Skip to main content

Advertisement

SpringerLink
Log in

Responding to the US opioid crisis: leveraging analytics to support decision making

  • Current Opinion
  • Published:
Health Care Management Science Aims and scope Submit manuscript

Abstract

The US is experiencing a severe opioid epidemic with more than 80,000 opioid overdose deaths occurring in 2022. Beyond the tragic loss of life, opioid use disorder (OUD) has emerged as a major contributor to morbidity, lost productivity, mounting criminal justice system costs, and significant social disruption. This Current Opinion article highlights opportunities for analytics in supporting policy making for effective response to this crisis. We describe modeling opportunities in the following areas: understanding the opioid epidemic (e.g., the prevalence and incidence of OUD in different geographic regions, demographics of individuals with OUD, rates of overdose and overdose death, patterns of drug use and associated disease outbreaks, and access to and use of treatment for OUD); assessing policies for preventing and treating OUD, including mitigation of social conditions that increase the risk of OUD; and evaluating potential regulatory and criminal justice system reforms.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Data Availability

There is no dataset or code associated with this manuscript.

References

  1. Centers for Disease Control and Prevention (2023) The drug overdose epidemic: behind the numbers. Available at https://www.cdc.gov/opioids/data/index.html

  2. Centers for Disease Control and Prevention (2023) Provisional data shows U.S. drug overdose deaths top 100,000 in 2022. Available at https://blogs.cdc.gov/nchs/2023/05/18/7365/

  3. National Institute on Drug Abuse (2023) Drug overdose death rates. Available at https://nida.nih.gov/research-topics/trends-statistics/overdose-death-rates

  4. Statistica (2023) Number of military fatalities in all major wars involving the United States from 1775 to 2023. Available at https://www.statista.com/statistics/1009819/total-us-military-fatalities-in-american-wars-1775-present/

  5. Jalal H, Buchanich JM, Roberts MS et al (2018) Changing dynamics of the drug overdose epidemic in the United States from 1979 through 2016. Science 361:eaau1184. https://doi.org/10.1126/science.aau1184

    Article  Google Scholar 

  6. Jalal H, Buchanich JM, Sinclair DR, Roberts MS, Burke DS (2020) Age and generational patterns of overdose death risk from opioids and other drugs. Nat Med 26:699–704. https://doi.org/10.1038/s41591-020-0855-y

    Article  Google Scholar 

  7. Unick GJ, Ciccarone D (2017) US regional and demographic differences in prescription opioid and heroin-related overdose hospitalizations. Int J Drug Policy 46:112–119. https://doi.org/10.1016/j.drugpo.2017.06.003

    Article  Google Scholar 

  8. Jones CM, Shoff C, Hodges K et al (2022) Receipt of telehealth services, receipt and retention of medications for opioid use disorder, and medically treated overdose among Medicare beneficiaries before and during the COVID-19 pandemic. JAMA Psychiatry 79:981–992. https://doi.org/10.1001/jamapsychiatry.2022.2284

    Article  Google Scholar 

  9. Harris RA, Long JA, Bao Y, Mandell DS (2023) Racial, ethnic, and sex differences in methadone-involved overdose deaths before and after the US Federal policy change expanding take-home methadone doses. JAMA Health Forum 4:e231235. https://doi.org/10.1001/jamahealthforum.2023.1235

    Article  Google Scholar 

  10. Palzes VA, Chi FW, Metz VE et al (2023) Overall and telehealth addiction treatment utilization by age, race, ethnicity, and socioeconomic status in California after COVID-19 policy changes. JAMA Health Forum 4:e231018. https://doi.org/10.1001/jamahealthforum.2023.1018

    Article  Google Scholar 

  11. Hailu R, Mehrotra A, Huskamp HA, Busch AB, Barnett ML (2023) Telemedicine use and quality of opioid use disorder treatment in the US during the COVID-19 pandemic. JAMA Netw Open 6:e2252381. https://doi.org/10.1001/jamanetworkopen.2022.52381

    Article  Google Scholar 

  12. Reuter P, Caulkins JP, Midgette G (2021) Heroin use cannot be measured adequately with a general population survey. Addiction 116:2600–2609. https://doi.org/10.1111/add.15458

    Article  Google Scholar 

  13. Tatar M, Faraji MR, Keyes K, Wilson FA, Jalali MS (2023) Social vulnerability predictors of drug poisoning mortality: a machine learning analysis in the United States. Am J Addict Epub Ahead of Print. https://doi.org/10.1111/ajad.13445

    Article  Google Scholar 

  14. Keyes KM, Rutherford C, Hamilton A et al (2022) What is the prevalence of and trend in opioid use disorder in the United States from 2010 to 2019? Using multiplier approaches to estimate prevalence for an unknown population size. Drug Alcohol Depend Rep 3. https://doi.org/10.1016/j.dadr.2022.100052

  15. Hepler SA, Kline DM, Bonny A, McKnight E, Waller LA (2023) An integrated abundance model for estimating county-level prevalence of opioid misuse in Ohio. J R Stat Soc Ser a Stat Soc 186:43–60. https://doi.org/10.1093/jrsssa/qnac013

    Article  Google Scholar 

  16. Lu H, Crawford FW, Gonsalves GS, Grau LE (2023) Geographic and temporal trends in fentanyl-detected deaths in Connecticut, 2009–2019. Ann Epidemiol 79:32–38. https://doi.org/10.1016/j.annepidem.2023.01.009

    Article  Google Scholar 

  17. Fairley M, Rao IJ, Brandeau ML, Qian GL, Gonsalves GS (2022) Surveillance for endemic infectious disease outbreaks: adaptive sampling using profile likelihood estimation. Stat Med 41:3336–3348. https://doi.org/10.1002/sim.9420

    Article  Google Scholar 

  18. Caulkins JP, Disley E, Tzvetkova M et al (2016) Modeling the structure and operation of drug supply chains: the case of cocaine and heroin in Italy and Slovenia. Int J Drug Policy 31:64–73. https://doi.org/10.1016/j.drugpo.2016.02.003

    Article  Google Scholar 

  19. Lim TY, Stringfellow EJ, Stafford CA et al (2022) Modeling the evolution of the US opioid crisis for national policy development. Proc Natl Acad Sci U S A 119:e2115714119. https://doi.org/10.1073/pnas.2115714119

    Article  Google Scholar 

  20. Bjarnadottir MV, Anderson DB, Agarwal R, Nelson DA (2022) Aiding the prescriber: developing a machine learning approach to personalized risk modeling for chronic opioid therapy amongst US Army soldiers. Health Care Manag Sci 25:649–665. https://doi.org/10.1007/s10729-022-09605-4

    Article  Google Scholar 

  21. Sharma V, Kulkarni V, Jess E et al (2022) Development and validation of a machine learning model to estimate risk of adverse outcomes within 30 days of opioid dispensation. JAMA Netw Open 5:e2248559. https://doi.org/10.1001/jamanetworkopen.2022.48559

    Article  Google Scholar 

  22. Pitt AL, Humphreys K, Brandeau ML (2018) Modeling health benefits and harms of public policy responses to the US opioid epidemic. Am J Public Health 108:1394–1400. https://doi.org/10.2105/AJPH.2018.304590

    Article  Google Scholar 

  23. Rao IJ, Humphreys K, Brandeau ML (2021) Effectiveness of policies for controlling the US opioid epidemic: a model-based analysis from the Stanford-Lancet Commission on the North American Opioid Crisis. Lancet Reg Health - Americas 3:100031. https://doi.org/10.1016/j.lana.2021.100031

    Article  Google Scholar 

  24. Kim S, Suh HS (2023) A population-based study on the risk of prescription opioid abuse in patients with chronic opioid use and cost-effectiveness of prescription drug monitoring program using a patient simulation model in South Korea. Int J Drug Policy 112:103953. https://doi.org/10.1016/j.drugpo.2023.103953

    Article  Google Scholar 

  25. Magliocca NR, McSweeney K, Sesnie SE et al (2019) Modeling cocaine traffickers and counterdrug interdiction forces as a complex adaptive system. Proc Natl Acad Sci U S A 116:7784–7792. https://doi.org/10.1073/pnas.1812459116

    Article  Google Scholar 

  26. Tragler G, Caulkins JP, Feichtinger G (2001) Optimal dynamic allocation of treatment and enforcement in illicit drug control. Oper Res 49:352–362. https://doi.org/10.1287/opre.49.3.352.11215

    Article  Google Scholar 

  27. Case A, Deaton A (2020) Deaths of despair and the future of capitalism. Princeton University Press, Princeton, NJ

    Book  Google Scholar 

  28. Chatterjee A, Weitz M, Savinkina A et al (2023) Estimated costs and outcomes associated with use and nonuse of medications for opioid use disorder during incarceration and at release in Massachusetts. JAMA Netw Open 6:e237036. https://doi.org/10.1001/jamanetworkopen.2023.7036

    Article  Google Scholar 

  29. Claypool AL, DiGennaro C, Russell WA et al (2023) Cost-effectiveness of increasing buprenorphine treatment initiation, duration, and capacity among individuals who use opioids. JAMA Health Forum 4:e231080. https://doi.org/10.1001/jamahealthforum.2023.1080

    Article  Google Scholar 

  30. Enns B, Krebs E, Whitehurst DGT et al (2023) Cost-effectiveness of flexible take-home buprenorphine-naloxone versus methadone for treatment of prescription-type opioid use disorder. Drug Alcohol Depend 247:109893. https://doi.org/10.1016/j.drugalcdep.2023.109893

    Article  Google Scholar 

  31. Fairley M, Humphreys K, Joyce VR et al (2021) Cost-effectiveness of treatments for opioid use disorder. JAMA Psychiatry 78:767–777. https://doi.org/10.1001/jamapsychiatry.2021.0247

    Article  Google Scholar 

  32. Zaric GS, Barnett PG, Brandeau ML (2000) HIV transmission and the cost-effectiveness of methadone maintenance. Am J Public Health 90:1100–1111. https://doi.org/10.2105/ajph.90.7.1100

    Article  Google Scholar 

  33. Meltzer DO, Hoomans T, Chung JW, Basu A (2011) Minimal modeling approaches to value of information analysis for health research. Med Decis Making 31:E1–E22. https://doi.org/10.1177/0272989X11412975

    Article  Google Scholar 

  34. Williams AR, Nunes EV, Bisaga A, Levin FR, Olfson M (2019) Development of a Cascade of Care for responding to the opioid epidemic. Am J Drug Alcohol Abuse 45:1–10. https://doi.org/10.1080/00952990.2018.1546862

    Article  Google Scholar 

  35. Barrow JG, Fairley M, Brandeau ML (2020) Optimizing interventions across the HIV care continuum: process improvement analysis. Oper Res Health Care 25:100258. https://doi.org/10.1016/j.orhc.2020.100258

    Article  Google Scholar 

  36. Singer JA (2023) Overdose prevention centers: a successful strategy for preventing death and disease. Cato Institute. https://www.cato.org/briefing-paper/overdose-prevention-centers-successful-strategy-preventing-death-disease

  37. Zang X, Bessey SE, Krieger MS et al (2022) Comparing projected fatal overdose outcomes and costs of strategies to expand community-based distribution of naloxone in Rhode Island. JAMA Netw Open 5:e2241174. https://doi.org/10.1001/jamanetworkopen.2022.41174

    Article  Google Scholar 

  38. Kaplan EH, O’Keefe E (1993) Let the needles do the talking! Evaluating the New Haven Needle Exchange. Interfaces 23:7–26. https://doi.org/10.1287/inte.23.1.7

    Article  Google Scholar 

  39. Bayoumi AM, Zaric GS (2008) The cost-effectiveness of Vancouver’s supervised injection facility. CMAJ 179:1143–1151. https://doi.org/10.1503/cmaj.080808

    Article  Google Scholar 

  40. Homer J, Wakeland W (2021) A dynamic model of the opioid drug epidemic with implications for policy. Am J Drug Alcohol Abuse 47:5–15. https://doi.org/10.1080/00952990.2020.1755677

    Article  Google Scholar 

  41. Abel-Ollo K (2022) What lessons from Estonia’s experience could be applied in the United States in response to the addiction and overdose crisis? Addiction 117:1188–1189. https://doi.org/10.1111/add.15833

    Article  Google Scholar 

  42. Buchanan AS, Latkin CA (2008) Drug use in the social networks of heroin and cocaine users before and after drug cessation. Drug Alcohol Depend 96:286–289. https://doi.org/10.1016/j.drugalcdep.2008.03.008

    Article  Google Scholar 

  43. Substance Abuse and Mental Health Services Administration (2020) Leveraging Existing Health and Disease Management Programs to Provide Mental Health and Substance Use Disorder Resources During the COVID-19 Public Health Emergency (PHE). Available at https://www.samhsa.gov/coronavirus

  44. Substance Abuse and Mental Health Services Administration (2020) Methadone Take-Home Flexibilities Extension Guidance. Available at https://www.samhsa.gov/medications-substance-use-disorders/statutes-regulations-guidelines/methadone-guidance

  45. Qian G, Rao IJ, Humphreys K, Owens DK, Brandeau ML (2023) Cost-effectiveness of office-based buprenorphine treatment for opioid use disorder. Drug Alcohol Depend 243:109762. https://doi.org/10.1016/j.drugalcdep.2022.109762

    Article  Google Scholar 

  46. United Nations AIDS, Programme (2016) UNAIDS urges countries to adopt a people-, rights- and health-centred approach to reverse the HIV epidemic among people who inject drugs. UNAIDS. Available at http://www.unaids.org/en/resources/presscentre/pressreleaseandstatementarchive/2016/april/20160415_UNGASS

  47. Caulkins JP, Gould A, Pardo B, Reuter P, Stein BD (2021) Opioids and the criminal justice system: new challenges posed by the modern opioid epidemic. Ann Rev Criminology 4:353–375. https://doi.org/10.1146/annurev-criminol-061020-125715

    Article  Google Scholar 

  48. Humphreys K, Shover CL, Andrews CM et al (2022) Responding to the opioid crisis in North America and beyond: recommendations of the Stanford-Lancet Commission. Lancet 399:555–604. https://doi.org/10.1016/S0140-6736(21)02252-2

    Article  Google Scholar 

  49. Bernard CM, Rao IJ, Robison KK, Brandeau ML (2020) Health outcomes and cost-effectiveness of diversion programs for low-level drug offenders: a model-based analysis. PLoS Med 17:1003239. https://doi.org/10.1371/journal.pmed.1003239

    Article  Google Scholar 

  50. Downey PM, Roman J (2010) A Bayesian meta-analysis of drug court cost-effectiveness. District of Columbia Crime Policy Institute, Washington, DC

    Google Scholar 

  51. Shanahan M, Lancsar E, Haas M et al (2004) Cost-effectiveness analysis of the New South Wales adult drug court program. Eval Rev 28:3–27. https://doi.org/10.1177/0193841X03257531

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by Grant R37-DA15612 from the National Institute on Drug Abuse.

Author information

Authors and Affiliations

  1. Department of Management Science and Engineering, Stanford University, Stanford, CA, USA

    Margaret L. Brandeau

Authors
  1. Margaret L. Brandeau
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Margaret L. Brandeau.

Ethics declarations

Conflict of interest

The author has no competing financial or other interest to declare.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Brandeau, M.L. Responding to the US opioid crisis: leveraging analytics to support decision making. Health Care Manag Sci 26, 599–603 (2023). https://doi.org/10.1007/s10729-023-09657-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10729-023-09657-0

Keywords

Search

Navigation