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Estimating Heterogeneity in the Benefits of Medical Treatment Intensity

Author

Listed:
  • William N. Evans

    (Department of Economics, University of Notre Dame)

  • Craig Garthwaite

    (Department of Management and Strategy, Kellogg School of Management, Northwestern University)

Abstract

We exploit increases in postpartum length of stay generated by legislative changes in the late 1990s to identify the impact of greater hospital care on the health of newborns. Using all births in California over the 1995–2000 period, two-stage least-square estimates show that increased treatment intensity had a modest impact on readmission probabilities for the average newborn. Allowing the treatment effect to vary by two objective measures of medical need demonstrates that the law had large impacts for those with the greatest likelihood of a readmission. The results suggest that the returns to average and marginal patients vary considerably in this context. © 2012 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Suggested Citation

  • William N. Evans & Craig Garthwaite, 2012. "Estimating Heterogeneity in the Benefits of Medical Treatment Intensity," The Review of Economics and Statistics, MIT Press, vol. 94(3), pages 635-649, August.
  • Handle: RePEc:tpr:restat:v:94:y:2012:i:3:p:635-649
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    1. Amitabh Chandra & Douglas O. Staiger, 2007. "Productivity Spillovers in Health Care: Evidence from the Treatment of Heart Attacks," Journal of Political Economy, University of Chicago Press, vol. 115(1), pages 103-140.
    2. James J. Heckman & Sergio Urzua & Edward Vytlacil, 2006. "Understanding Instrumental Variables in Models with Essential Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 389-432, August.
    3. Marianne P. Bitler & Jonah B. Gelbach & Hilary W. Hoynes, 2006. "What Mean Impacts Miss: Distributional Effects of Welfare Reform Experiments," American Economic Review, American Economic Association, vol. 96(4), pages 988-1012, September.
    4. Amy Finkelstein & Robin McKnight, 2005. "What Did Medicare Do (And Was It Worth It)?," NBER Working Papers 11609, National Bureau of Economic Research, Inc.
    5. Alberto Abadie & Joshua Angrist & Guido Imbens, 2002. "Instrumental Variables Estimates of the Effect of Subsidized Training on the Quantiles of Trainee Earnings," Econometrica, Econometric Society, vol. 70(1), pages 91-117, January.
    6. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects, and Econometric Policy Evaluation," Econometrica, Econometric Society, vol. 73(3), pages 669-738, May.
    7. Douglas Almond & Joseph J. Doyle & Amanda E. Kowalski & Heidi Williams, 2010. "Estimating Marginal Returns to Medical Care: Evidence from At-risk Newborns," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(2), pages 591-634.
    8. Douglas Almond & Joseph J. Doyle, 2011. "After Midnight: A Regression Discontinuity Design in Length of Postpartum Hospital Stays," American Economic Journal: Economic Policy, American Economic Association, vol. 3(3), pages 1-34, August.
    9. Anirban Basu & James J. Heckman & Salvador Navarro-Lozano & Sergio Urzua, 2007. "Use of instrumental variables in the presence of heterogeneity and self-selection: an application to treatments of breast cancer patients," Health Economics, John Wiley & Sons, Ltd., vol. 16(11), pages 1133-1157.
    10. Evans, William N. & Garthwaite, Craig & Wei, Heng, 2008. "The impact of early discharge laws on the health of newborns," Journal of Health Economics, Elsevier, vol. 27(4), pages 843-870, July.
    11. James J. Heckman & Jeffrey Smith & Nancy Clements, 1997. "Making The Most Out Of Programme Evaluations and Social Experiments: Accounting For Heterogeneity in Programme Impacts," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 487-535.
    12. Cutler David M. & Meara Ellen, 2000. "The Technology of Birth: Is It Worth It?," Forum for Health Economics & Policy, De Gruyter, vol. 3(1), pages 1-37, January.
    13. Duggan Mark G & Evans William N, 2008. "Estimating the Impact of Medical Innovation: A Case Study of HIV Antiretroviral Treatments," Forum for Health Economics & Policy, De Gruyter, vol. 11(2), pages 1-39, January.
    14. David M. Cutler & Ellen Meara, 2000. "The Technology of Birth: Is It Worth It?," NBER Chapters, in: Frontiers in Health Policy Research, Volume 3, pages 33-68, National Bureau of Economic Research, Inc.
    15. David M. Cutler & Mark McClellan & Joseph P. Newhouse & Dahlia Remler, 1998. "Are Medical Prices Declining? Evidence from Heart Attack Treatments," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(4), pages 991-1024.
    16. James Heckman & Justin L. Tobias & Edward Vytlacil, 2003. "Simple Estimators for Treatment Parameters in a Latent-Variable Framework," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 748-755, August.
    17. Anirban Basu & James J. Heckman & Salvador Navarro-Lozano & Sergio Urzua, 2007. "Use of instrumental variables in the presence of heterogeneity and self-selection: An application in breast cancer patients," Health, Econometrics and Data Group (HEDG) Working Papers 07/07, HEDG, c/o Department of Economics, University of York.
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    3. Dzhamilya Nigmatulina & Charles Becker, 2016. "Is high-tech care in a middle-income country worth it?," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 24(4), pages 585-620, October.
    4. Sievertsen, Hans Henrik & Wüst, Miriam, 2017. "Discharge on the day of birth, parental response and health and schooling outcomes," Journal of Health Economics, Elsevier, vol. 55(C), pages 121-138.
    5. Mindy Marks & Moonkyung Kate Choi, 2019. "Baby Boomlets and Baby Health: Hospital Crowdedness, Hospital Spending, and Infant Health," American Journal of Health Economics, MIT Press, vol. 5(3), pages 376-406, Summer.
    6. David B. Audretsch, 2015. "Knowledge spillovers and future jobs," IZA World of Labor, Institute of Labor Economics (IZA), pages 218-218, December.
    7. Daysal, N. Meltem & Trandafir, Mircea & van Ewijk, Reyn, 2016. "Heterogeneous Effects of Medical Interventions on the Health of Low-Risk Newborns," IZA Discussion Papers 9810, Institute of Labor Economics (IZA).
    8. Mindy Marks & Kate Choi, 2011. "Baby Boomlets and Baby Health: Hospital Crowdedness, Treatment Intensity, and Infant Health," Working Papers 201440, University of California at Riverside, Department of Economics.

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    More about this item

    Keywords

    hospital stay; hospital care; birth; newborns;
    All these keywords.

    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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