutes)	$166 (2015 dollars)	$176	--	--	(Centers of Medicare and Medicaid Services, 2016)
Physician visit (established patient, 15 minutes)	$73 (2015 dollars)	$77	--	--	(Centers of Medicare and Medicaid Services, 2016)
Physician visit (established patient, 25 minutes)	$109 (2015 dollars)	$115	--	--	(Centers of Medicare and Medicaid Services, 2016)
Behavioral Health Services
Psychiatric Inpatient (per day)	$710 (2008 dollars)	$999	--	--	(Stranges, Levit, Stocks, & Santora, 2011)
Psychiatric diagnostic examination with medical services (new patient with physician)	$148 (2015 dollars)	$157	--	--	(Centers of Medicare and Medicaid Services, 2016)
Individual psychotherapy session, insight oriented, behavior modifying, and/or supportive (established patient, 45 minutes)	$85 (2015 dollars)	$90	--	--	(Centers of Medicare and Medicaid Services, 2016)
Individual psychotherapy with medication management services (established patient, 60 minutes)	$110 (2015 dollars)	$116	--	--	(Centers of Medicare and Medicaid Services, 2016)
Group therapy and counseling session with physician (per client)	$8.78 (2014 dollars)	$9.84	$3.32	--	(Berger 2005)
Group therapy and counseling session with licensed therapist (per client)	$2.12 (2014 dollars)	$2.38	$1.40	$3.61	(Berger 2005)
Group therapy and counseling session with nurse (per client)	$3.36 (2014 dollars)	$3.77	$2.48	$5.33	(Berger 2005)
Laboratory Services
Test for alcohol/drug use – Urinalysis	$65 (2016 dollars)	$65	$28	$80	(Cost Helper Inc, 2017)
HIV testing per patient (STD Clinic, with pre-test counseling)	$23 (non-reactive) $77 (reactive) (2006 dollars)	$36 (non-reactive) $121 (reactive)	--	--	(Farnham, Hutchinson, Sansom, & Branson, 2008)
HIV testing per patient (STD Clinic, without pretest counseling)	$13 (non-reactive) $66 (reactive) (2006 dollars)	$20 (non-reactive) $104 (reactive)	--	--	(Farnham et al., 2008)
HIV testing per patient (emergency department)	$10 (non-reactive) $61 (reactive) (2006 dollars)	$16 (non-reactive) $96 (reactive)	--	--	(Farnham et al., 2008)
HIV/AIDS counseling and rapid test (HIV-negative, hospital setting)	$48 (2006 dollars)	$75	$39	$138	(Pinkerton et al., 2010)
Screening for Hepatitis B Infection (office visit and blood test)	$33 (2008 dollars)	$46	--	--	(Eckman, Kaiser, & Sherman, 2011)

STD = Sexually Trasnmitted Disease

Table 5. Monetary Conversion Factors for Infectious Disease Consequences.

Measure	Original Value	2016 Value	Minimum	Maximum	Reference
HIV, HCV, Hepatitis B
Lifetime medical cost savings from preventing a case of HIV	$326,500 (2012 dollars)	$389,359	$358,592	$420,246	(Schackman et al., 2015)
Lifetime cost of care for HIV infected person (early diagnosis)	$253,222 (2011 dollars)	$314,148	--	--	(Farnham et al., 2013)
Lifetime cost of care for HIV infected person (late diagnosis)	$402,238 (2011 dollars)	$499,018	--	--	(Farnham et al., 2013)
Lifetime cost for individual infected with Hepatitis C	$64,490 (2011 dollars)	$80,007	$58,036	$90,800	(Razavi et al., 2013)
Annual health care costs associated with Hepatitis B (chronic Hepatitis B)	$761 (2000 dollars)	$1,814	--	--	(Lee, Veenstra, Iloeje, & Sullivan, 2004)
Annual health care costs associated with Hepatitis B (decompensated cirrhosis)	$11,459 (2000 dollars)	$27,316	--	--	(Lee et al., 2004)
Sexually Transmitted Infections
Chlamydia medical costs
Men	$30 (2010 dollars)	$39	$19	$58	(Owusu-Edusei et al., 2013)
Women	$364 (2010 dollars)	$471	$236	$707	(Owusu-Edusei et al., 2013)
Gonorrhea medical costs
Men	$79 (2010 dollars)	$102	$52	$154	(Owusu-Edusei et al., 2013)
Women	$354 (2010 dollars)	$458	$229	$688	(Owusu-Edusei et al., 2013)
Human Papillomavirus medical costs
Men	$45 (2010 dollars)	$58	$30	$101	(Owusu-Edusei et al., 2013)
Women	$191 (2010 dollars)	$247	$124	$426	(Owusu-Edusei et al., 2013)
Herpes Simplex Virus Type II medical costs
Men	$761 (2010 dollars)	$985	$493	$1,479	(Owusu-Edusei et al., 2013)
Women	$621 (2010 dollars)	$804	$403	$1,207	(Owusu-Edusei et al., 2013)
Syphilis medical costs
Men and Women	$709 (2010 dollars)	$918	$460	$1,378	(Owusu-Edusei et al., 2013)

Table 3. Monetary Conversion Factors for Social Services, Productivity Outcomes, and Disability Outcomes.

Measure	Original Value	2016 Value	Minimum	Maximum	Reference
Day missed school/training for any reason	$9.13 (1986 dollars)	$17	--	--	(Light, 2001)
Day missed work for any reason	$130 (2007 dollars)	$149	--	--	(Grosse, Krueger, & Mvundura, 2009)
Day in foster care, group home, or ward of the state	$22 (2012 dollars)	$23	$15	$29	(DeVooght & Blazey, 2013)
Day in homeless shelter	$29 (2004 dollars)	$36	$14	$68	(The Lewin Group, 2004)
Lifetime cost of low birthweight (per case)	$40,000 (1990 dollars)	$173,001	--	--	(Cutler & Meara, 1999)
Lifetime cost of fetal alcohol syndrome (per case)	$932,000 (2002 dollars)	$1,884,290	--	--	(Lupton, Burd, & Harwood, 2004)
Day experiencing medical problems (any)	$20 (1999 dollars)	$50	--	--	(French, Salome, & Carney, 2002)
Day experiencing psychological or psychiatric problems	$7.62 (1999 dollars)	$19	--	--	(French et al., 2002)
Quality-adjusted life year lost	$100,000	$100,000	$50,000	$200,000	(Neumann, Cohen, & Weinstein, 2014)

Once we identified the available MCFs for each measure, we converted all estimates into 2016 dollars using the GDP deflator (for non-health outcomes) or Personal Consumption Expenditures – Health Care (PCE-Health) index (for medical expenditures) (Dunn, Grosse, & Zuvekas, 2016). These tools for normalizing expenditures from different years are considered superior to the consumer price index (CPI), as they take into account different rates of inflation between health and non-health expenditures, among other factors.

3. Results

The MCF estimates fall into two general categories with different analytic timeframes. Most of the MCFs capture short-term economic consequences by valuing units of medical or behavioral health care services, contacts with the criminal justice system, days missed from work, etc. The second category of MCFs captures lifetime costs associated with chronic conditions or other health outcomes (HIV, HCV, birth outcomes, QALYs). The short-term estimates represent the immediate impact of an intervention and align well with outcome data being collected within a post-intervention follow-up assessment (e.g., up to 5 years, although the vast majority of SUD research studies do not extend data collection beyond a 1 or 2 year follow up). Other studies focused on preventing HIV or HCV transmission or other risky behaviors will naturally assume a longer analytic timeframe requiring projections of lifetime costs. Combining short-term and long-term economic consequences for a full economic evaluation can be challenging, which is discussed further in the Discussion section.

Two outcome domains are presented in Table 1: Medical and Behavioral Health Services, and Laboratory Services. Measures include units of service, such as a day or episode of treatment, as well as laboratory products, such as urinalysis screening for drugs and alcohol and HIV testing. MCFs for health care services come from the American Hospital Association (AHA), the Centers for Medicare and Medicaid Services (CMS), and the Agency for Healthcare Research and Quality's Healthcare Utilization Project (HCUP) (Centers of Medicare and Medicaid Services, 2016; Kaiser Family Foundation, 2015; Stranges, Levit, Stocks, & Santora, 2011). The AHA provides estimates for the average “cost per hospital day” based on ownership status—for-profit, non-profit, and state or local hospitals (available on the Kaiser Family Foundation website). These estimates are based on CCR-adjusted hospital charges per inpatient day. CMS provides detailed estimates for the “cost per physician office visit” for physical and mental health concerns based on Medicare reimbursement rates for unique Current Procedural Terminology (CPT) codes. The CMS cost estimates are based on Medicare's relative value units (RVUs), which incorporate physician time, practice expenses, and malpractice insurance. The estimate for an emergency department visit (treat and release, unintentional injury) comes from the Centers for Disease Control and Prevention's Web-based Injury Statistics Query and Reporting System (WISQARS) (Centers for Disease Control and Prevention, 2010).

On average, the cost per inpatient hospital day ranges from $1,937 in a for-profit hospital to $2,553 in a non-profit hospital. A physician visit (physical health problem) ranges from $77 for a 15-minute visit with an established patient to $176 for a 45-minute visit with a new patient. The cost for an emergency department visit is $2,996, which represents the cost of “treat and release” for an unintentional injury. This estimate would be much higher for a more serious emergency department admission resulting in hospitalization and including patient productivity losses.

For behavioral health services, the average cost per day in a psychiatric inpatient hospital is $999. The average cost per mental health outpatient visit varies considerably depending on the type of patient (new or established), duration of visit, and whether the patient received medical management services. A psychiatric diagnostic examination by a physician for a new patient is $157 per visit. A 45-minute individual psychotherapy session with an established patient is $90. An individual psychotherapy session requiring medication management is $116 for a 60-minute session.

To estimate the cost per group therapy and counseling session, we made an assumption about the average number of clients attending a group therapy session. The website psychologistanywhereanytime.com reports that the average group therapy session has 5-10 participants. We selected an average of 10 participants per group session and used average hourly salary information excluding fringe benefits for mental health providers from the Bureau of Labor Statistics; average fringe benefit rates for all employees are also available from the Bureau of Labor Statistics (United States Department of Labor, 2017). The per-client cost for a group counseling session across all types of providers ranges from $2.38 to $9.84, depending on the qualifications of the provider. We did not have information on office lease rates or administrative expenses for group counseling services, so this estimate represents only personnel costs of conducting group counseling.

The last section of Table 1 reports MCFs for laboratory services. The average cost per alcohol or other drug screen varies widely depending on location of the test (at home, clinic, hospital), number of drugs included in the test, and payer (purchased over the counter, paid for by insurance). The website “http://health.costhelper.com/drug-alcohol-test.html#extres2” provides a number of estimates for drug tests from different sources (Cost Helper Inc, 2017). Based on available pharmacy and clinic prices for urine drug testing kits, we selected a cost per urinalysis test for alcohol and other drug use of $65, reflecting the mean for lab-based costs ranging from $50 - $80. For the minimum value, we selected $28, the average cost of an over-the-counter poly-drug testing kit according to drugstore.com. The maximum is based on the upper range for lab-based testing ($80). Per patient cost for HIV testing ranges from $16 in an emergency department (negative or nonreactive result) to $121 in a community-based health clinic with pre-test counseling (positive or reactive result) (Farnham, Hutchinson, Sansom, & Branson, 2008; Pinkerton et al., 2010). Finally, screening for hepatitis B in an office setting is $46 per patient (Eckman, Kaiser, & Sherman, 2011).

The cost of SUD treatment programs comes from systematic reviews and primary (micro-costing) economic studies in the peer-reviewed literature. National estimates of the cost per average inpatient detoxification episode were unavailable, so instead we present an estimate from a statewide evaluation of SUD treatment costs from the state of Florida (Alexandre et al., 2012). Seventeen inpatient detoxification programs were surveyed from different counties throughout the state. The average cost per day of inpatient detoxification treatment was $414.

French et al., (2008) reported the average cost per episode for different SUD treatment modalities as well as cost bands for each estimate (French, Popovici, & Tapsell, 2008). These estimates are based on more than 100 studies that collected primary data on treatment program resources used and associated costs using the Drug Abuse Treatment Cost Analysis Program (DATCAP) (French, 2003). A day in a residential alcohol/drug treatment program costs $177. Standard and intensive outpatient treatment visits cost $31 and $83, respectively. A day of methadone or disulfiram treatment costs $24 per patient.

Additional information on the cost of delivering screening, brief intervention, and referral to treatment (SBIRT) services was provided by Bray et al., (2012) and Barbosa et al. (2016) (Barbosa, Cowell, Landwehr, Dowd, & Bray, 2016; Bray, Zarkin, Hinde, & Mills, 2012). Bray et al., (2012) provides a systematic review of the costs of screening and brief intervention (SBI) for alcohol use disorders in primary care, emergency department, and inpatient settings. Seventeen SBI studies were identified with relevant cost information, although the costing methodology varied across these studies (activity-based, non-activity based, and hybrid). Accounting for a few outliers, the average cost of screening is $9.22, ranging from $0.69 to $32. The average cost of brief intervention is $62, ranging from $4.22 to $126.

Beginning in 2003, the Substance Abuse and Mental Health Services Administration (SAMHSA) provided funding to a cohort of seven states (subsequent cohorts were also funded) to support provision of SBIRT for alcohol and other substances in hospitals, urgent care facilities, and outpatient settings. Barbosa et al., (2016) estimated program and service-level costs for these different implementations of SBIRT using the Substance Abuse Services Cost Analysis Program (SASCAP) (Zarkin, Dunlap, & Homsi, 2004). Across all settings, the average cost per episode of brief treatment (BT) is $31, ranging from $27 to $33 per session. Referral to treatment is less resource intensive than BI or BT, with an average cost of $12 (range $9.58 to $14).

Table 3 presents MCFs for three outcome domains: Social Services, Productivity Loss, and Disability. The cost per day missed from school is adapted from a study by Light (2001), which estimated the wage premium for an additional year of schooling (Light, 2001). To calculate the value of one day of school or training ($17), we used the average hourly wage rate in Light (2001)'s sample ($6.20), annualized and adjusted to 2016 dollars using the CPI, and divided by a 180-day school year. The cost per day missed working for any reason is $149, and is calculated based on the average daily value of production for the U.S. non-institutional population, including both work and household productivity (Grosse, Krueger, & Mvundura, 2009). This estimate could be adjusted up or down if more detailed information on occupation and labor supply (e.g., full-time vs. part-time) is available.

For social services, a report from the National Survey on Family Foster Care Provider Classifications and Rates provided updated estimates of state payment rates for foster care services (DeVooght & Blazey, 2013). The average cost per day in foster care, a group home, or as a ward of the state is $23, ranging from $15 per day in Alaska to more than $29 per day in Maryland (DeVooght & Blazey, 2013). A report from the Lewin Group (2004) provided estimates of the cost per day in a homeless shelter based on shelter operating costs from 9 major U.S. cities. The average cost per homeless shelter day is $36, ranging from $14 to $68 (The Lewin Group, 2004).

Disability measures include short-term effects from a day experiencing medical or psychological problems as well as lifetime costs. MCFs for a “day experiencing medical/psychological/psychiatric problems” come from a study by French et al. (2002) (French, Salome, & Carney, 2002), which outlined a methodology for using the Drug Abuse Treatment Cost Analysis Program (DATCAP) (French, 2003) and measures from the ASI to conduct economic evaluations of SUD interventions. These MCFs draw from the literature on the value of a statistical life (VSL) (Viscusi & Aldy, 2003) and quality-adjusted life-years (QALYs) (Mehrez & Gafni, 1989) to project the cost per one-unit decrement in a quality-adjusted life-day based on a VSL of $1 million. A day experiencing medical problems is valued at $50 and a day experiencing psychological or psychiatric problems is valued at $19.

Lifetime impacts associated with SUD include poor birth outcomes and cases of fetal alcohol syndrome (FAS). Cutler and Meara (1999) estimated the lifetime cost per case of a low birthweight infant to be $173,001 (Cutler & Meara, 1999). This estimate includes costs from treating medical complications resulting from premature birth and related nonmedical costs such as special education and disability payments. A study by Lupton et al (2004) estimated the lifetime cost of a case of fetal alcohol syndrome to be $1.88 million, representing the present discounted value of lifetime medical costs and productivity losses (Lupton, Burd, & Harwood, 2004).

Change in QALYs is another key outcome in economic evaluation studies. QALYs combine the morbidity and mortality impact of a disease or condition into a single metric, expressed as the number of years of optimal health remaining (i.e., quality-adjusted life-expectancy), or how an individual's overall health in a given year ranks between the extreme states of “death” and “perfect health.” Considerable uncertainty is present in the economic value per QALY. Several studies have estimated the societal willingness-to-pay per QALY, which ranges from $33,702 to more than $580,000 (Hirth, Chernew, Miller, Fendrick, & Weissert, 2000). Others have estimated a range of approximately $100,000-$300,000 based on trends in healthcare spending and population health gains (Braithwaite, Meltzer, King, Leslie, & Roberts, 2008). These ranges are higher than the cost effectiveness threshold in the UK, which is typically 20,000 - 30,000 British Pounds (or approximately $25,000 - $36,000 in 2016 US dollars) (Rawlins, Barnett, & Stevens, 2010). Table 3 reports $100,000 as the suggested MCF per QALY based on the current trend of practice in the U.S. (Neumann, Cohen, & Weinstein, 2014).

Table 4 reports MCFs for individual criminal acts and contacts with the criminal justice system. The cost per criminal offense is taken from a study by McCollister, French, and Fang (2010) (McCollister, French, & Fang, 2010), which estimated the societal cost of crime for 13 unique offenses. This study used national data on criminal offenses, victim losses, productivity losses, and criminal justice system expenditures and has been used in several economic evaluation studies to date. This study also includes a review of the crime-costing literature to report a range of values for each offense. These are societal crime cost estimates, representing the tangible and intangible costs per offense, including the value of victims' pain and suffering and lost productivity. Violent offenses including murder, rape/sexual assault, and aggravated assault generated the highest cost-per-offense ($10.09 million, $270,352, and $120,166 per act, respectively). Robbery, arson, and motor vehicle theft have cost-per-offense of between $12,095 and $47,507 per act. The remaining crimes including stolen property, household burglary, embezzlement, forgery and counterfeiting, fraud, vandalism, and larceny/theft ranged between $3,966 and $8,953 per act. The cost per day of engaging in unspecified illegal activity, a measure from the ASI, was estimated to be $1,011, based on French et al. (2002) (French, Salome, & Carney, 2002).

Table 4. Monetary Conversion Factors for Criminal Activity and Criminal Justice Services.

Measure	Original Value	2016 Value	Minimum	Maximum	Reference
Criminal Activity (per offense)
Murder	$8,982,907 (2008 dollars)	$10,086,337	$4,653,795	$12,744,967	(McCollister, French, & Fang, 2010)
Rape/Sexual assault	$240,776 (2008 dollars)	$270,352	$90,279	$415,156	(McCollister et al., 2010)
Aggravated assault	$107,020 (2008 dollars)	$120,166	$24,086	--	(McCollister et al., 2010)
Robbery	$42,310 (2008 dollars)	$47,507	$20,875	$314,660	(McCollister et al., 2010)
Arson	$21,103 (2008 dollars)	$23,695	--	$60,217	(McCollister et al., 2010)
Motor vehicle theft	$10,772 (2008 dollars)	$12,095	$1,935	--	(McCollister et al., 2010)
Stolen property	$7,974 (2008 dollars)	$8,953	$170	$25,532	(McCollister et al., 2010)
Household burglary	$6,462 (2008 dollars)	$7,256	$2,216	$33,906	(McCollister et al., 2010)
Embezzlement	$5,480 (2008 dollars)	$6,153	--	--	(McCollister et al., 2010)
Forgery and counterfeiting	$5,265 (2008 dollars)	$5,912	$935	--	(McCollister et al., 2010)
Fraud	$5,032 (2008 dollars)	$5,650	--	--	(McCollister et al., 2010)
Vandalism	$4,860 (2008 dollars)	$5,457	--	--	(McCollister et al., 2010)
Larceny/theft	$3,532 (2008 dollars)	$3,966	$386	--	(McCollister et al., 2010)
Day engaged in illegal activity (for profit)	$708 (1997 dollars)	$1,011	--	--	(French et al., 2000)
Alcohol involved traffic crash (no injury)	$2,843 (2010 dollars)	$3,130	--	--	(Blincoe, Miller, Zaloshnja, & Lawrence, 2015)
Alcohol involved traffic crash (fatality)	$10,143,026 (2010 dollars)	$11,167,605	--	--	(Blincoe et al., 2015)
Criminal Justice Services
Day on probation	$3.42 (2008 dollars)	$3.84	--	--	(Pew Center on the State, 2009)
Day on parole	$7.47 (2008 dollars)	$8.39	--	--	(Pew Center on the State, 2009)
Day in jail/detention	$79 (2010 dollars)	$87	--	--	(Kyckelhahn, 2012)
Day incarcerated	$86 (2010 dollars)	$95	--	--	(Henrichson & Delaney, 2012)

Alcohol-involved traffic crashes are included among the economic consequences of criminal activity. Blincoe et al., (2015) estimated the average cost per alcohol-involved crash to be $3,130 without injury and $11.17 million per incident involving a fatality (Blincoe, Miller, Zaloshnja, & Lawrence, 2015). For studies interested in looking specifically at the economic consequences to the criminal justice system from incarceration and community supervision, we provide MCF estimates of the direct cost per criminal justice contact based on reports by the Pew Center on the States (Pew Center on the State, 2009), the U.S. Department of Justice's State Corrections Expenditures (Kyckelhahn, 2012), and VERA.org (Henrichson & Delaney, 2012). Incarceration costs (jail/detention or prisons) include operating costs (salaries, benefits, contracted services, supplies, facilities costs, healthcare and other services for inmates) as well as capital expenditures. For community supervision contacts, a day on probation is estimated to cost $3.84 and a day on parole is $8.39. A day in detention is $87 and a day incarcerated in state prison is $95.

Table 5 presents MCF estimates for infectious diseases consequences associated with substance use. Most of the MCFs come from published scientific studies (Eckman et al., 2011; Farnham et al., 2013; Hodgson, 1992; Lee, Veenstra, Iloeje, & Sullivan, 2004; Owusu-Edusei et al., 2013; Razavi et al., 2013; Schackman et al., 2015). The lifetime medical cost savings from preventing one HIV infection is estimated to be $389,359 (Schackman et al., 2015). Other estimates reporting the lifetime cost of care for HIV infected persons in the United States range from $314,148 to $499,018, depending on time of diagnosis and entry into care (Farnham et al., 2013). The additional lifetime cost of an individual infected with Hepatitis C is $80,007, ranging from $58,036 to more than $90,000 (Razavi et al., 2013). Average annual health care costs for patients infected with Hepatitis B are $1,814 for chronic hepatitis B and $27,316 for decompensated cirrhosis (Lee et al., 2004).

A study by Owusu-Edusei et al. (2013) (Owusu-Edusei et al., 2013) reports the direct medical costs of sexually transmitted infections in the United States for a range of diagnoses. For females, the cost per STI case ranges from $247 for Human Papilloma Virus (HPV) to $804 for Herpes-Simples Virus (HSV2). For males, the cost per case ranges from $39 for Chlamydia to $985 for HSV2. The average cost per case of syphilis is $918 (either gender).

4. Discussion

This study provides an updated and standardized source of information on the economic consequences of SUDs to facilitate future cost-effectiveness and cost-benefit analyses of interventions targeting SUDs and other risky behaviors in the US. The approach to selecting specific outcomes, consequences, and services to monetize was guided primarily by clinical assessment instruments commonly used in SUD research (e.g., ASI, GAIN, PhenX Toolkit). Most economic evaluations of SUD interventions will have at least a subset of these outcomes. The majority of CEAs, CBAs, and economic burden studies in this field estimate the economic consequences of SUDs from health care services, criminal activity, and labor market outcomes (e.g., (Bouchery et al., 2011; Ettner et al., 2006; McCollister & French, 2003; Zarkin et al., 2015)). Of these domains, the relative contribution of criminal activity to the total economic consequences of SUDs is typically the largest driver of social costs.

The variety of domains and measures considered here allows for the framing of analyses from different perspectives (e.g., criminal justice system, insurance payer, treatment provider). For instance, a SUD treatment provider may want to estimate the change in SUD treatment utilization and costs following an initial episode of treatment. The MCFs in Table 2 provide estimates for six different modalities of treatment that could be used for this assessment (inpatient detoxification, residential treatment, intensive outpatient treatment, standard (drug free) outpatient treatment, methadone or disulfiram treatment, and screening, brief intervention, and referral to treatment or SBIRT). The estimates can also be used outside of SUD treatment evaluations to estimate the economic consequences of crime prevention programs, school-based delinquency interventions, and prevention programs targeting risky behaviors.

Table 2. Monetary Conversion Factors for Substance Use Disorder Treatment.

Service	Original Value	2016 Value	Minimum	Maximum	Reference
Inpatient detoxification for SUD (day)	$308 (2009 dollars)	$414	$20	$810	(Alexandre et al., 2012)
Residential SUD treatment (day)	$113 (2006 dollars)	$177	$136	$206	(French, Popovici, & Tapsell, 2008)
Intensive outpatient treatment (visit)	$53 (2006 dollars)	$83	$54	$134	(French et al., 2008)
Standard outpatient treatment (visit)	$20 (2006 dollars)	$31	$17	$50	(French et al., 2008)
Methadone or disulfiram (day)	$15 (2006 dollars)	$24	$19	$25	(French et al., 2008)
Screening for SUD	$6.85 (2009 dollars)	$9.22	$0.69	$32	(Bray, Zarkin, Hinde, & Mills, 2012)
Brief Intervention	$46 (2009 dollars)	$62	$4.22	$126	(Bray et al., 2012)
Brief Treatment	$26 (2012 dollars)	$31	$27	$33	(Barbosa, Cowell, Landwehr, Dowd, & Bray, 2016)
Referral to Treatment	$9.77 (2012 dollars)	$12	$9.58	$14	(Barbosa et al., 2016)

SUD = substance use disorder

Of course, a number of limitations must be noted. In searching for the most rigorous MCFs, the quality and availability of data remain the primary challenges. Some measures, such as SUD treatment episode costs, are based on detailed micro-costing studies that most accurately reflect the opportunity cost of program resources (Alexandre et al., 2012; Barbosa et al., 2016; Bray et al., 2012; Popovici, French, & McKay, 2008). This is the recommended approach highlighted in the Second Panel on Cost Effectiveness in Health and Medicine (Neumann et al., 2017) as well as in the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) (Husereau et al., 2013). Health services costs, on the other hand, are based on national reimbursement rates or adjusted hospital charges, which may not accurately represent actual costs of service delivery. Moreover, several MCFs are based on present-value adjustments of earlier published estimates rather than recent analyses. Variation in MCFs was limited by the very small number of studies available for data abstraction, which prevented us from calculating statistical inference metrics (e.g., median, standard deviation, interquartile ranges). Considering the importance of these metrics when conducting sensitivity analyses in cost-effectiveness and cost-benefit studies, this is a critical shortcoming that can only be addressed through additional research.

Similarly, we have limited information on potential sources of heterogeneity that would impact the utility of the MCFs for certain types of analyses. Most of the MCFs are based on aggregate sources of cost data rather than cost information differentiated by population subgroups. Relying on aggregate data would limit the applicability of these MCFs for examining the economic consequences of SUDs in rural communities, among Native Americans, pregnant/parenting women, or for other special populations. Nonetheless, we have attempted to select high quality information based upon the best available data sources and believe that these MCFs are the “current state of the science” for estimating economic consequences.

Another limitation to note is the different analytic timeframes for the MCFs. HIV and HCV measures, for instance, represent a lifetime perspective on costs, whereas other measures (e.g., day on probation, day missed work) represent short-term costs. Long-term costs are often translated into net present values (by discounting future costs at a standard rate, usually 3%), which can then be compared and/or combined with short-term costs. However, long-term costs have more uncertainty and this can cause considerable variation in total cost estimates.

An additional limitation in using MCFs is that some outcomes, such as violent crime, occur infrequently yet have very high costs. Monetizing reductions in these rare yet costly events tend to skew the distribution of total social costs and introduces a number of statistical challenges in estimating cost-effectiveness ratios or net economic benefits. In cases where only one or a small number of these crimes are reported, a sensitivity analysis is recommended to remove extreme outliers from the calculations and then re-examine how results change.

Nonviolent crimes such as theft or household burglary may also generate intangible costs to crime victims, but we were not able to estimate this component with existing data sources. Other types of “victimless” crimes, such as buying/selling drugs and prostitution, are prevalent among people with SUDs, but little consensus exists on how to value them in terms of a cost per offense. The true incidence of these offenses is probably much higher than reported, and if an act does not result in an arrest or other contact with the criminal justice system, the associated societal costs of the individual transaction is minimal. Indeed, a transaction between a prostitute and client might be viewed as a simple exchange of service for pay assuming that pregnancy, sexually transmitted infections, and other negative consequences are absent.

5. Conclusions

This review and cost-compilation study offers an important contribution to the economic evaluation literature by providing a current, comprehensive, and standardized source of MCFs for estimating the economic consequences of substance use disorders in the US. A broad collection of MCFs should serve as a valuable tool for clinicians, researchers, and policy makers seeking to conduct economic evaluations of substance use treatment, prevention, and related programs. Continued research is warranted to update these estimates as more rigorous estimation approaches and better sources of data become available.

Highlights.

• Comprehensive source of Monetary Conversion Factors for estimating the economic consequences of Substance Use Disorders

• Features eight service/consequence domains and more than sixty unique measures

• Valuable tool for clinicians, researchers, and policy makers seeking to conduct economic evaluations

Appendix.

Table A1. Literature Search and Cost Data Abstraction: Number of Sources.

Literature Search Step	Soci al Cost s of SU Dsa	Medical and Laborat ory Services	Behavi oral Health Service s	SUD treatm ent	Socal Services, Producti vity, Disabilit y	Crimi nal Activi ty/ Crimi nal Justic e	Infectious Diseases Conseque nces
MeSH and targeted search for cost of substance use disorders and specific outcome domains (non-duplicates)	471	5,297	623	791	916	7,727	1,828
Abstracts reviewed	45	182	114	131	129	207	143
Full text articles reviewed	20	18	5	19	13	23	14
Journal articles fully abstracted	N/A	3	1	4	8	8	5
National data and online sources abstractedb	N/A	4	3	N/A	N/A	N/A	N/A

Notes: Databases searched were PubMed, Google Scholar, EBSCOhost, Web of Science. Key words: “substance use disorder” or “substance abuse” combined with “cost,” “economic consequences,” “economic burden,” or “social costs.” For each outcome measure we used keywords “outcome” with the cost-related keywords above (e.g., “emergency department visits and cost”).

N/A = not applicable; SUD = substance use disorder; MeSH = Medical Subject Headings; MCF = monetary conversion factor; CMS = Centers for Medicare and Medicaid

^aMCFs were not selected from studies on the social costs of SUDs. We identified the cost sources used in the studies separately in our domain- and outcome-specific searches.

^bTwo sources (CMS data) used for both Medical and Behavioral Health Services. Final count of sources from which MCFs were abstracted is 34.