IDEAS home Printed from https://ideas.repec.org/a/aea/aejpol/v10y2018i1p77-112.html
   My bibliography  Save this article

The Effect of Prescription Drug Monitoring Programs on Opioid Utilization in Medicare

Author

Listed:
  • Thomas C. Buchmueller
  • Colleen Carey

Abstract

The misuse of prescription opioids has become a serious epidemic in the United States. In response, states have implemented Prescription Drug Monitoring Programs (PDMPs), which record a patient's opioid prescribing history. While few providers participated in early systems, states have recently begun to require providers to access the PDMP under certain circumstances. We find that "must access" PDMPs significantly reduce measures of misuse in Medicare Part D. In contrast, we find that PDMPs without such provisions have no effect. We find stronger effects when providers are required to access the PDMP under broad circumstances, not only when they are suspicious.

Suggested Citation

  • Thomas C. Buchmueller & Colleen Carey, 2018. "The Effect of Prescription Drug Monitoring Programs on Opioid Utilization in Medicare," American Economic Journal: Economic Policy, American Economic Association, vol. 10(1), pages 77-112, February.
    • Handle: RePEc:aea:aejpol:v:10:y:2018:i:1:p:77-112
    Note: DOI: 10.1257/pol.20160094
    as

    Download full text from publisher

    File URL: https://www.aeaweb.org/articles?id=10.1257/pol.20160094
    Download Restriction: no
    File URL: https://www.aeaweb.org/content/file?id=6410
    Download Restriction: no
    File URL: https://www.aeaweb.org/articles/attachments?retrieve=VeDwvOdBFGxxPHAv2aeV4vW8CANziZF4
    Download Restriction: no
    File URL: https://www.aeaweb.org/articles/attachments?retrieve=o3pr5BPOSr5d-zJ49PZ1OujXxepDaXS8
    Download Restriction: Access to full text is restricted to AEA members and institutional subscribers.
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Borgschulte, Mark & Corredor-Waldron, Adriana & Marshall, Guillermo, 2018. "A path out: Prescription drug abuse, treatment, and suicide," Journal of Economic Behavior & Organization, Elsevier, vol. 149(C), pages 169-184.
    2. Abby Alpert & David Powell & Rosalie Liccardo Pacula, 2017. "Supply-Side Drug Policy in the Presence of Substitutes: Evidence from the Introduction of Abuse-Deterrent Opioids," NBER Working Papers 23031, National Bureau of Economic Research, Inc.
    3. Anne Case & Angua Deaton, 2015. "Rising morbidity and mortality in midlife among white non-Hispanic Americans in the 21st century," Working Papers 15078.full.pdf, Princeton University, Woodrow Wilson School of Public and International Affairs, Research Program in Development Studies..
    4. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    5. Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004. "How Much Should We Trust Differences-In-Differences Estimates?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(1), pages 249-275.
    6. Brewer Mike & Crossley Thomas F. & Joyce Robert, 2018. "Inference with Difference-in-Differences Revisited," Journal of Econometric Methods, De Gruyter, vol. 7(1), pages 1-16, January.
    7. Davis, C.S. & Pierce, M. & Dasgupta, N., 2014. "Evolution and convergence of state laws governing controlled substance prescription monitoring programs, 1998-2011," American Journal of Public Health, American Public Health Association, vol. 104(8), pages 1389-1395.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bobonis, Gustavo J. & Stabile, Mark & Tovar, Leonardo, 2020. "Military training exercises, pollution, and their consequences for health," Journal of Health Economics, Elsevier, vol. 73(C).
    2. MacKinnon, James G. & Nielsen, Morten Ørregaard & Webb, Matthew D., 2023. "Cluster-robust inference: A guide to empirical practice," Journal of Econometrics, Elsevier, vol. 232(2), pages 272-299.
    3. Cockx, Bart & Ghirelli, Corinna, 2016. "Scars of recessions in a rigid labor market," Labour Economics, Elsevier, vol. 41(C), pages 162-176.
    4. Huebener, Mathias & Marcus, Jan, 2017. "Compressing instruction time into fewer years of schooling and the impact on student performance," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 58, pages 1-14.
    5. Luca Aguzzoni & Benno Buehler & Luca Martile & Ron Kemp & Anton Schwarz, 2018. "Ex-post Analysis of Mobile Telecom Mergers: The Case of Austria and The Netherlands," De Economist, Springer, vol. 166(1), pages 63-87, March.
    6. Arun Advani & Tymon Słoczyński, 2013. "Mostly harmless simulations? On the internal validity of empirical Monte Carlo studies," CeMMAP working papers 64/13, Institute for Fiscal Studies.
    7. Matthew D. Webb, 2023. "Reworking wild bootstrap‐based inference for clustered errors," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 56(3), pages 839-858, August.
    8. Arun Advani & Toru Kitagawa & Tymon Słoczyński, 2019. "Mostly harmless simulations? Using Monte Carlo studies for estimator selection," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(6), pages 893-910, September.
    9. Slawa Rokicki & Jessica Cohen & Gunther Fink & Joshua Salomon & Mary Beth Landrum, 2018. "Inference with difference-in-differences with a small number of groups: a review, simulation study and empirical application using SHARE data," CHaRMS Working Papers 18-01, Centre for HeAlth Research at the Management School (CHaRMS).
    10. Charlotte Senftleben-König, "undated". "Product Market Deregulation and Employment Outcomes: Evidence from the German Retail Sector," BDPEMS Working Papers 2014009, Berlin School of Economics.
    11. Bruno Ferman, 2023. "Inference in difference‐in‐differences: How much should we trust in independent clusters?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 358-369, April.
    12. Brewer, Mike & Crossley, Thomas F. & Zilio, Federico, 2019. "What Do We Really Know about the Employment Effects of the UK's National Minimum Wage?," IZA Discussion Papers 12369, Institute of Labor Economics (IZA).
    13. Bruno Ferman & Cristine Pinto, 2019. "Inference in Differences-in-Differences with Few Treated Groups and Heteroskedasticity," The Review of Economics and Statistics, MIT Press, vol. 101(3), pages 452-467, July.
    14. repec:fgv:eesptd:411 is not listed on IDEAS
    15. James G. MacKinnon & Matthew D. Webb, 2020. "When and How to Deal with Clustered Errors in Regression Models," Working Paper 1421, Economics Department, Queen's University.
    16. Sumedha Gupta & Morhaf Al Achkar & Bradley Ray, 2022. "Are prescription drug monitoring laws effective for all? Evidence from administrative data," Contemporary Economic Policy, Western Economic Association International, vol. 40(1), pages 28-47, January.
    17. Cohle, Zachary & Ortega, Alberto, 2023. "The effect of the opioid crisis on patenting," Journal of Economic Behavior & Organization, Elsevier, vol. 214(C), pages 493-521.
    18. Cantoni, Enrico & Gazzè, Ludovica & Schafer, Jerome, 2021. "Turnout in concurrent elections: Evidence from two quasi-experiments in Italy," European Journal of Political Economy, Elsevier, vol. 70(C).
    19. Martin Huber, 2019. "An introduction to flexible methods for policy evaluation," Papers 1910.00641, arXiv.org.
    20. Christopher J. Ruhm, 2018. "Deaths of Despair or Drug Problems?," NBER Working Papers 24188, National Bureau of Economic Research, Inc.
    21. Grönqvist, Hans & Niknami, Susan, 2014. "Alcohol availability and crime: Lessons from liberalized weekend sales restrictions," Journal of Urban Economics, Elsevier, vol. 81(C), pages 77-84.

    More about this item

    JEL classification:

    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aea:aejpol:v:10:y:2018:i:1:p:77-112. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Michael P. Albert (email available below). General contact details of provider: https://edirc.repec.org/data/aeaaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.