IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/29373.html
   My bibliography  Save this paper

The Effect of Medicaid on Care and Outcomes for Chronic Conditions: Evidence from the Oregon Health Insurance Experiment

Author

Listed:
  • Heidi Allen
  • Katherine Baicker

Abstract

Health insurance may play an important role not only in immediate access to care but in the management of chronic disease, which would have implications for long-run care needs as well as health outcomes. Such causal connections are often difficult to establish, but we use Oregon’s 2008 Medicaid lottery to assess the management of diabetes and asthma, as well as several markers of physical health. This analysis complements several prior studies by introducing new data elements and by analyzing chronically ill subpopulations. While we had previously found that having insurance increases the diagnosis and use of medication for diabetes, we show here that it does not significantly increase the likelihood of diabetic patients receiving recommended care such as eye exams and regular blood sugar monitoring, nor does it improve the management of patients with asthma. We also find no effect on measures of physical health including pulse, obesity, or blood markers of chronic inflammation. Effects of Medicaid on health care utilization appear similar for those with and without pre-lottery diagnoses of chronic physical health conditions. Thus, while Medicaid is an important determinant of access to care overall, it does not appear that Medicaid alone has detectable effects on the management of several chronic physical health conditions, at least over the first two years in this setting. However, sample limitations highlight the value of additional research.

Suggested Citation

  • Heidi Allen & Katherine Baicker, 2021. "The Effect of Medicaid on Care and Outcomes for Chronic Conditions: Evidence from the Oregon Health Insurance Experiment," NBER Working Papers 29373, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:29373
    Note: EH PE AG
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w29373.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    2. Abadie, Alberto, 2003. "Semiparametric instrumental variable estimation of treatment response models," Journal of Econometrics, Elsevier, vol. 113(2), pages 231-263, April.
    3. Abadie A., 2002. "Bootstrap Tests for Distributional Treatment Effects in Instrumental Variable Models," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 284-292, March.
    4. Katherine Baicker & Amy Finkelstein & Jae Song & Sarah Taubman, 2014. "The Impact of Medicaid on Labor Market Activity and Program Participation: Evidence from the Oregon Health Insurance Experiment," American Economic Review, American Economic Association, vol. 104(5), pages 322-328, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Claire E. Boone & Pablo A. Celhay & Paul Gertler & Tadeja Gracner, 2023. "Encouraging Preventative Care to Manage Chronic Disease at Scale," NBER Working Papers 31643, National Bureau of Economic Research, Inc.

    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. Seojeong Lee, 2018. "A Consistent Variance Estimator for 2SLS When Instruments Identify Different LATEs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(3), pages 400-410, July.
    2. Imbens, Guido W., 2014. "Instrumental Variables: An Econometrician's Perspective," IZA Discussion Papers 8048, Institute of Labor Economics (IZA).
    3. Joshua D. Angrist, 2022. "Empirical Strategies in Economics: Illuminating the Path From Cause to Effect," Econometrica, Econometric Society, vol. 90(6), pages 2509-2539, November.
    4. Atila Abdulkadiroğlu & Joshua D. Angrist & Susan M. Dynarski & Thomas J. Kane & Parag A. Pathak, 2011. "Accountability and Flexibility in Public Schools: Evidence from Boston's Charters And Pilots," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 126(2), pages 699-748.
    5. Huber, Martin & Wüthrich, Kaspar, 2017. "Evaluating local average and quantile treatment effects under endogeneity based on instruments: a review," FSES Working Papers 479, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    6. Pedro H. C. Sant'Anna & Xiaojun Song & Qi Xu, 2022. "Covariate distribution balance via propensity scores," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1093-1120, September.
    7. Joshua D. Angrist, 2004. "Treatment effect heterogeneity in theory and practice," Economic Journal, Royal Economic Society, vol. 114(494), pages 52-83, March.
    8. Joshua D. Angrist & Sarah R. Cohodes & Susan M. Dynarski & Parag A. Pathak & Christopher R. Walters, 2016. "Stand and Deliver: Effects of Boston's Charter High Schools on College Preparation, Entry, and Choice," Journal of Labor Economics, University of Chicago Press, vol. 34(2), pages 275-318.
    9. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2013. "Program evaluation with high-dimensional data," CeMMAP working papers CWP77/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Huber Martin & Wüthrich Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-27, January.
    11. Hsu, De Fen & Morrill, Melinda & Pathak, Aditi, 2024. "Health and retirement: Heterogeneity in the responsiveness to pension incentives," Economics Letters, Elsevier, vol. 238(C).
    12. Sloczynski, Tymon, 2018. "A General Weighted Average Representation of the Ordinary and Two-Stage Least Squares Estimands," IZA Discussion Papers 11866, Institute of Labor Economics (IZA).
    13. Patrick Kline & Christopher R. Walters, 2019. "On Heckits, LATE, and Numerical Equivalence," Econometrica, Econometric Society, vol. 87(2), pages 677-696, March.
    14. Markus Frölich & Martin Huber, 2017. "Direct and indirect treatment effects–causal chains and mediation analysis with instrumental variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1645-1666, November.
    15. McLaughlin, Joanne Song, 2017. "Does Communist party membership pay? Estimating the economic returns to party membership in the labor market in China," Journal of Comparative Economics, Elsevier, vol. 45(4), pages 963-983.
    16. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    17. Eva Deuchert & Martin Huber, 2017. "A Cautionary Tale About Control Variables in IV Estimation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(3), pages 411-425, June.
    18. Yumou Qiu & Jing Tao & Xiao‐Hua Zhou, 2021. "Inference of heterogeneous treatment effects using observational data with high‐dimensional covariates," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(5), pages 1016-1043, November.
    19. Stephan Litschig & Yves Zamboni, 2008. "Judicial presence and rent extraction," Economics Working Papers 1143, Department of Economics and Business, Universitat Pompeu Fabra, revised Dec 2012.
    20. Peter Hull & Michal Kolesár & Christopher Walters, 2022. "Labor by design: contributions of David Card, Joshua Angrist, and Guido Imbens," Scandinavian Journal of Economics, Wiley Blackwell, vol. 124(3), pages 603-645, July.

    More about this item

    JEL classification:

    • I1 - Health, Education, and Welfare - - Health
    • I13 - Health, Education, and Welfare - - Health - - - Health Insurance, Public and Private

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:nbr:nberwo:29373. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.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.