Tackling the opioid crisis: How decision analytic modeling can inform funding decisions

By Tara Lavelle, PhD, Assistant Professor, Maitreyi Bandlamudi, BS, Boston University School of Public Health, & Elizabeth Sherman, BS, Harvard University School of Public Health

Reports that Purdue Pharma, the makers of OxyContin, offered to settle more than 2,000 lawsuits from U.S. states and cities for $10 to $12 billion, and that Johnson & Johnson would be forced to pay Oklahoma over half a billion dollars for its role in the opioid crisis, is welcome news.  Going forward, the key question is how the money from settlements will be spent by states and cities on prevention and treatment services to best address and mitigate the epidemic.

Economic evaluations that compare the costs versus benefits of policy initiatives can provide valuable guidance on the mix of interventions that provide the greatest benefit with available funding.  They have been used successfully to help address other serious public health problems in the U.S., including the HIV/AIDS and influenza epidemics, and can provide guidance on effective ways to optimize the use of resources available to combat the opioid crisis. They can also be customized for different settings with different resources available, and varied rates of opioid use and overdose. 

To date, states have invested in a range of prevention and treatment programs, including prescription drug monitoring systems, medication-assisted treatment (MAT), and expanded access to naloxone, a drug that can counter the effects of an opioid overdose.  Funding has come from varied sources, but much of the financial burden has fallen on the states. All 51 Medicaid programs cover at least one medication used as part of MAT and between 2011 and 2016, spending on Medicaid-covered prescriptions used to treat opioid addiction and overdose increased from $394 million to $930 million.1 To ease the burden on states, the federal government allotted approximately 7.5 billion dollars to states to help pay for opioid addiction programs in 2018.

Mitigating the opioid crisis will require an enduring, multi-pronged approach that is tailored to different settings. Effective policy decisions cannot be made without considering the cost-effectiveness of alternative strategies, especially when states are receiving large amounts of funds.  Unfortunately, states currently have limited evidence to guide their funding decisions as cost-effectiveness information on opioid-related programs is scarce.

Among the available evidence, some studies have found the distribution of naloxone to be cost-effective (less than $100,000 per quality-adjusted life year gained). However, several of these studies, such as those evaluating the distribution of naloxone in Canadian high schools,2 among heroin3 or injectable drug users,4 or those co-infected with HIV and hepatitis C,5 focus on specific circumstances, populations, and settings  and may not be widely applicable. They also do not evaluate the use of naloxone in combination with other ongoing policy options. Broader cost-effectiveness analyses focused on alternative public policy options may better assist state officials prioritize funding.   For example, a cost-effectiveness analysis of a publicly-funded opioid agonist treatment (OAT) in California found the program to save money and improve health relative to the current standard of care.6 The analysis projected that, in a hypothetical scenario in which all Californians starting treatment for opioid use disorder in 2014 had immediate access to OAT, lifetime savings could be as high as $3.8 billion.  However, few such studies are available to guide policy making. 

The lack of health economic data is not unique to the opioid crisis.  However, the scarcity of cost-effectiveness evidence is particularly pronounced for health interventions related to substance abuse and mental health disorders, two areas crucial to fighting the opioid crisis.7  With few exceptions (e.g., the Centers for Disease Control and Prevention’s use of cost-effectiveness research to help guide immunization decisions), economic evidence has infrequently been used at the federal or state levels to inform policy decisions. As an exception, Washington State conducts and uses benefit-cost analyses to help guide public funding decisions. The Washington State Institute for Public Policy (WSIPP) conducts benefit-cost studies to ensure that policies are “evidence-based,” and has researched multiple opioid-related programs, including methadone maintenance, buprenorphine maintenance, and cognitive-behavioral coping-skills therapy for opioid use disorder.

More such studies are needed. Developing decision analytic models that examine the potential cost-effectiveness of a broad range of interventions and policies for opioid use disorder, but are tailored to local circumstances, can best inform state policy and use of funding.


  1. Clemans-Cope L, Epstein M, Kenney GM. Rapid growth in Medicaid spending on medications to treat opioid use disorder and overdose. 2017.
  2.  Cipriano LE, Zaric GS. Cost-effectiveness of naloxone kits in secondary schools. Drug Alcohol Depend. 2018;192:352-361.
  3. Coffin PO, Sullivan SD. Cost-effectiveness of distributing naloxone to heroin users for lay overdose reversal in Russian cities. J Med Econ. 2013;16(8):1051-1060.
  4. Uyei J, Fiellin DA, Buchelli M, Rodriguez-Santana R, Braithwaite RS. Effects of naloxone distribution alone or in combination with addiction treatment with or without pre-exposure prophylaxis for HIV prevention in people who inject drugs: a cost-effectiveness modelling study. Lancet Public Health. 2017;2(3):e133-e140.
  5. Barocas JA, Morgan JR, Fiellin DA, et al. Cost-effectiveness of integrating buprenorphine-naloxone treatment for opioid use disorder into clinical care for persons with HIV/hepatitis C co-infection who inject opioids. Int J Drug Policy. 2019;72:160-168.
  6. Krebs E, Enns B, Evans E, et al. Cost-Effectiveness of Publicly Funded Treatment of Opioid Use Disorder in California. Ann Intern Med. 2018;168(1):10-19.
  7. Neumann PJ, Farquhar M, Wilkinson CL, Lowry M, Gold M. Lack of Cost-Effectiveness Analyses to Address Healthy People 2020 Priority Areas. Am J Public Health. 2016;106(12):2205-2207.
Tackling the opioid crisis: How decision analytic modeling can inform funding decisions

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