IDEAS home Printed from https://ideas.repec.org/a/ucp/amjhec/v2y2016i4p399-430.html
   My bibliography  Save this article

Health Plan Type Variations in Spells of Health-Care Treatment

Author

Listed:
  • Randall P. Ellis

    () (Boston University)

  • Wenjia Zhu

    (Boston University)

Abstract

This paper analyzes 30-day "treatment spells"—fixed-length periods that commence with a service after a gap in provider contact—to examine how health-care utilization and spending of insured employees at large firms are influenced by health plan types. We focus on differences between preferred provider organizations (PPOs) and two recent innovations: plans that feature a narrow panel of providers, and plans that allow free choice of providers but increase demand-side cost sharing: consumer-driven/high-deductible health plans. Health plan effect estimates change dramatically after controlling for endogenous plan type choice, and individual fixed effects. With these controls, narrow-panel plans reduce the probability of new treatment spells relative to PPOs by 34 percent with little effect on chronic, repeat visit spells. Visit reductions are more concentrated in less severe conditions in narrow-network plans, hence diagnostic coding on the remaining patients increases. We find no evidence that either narrow panel or higher-cost-sharing plans pay lower prices per procedure or have less intensive treatment given initiation of treatment. With controls, consumer-driven/high-deductible health plans are associated with higher total spending on procedures than PPO plans.

Suggested Citation

  • Randall P. Ellis & Wenjia Zhu, 2016. "Health Plan Type Variations in Spells of Health-Care Treatment," American Journal of Health Economics, University of Chicago Press, vol. 2(4), pages 399-430, Fall.
  • Handle: RePEc:ucp:amjhec:v:2:y:2016:i:4:p:399-430
    as

    Download full text from publisher

    File URL: https://www.journals.uchicago.edu/doi/pdf/10.1162/AJHE_a_00056
    Download Restriction: Access to the online full text or PDF requires a subscription.

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Amanda Kowalski, 2016. "Censored Quantile Instrumental Variable Estimates of the Price Elasticity of Expenditure on Medical Care," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 107-117, January.
    2. Jerome Dugan, 2015. "Trends in Managed Care Cost Containment: An Analysis of the Managed Care Backlash," Health Economics, John Wiley & Sons, Ltd., vol. 24(12), pages 1604-1618, December.
    3. Manning, Willard G, et al, 1987. "Health Insurance and the Demand for Medical Care: Evidence from a Randomized Experiment," American Economic Review, American Economic Association, vol. 77(3), pages 251-277, June.
    4. Liran Einav & Amy Finkelstein & Paul Schrimpf, 2015. "The Response of Drug Expenditure to Nonlinear Contract Design: Evidence from Medicare Part D," The Quarterly Journal of Economics, Oxford University Press, vol. 130(2), pages 841-899.
    5. Randall P. Ellis, 1986. "Rational Behavior in the Presence of Coverage Ceilings and Deductibles," RAND Journal of Economics, The RAND Corporation, vol. 17(2), pages 158-175, Summer.
    6. Patrick Bajari & Christina Dalton & Han Hong & Ahmed Khwaja, 2014. "Moral hazard, adverse selection, and health expenditures: A semiparametric analysis," RAND Journal of Economics, RAND Corporation, vol. 45(4), pages 747-763, December.
    7. Eichner, Matthew J, 1998. "The Demand for Medical Care: What People Pay Does Matter," American Economic Review, American Economic Association, vol. 88(2), pages 117-121, May.
    8. Michael Geruso & Timothy Layton, 2020. "Upcoding: Evidence from Medicare on Squishy Risk Adjustment," Journal of Political Economy, University of Chicago Press, vol. 128(3), pages 984-1026.
    9. Partha Deb & Pravin K. Trivedi, 2006. "Specification and simulated likelihood estimation of a non-normal treatment-outcome model with selection: Application to health care utilization," Econometrics Journal, Royal Economic Society, vol. 9(2), pages 307-331, July.
    10. A. Colin Cameron & Douglas L. Miller, 2015. "A Practitioner’s Guide to Cluster-Robust Inference," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 317-372.
    11. Manning, D. N., 1988. "Household demand for energy in the UK," Energy Economics, Elsevier, vol. 10(1), pages 59-78, January.
    12. Wennberg, David E. & Sharp, Sandra M. & Bevan, Gwyn & Skinner, Jonathan S. & Gottlieb, Daniel J. & Wennberg, John E., 2014. "A population health approach to reducing observational intensity bias in health risk adjustment: cross sectional analysis of insurance claims," LSE Research Online Documents on Economics 56671, London School of Economics and Political Science, LSE Library.
    13. Duarte, Fabian, 2012. "Price elasticity of expenditure across health care services," Journal of Health Economics, Elsevier, vol. 31(6), pages 824-841.
    14. Kate Bundorf, M., 2002. "Employee demand for health insurance and employer health plan choices," Journal of Health Economics, Elsevier, vol. 21(1), pages 65-88, January.
    15. Busch, Susan H. & Duchovny, Noelia, 2005. "Family coverage expansions: Impact on insurance coverage and health care utilization of parents," Journal of Health Economics, Elsevier, vol. 24(5), pages 876-890, September.
    16. Jonathan Gruber & Robin McKnight, 2016. "Controlling Health Care Costs through Limited Network Insurance Plans: Evidence from Massachusetts State Employees," American Economic Journal: Economic Policy, American Economic Association, vol. 8(2), pages 219-250, May.
    17. Keeler, Emmett B. & Rolph, John E., 1988. "The demand for episodes of treatment in the health insurance experiment," Journal of Health Economics, Elsevier, vol. 7(4), pages 337-367, December.
    18. Arlene Ash & Randall P. Ellis & Gregory Pope & John Ayanian & David Bates & Helen Burstin & Lisa Iezzoni & Elizabeth McKay & Wei Yu, 2000. "Using Diagnoses to Describe Populations and Predict Costs," Papers 0099, Boston University - Industry Studies Programme.
    19. Allison B. Rosen & Eli Liebman & Ana Aizcorbe & David M. Cutler, 2012. "Comparing Commercial Systems for Characterizing Episodes of Care," BEA Working Papers 0085, Bureau of Economic Analysis.
    20. Keeler, Emmett B. & Manning, Willard G. & Wells, Kenneth B., 1988. "The demand for episodes of mental health services," Journal of Health Economics, Elsevier, vol. 7(4), pages 369-392, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Thesis Thursday: Wenjia Zhu
      by Chris Sampson in The Academic Health Economists' Blog on 2018-06-21 06:00:42

    Citations

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


    Cited by:

    1. Denzil G. Fiebig, 2017. "Big Data: Will It Improve Patient-Centered Care?," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 10(2), pages 133-139, April.
    2. Chenyuan Liu & Justin R. Sydnor, 2018. "Dominated Options in Health-Insurance Plans," NBER Working Papers 24392, 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. Ellis, Randall P. & Martins, Bruno & Zhu, Wenjia, 2017. "Health care demand elasticities by type of service," Journal of Health Economics, Elsevier, vol. 55(C), pages 232-243.
    2. Lin, Haizhen & Sacks, Daniel W., 2019. "Intertemporal substitution in health care demand: Evidence from the RAND Health Insurance Experiment," Journal of Public Economics, Elsevier, vol. 175(C), pages 29-43.
    3. Kowalski, Amanda E., 2015. "Estimating the tradeoff between risk protection and moral hazard with a nonlinear budget set model of health insurance," International Journal of Industrial Organization, Elsevier, vol. 43(C), pages 122-135.
    4. David Powell & Dana Goldman, 2016. "Disentangling Moral Hazard and Adverse Selection in Private Health Insurance," NBER Working Papers 21858, National Bureau of Economic Research, Inc.
    5. Dunn, Abe, 2016. "Health insurance and the demand for medical care: Instrumental variable estimates using health insurer claims data," Journal of Health Economics, Elsevier, vol. 48(C), pages 74-88.
    6. David Powell & Dana P. Goldman, 2014. "Moral Hazard and Adverse Selection in Private Health Insurance," Working Papers WR-1032, RAND Corporation.
    7. Guo, Audrey & Zhang, Jonathan, 2019. "What to expect when you are expecting: Are health care consumers forward-looking?," Journal of Health Economics, Elsevier, vol. 67(C).
    8. Stefan Boes & Michael Gerfin, 2016. "Does Full Insurance Increase the Demand for Health Care?," Health Economics, John Wiley & Sons, Ltd., vol. 25(11), pages 1483-1496, November.
    9. Toshiaki Iizuka & Hitoshi Shigeoka, 2018. "Free for Children? Patient Cost-sharing and Healthcare Utilization," NBER Working Papers 25306, National Bureau of Economic Research, Inc.
    10. Liran Einav & Amy Finkelstein & Stephen P. Ryan & Paul Schrimpf & Mark R. Cullen, 2013. "Selection on Moral Hazard in Health Insurance," American Economic Review, American Economic Association, vol. 103(1), pages 178-219, February.
    11. Amanda Kowalski, 2016. "Censored Quantile Instrumental Variable Estimates of the Price Elasticity of Expenditure on Medical Care," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 107-117, January.
    12. Jianmei Zhao & Hai Zhong, 2015. "Medical expenditure in urban China: a quantile regression analysis," International Journal of Health Economics and Management, Springer, vol. 15(4), pages 387-406, December.
    13. Klein, Tobias J. & Salm, Martin & Upadhyay, Suraj, 2020. "The Response to Dynamic Incentives in Insurance Contracts with a Deductible: Evidence from a Differences-in-Regression-Discontinuities Design," IZA Discussion Papers 13108, Institute of Labor Economics (IZA).
    14. Quitterie Roquebert & Marianne Tenand, 2017. "Pay less, consume more? The price elasticity of home care for the disabled elderly in France," Health Economics, John Wiley & Sons, Ltd., vol. 26(9), pages 1162-1174, September.
    15. Hayen, Arthur & Klein, Tobias & Salm, Martin, 2018. "Does the framing of patient cost-sharing incentives matter? The effects of deductibles vs. no-claim refunds," CEPR Discussion Papers 12908, C.E.P.R. Discussion Papers.
    16. Dalton, Christina M., 2014. "Estimating demand elasticities using nonlinear pricing," International Journal of Industrial Organization, Elsevier, vol. 37(C), pages 178-191.
    17. Chung Jen Yang & Ying Che Tsai & Joseph J. Tien, 2017. "The Impacts of Persistent Behaviour and Cost-Sharing Policy on Demand for Outpatient Visits by the Elderly: Evidence from Taiwan’s National Health Insurance," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 42(1), pages 31-52, January.
    18. John F. Cogan & R. Glenn Hubbard & Daniel P. Kessler, 2007. "Evaluating Effects of Tax Preferences on Health Care Spending and Federal Revenues," NBER Chapters, in: Tax Policy and the Economy, Volume 21, pages 65-82, National Bureau of Economic Research, Inc.
    19. Zarek C. Brot-Goldberg & Amitabh Chandra & Benjamin R. Handel & Jonathan T. Kolstad, 2017. "What does a Deductible Do? The Impact of Cost-Sharing on Health Care Prices, Quantities, and Spending Dynamics," The Quarterly Journal of Economics, Oxford University Press, vol. 132(3), pages 1261-1318.
    20. Aviva Aron-Dine & Liran Einav & Amy Finkelstein & Mark Cullen, 2012. "Moral hazard in health insurance: How important is forward looking behavior?," Discussion Papers 11-007, Stanford Institute for Economic Policy Research.

    More about this item

    Keywords

    health-care spending; treatment spells; risk adjustment provider organizations; consumer-driven health plans;

    JEL classification:

    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets

    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:ucp:amjhec:v:2:y:2016:i:4:p:399-430. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Journals Division). General contact details of provider: https://www.journals.uchicago.edu/AJHE .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.