Cost-Effectiveness of Publicly Funded Treatment of Opioid Use Disorder in California

Limited access to opioid agonist treatment (OAT) with either methadone or buprenorphine is a major impediment to reducing the societal burden of the current prescription opioid and heroin use epidemic (1, 2). The number of Americans with an opioid use disorder has increased from 1.4 million in 2003 to nearly 2.4 million in 2015 (1, 3). Meanwhile, rates of use of opioid use disorder treatment did not increase between 2003 and 2013, after adjustment for changing population characteristics (4), and in 2015 nearly 80% of persons with an opioid use disorder did not receive treatment (5). California has the largest number of persons with an opioid use disorder in the United States (Substance Abuse and Mental Health Services Administration. Unpublished data.). Fewer than half of Californians who received treatment in 2014 received the international evidence-based standard of care, with both initial access to OAT and no restriction on the duration of treatment (hereafter, OAT refers to this standard of care) (69). Regulations to receive opioid use disorder treatment in California's opioid treatment programs are more stringent than federal regulations, notably limiting the duration of medically managed withdrawal to 21 days and requiring documentation of 2 or more failed treatments with medically managed withdrawal before OAT can be started (10). Although individual and programmatic exemptions are available and believed to be widely applied (11), the language remains part of state clinical guidelines, despite acknowledgment by the California Society of Addiction Medicine that medically managed withdrawal by itself should not be considered treatment of opioid use disorder (10). Limiting the term of treatment is inconsistent with the disease course of opioid use disorder. The scientific and medical community acknowledges that opioid use disorder is a chronic, recurrent disorder with patterns of adherence to treatment and relapse rates that are similar to those of other chronic disorders, such as hypertension, diabetes, and asthma (8, 12). Moreover, a 30-fold increase in risk for death in the 2 weeks after treatment interruption underlines the serious risks associated with limited-term treatment of opioid use disorder (13). We aimed to determine the cost-effectiveness of OAT for all persons initially presenting with opioid use disorder to California's publicly funded treatment facilities compared with the observed standard of care, in which most patients initiate treatment with time-limited medically managed withdrawal. We further compared evidence-based care to that currently recommended in California's clinical guidelines to show the value of immediate access to OAT for all treatment recipients. Methods Overview To determine the benefits and costs of opioid use disorder treatment in California's publicly funded opioid treatment programs, we modeled the representative patient population as 35-year-old patients receiving initial treatment of opioid use disorder, 35.8% of whom were women and 62.9% of whom primarily used heroin (as opposed to prescription opioids) (Table 1) (13, 14). The baseline prevalence of HIV infection in the model was 7.1% (15). Table 1. Estimates for Key Model Parameters* We compared California's observed standard of care, in which 54.3% of patients initiate opioid use disorder treatment with mandated, short-term, medically managed withdrawal (hereafter referred to as observed California care) (14), with a hypothetical strategy in which all patients have immediate access to OAT with methadone of unrestricted duration (hereafter referred to as initial OAT), thus eliminating the possibility of offering short-term medically managed withdrawal. We also modeled current practice recommended by California clinical guidelines, which require documentation of 2 or more failed treatments with medically managed withdrawal before OAT with methadone can be started (hereafter referred to as California guideline) (Supplement Table 1) (10). Supplement. Supplementary Material Model outcomes also included mortality, HIV seroconversion, and incarceration. We adhered to economic modeling recommendations in all phases of model design and implementation (37, 38). Model Description We adapted a semi-Markov cohort model that had been published previously (16) to capture the chronic, recurrent nature of opioid use disorder. The model consisted of mutually exclusive health states seen in long-term observational studies of persons with opioid use disorder (3941). Patients entered the model in their first treatment of opioid use disorder and progressed through periods of treatment, relapse, incarceration, and abstinence from opioids until death. Given the elevated risk for death immediately after treatment discontinuation (13, 42), the model distinguished between the first month of opioid use outside of treatment (acute relapse state) and subsequent periods of relapse. Patients could transition between health states every month until death and could die from any health state, and HIV seroconversion could occur at any stage in the model (the dynamics of the model are shown in Supplement Figure 1). We assessed the model's internal and external validity by comparing projected mortality, HIV incidence, and proportion of time spent in treatment with observed outcomes (Supplement). Analyses were done using R Project software (43). Data In California, treatment in a publicly funded opioid treatment program predominantly entails receiving methadone, as opposed to buprenorphine (44), and each program licensed to dispense methadone is required to submit treatment data to the California Outcomes Measurement System on a monthly basis (11). Data from this system were linked to statewide databases from the Department of Justice, the California Department of Corrections and Rehabilitation, and the National Death Index (13, 14, 17). We derived model parameters using individual-level linked administrative databases with comprehensive longitudinal information on drug treatment and criminal justice system interactions for California where possible (Table 1; Section 2.0 of the Supplement) (11, 13, 14, 17). We accounted for distinctions in treatment course and outcomes of primary users of prescription opioids and heroin (11, 13, 14, 17), as well as stratifying the model by HIV serostatus. A new treatment cycle was defined each time a patient reentered treatment and subsequent episodes of treatment were longer and relapse shorter on the basis of prior findings (45). Given that short-term medically managed withdrawal is mandated in California (10), we assumed that all patients would transition out of withdrawal after 1 monthly period, and we explicitly modeled empirically observed transitions from medically managed withdrawal to OAT (Table 1) (14). Statistical Analysis Primary Analysis The primary model-projected outcomes included health benefits, measured with accumulated quality-adjusted life-years (QALYs), and lifetime costs (in 2016 U.S. dollars). Analyses were done from a societal perspective (see Supplement Tables 2 and 3, for an impact inventory and reporting checklist), and as recommended, we also reported the results from the health care sector perspective (37). Patients accumulated costs associated with opioid use disorder treatment, antiretroviral treatment of HIV, other health care resource use, and criminal activity (Table 1) (17). Costs of crime were age-dependent; were estimated in 5-year increments; and comprised costs of policing, court, corrections, and criminal victimization (Section 2.3.3 of the Supplement). We applied health statespecific QALY weights derived from the peer-reviewed literature, adjusting for primary substance used and HIV serostatus (Table 1; Section 2.4 of the Supplement). We estimated incremental cost-effectiveness ratios for the initial OAT group compared with the observed California care and California guideline groups over a lifetime horizon to capture differences in future outcomes. The analysis conformed to good practice guidelines on cost-effectiveness analyses (see Supplement Table 4 for a Consolidated Health Economic Evaluation Reporting Standards checklist) (4648), and both costs and QALYs are reported in present value using a 3% annual discount rate. We also compared lifetime HIV seroconversion rates, mortality, and months of incarceration over the model's midpoint (30-year). Finally, we projected potential lifetime savings associated with the initial OAT strategy for a hypothetical 1-year cohort of patients receiving initial opioid use disorder treatment by multiplying the latest available data for those starting treatment in California (2014) (49) by estimated cost savings, differentiating between those who primarily use prescription opioids and those who use heroin. Sensitivity Analysis We did probabilistic sensitivity analysis to evaluate the robustness of the results to parameter uncertainty. Distributions were developed for each model parameter, and we did 2000 simulations while sampling all parameters simultaneously (Section 3.0 of the Supplement). One-way sensitivity analyses were performed to determine the effect of varying model parameters and critical model assumptions (Section 3.2 of the Supplement), and we did additional conditional sensitivity analyses to examine the effect of variation in the value of 1 parameter on cost-effectiveness. We conducted an additional sensitivity analysis to address potential selection bias in our nonrandomized OAT and medically managed withdrawal observational care data, in which patients selected for OAT may have been more likely to have better outcomes. We did a threshold analysis to determine when OAT would no longer generate savings if durability were reduced. Role of the Funding Source This study was funded by grants from the National Institute on Drug Abuse, which had no direct role in the design, conduct, and analysis of the study or in the decision to