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Negative Tests and the Efficiency of Medical Care: What Determines Heterogeneity in Imaging Behavior?

Author

Listed:
  • Jason Abaluck
  • Leila Agha
  • Christopher Kabrhel
  • Ali Raja
  • Arjun Venkatesh

Abstract

We develop a model of the efficiency of medical testing based on rates of negative CT scans for pulmonary embolism. The model is estimated using a 20% sample of Medicare claims from 2000- 2009. We document enormous across-doctor heterogeneity in testing decisions conditional on patient risk and show it explains the negative relationship between physicians' testing frequencies and test yields. Physicians in high spending regions test more low-risk patients. Under calibration assumptions, 84% of doctors test even when costs exceed expected benefits. Furthermore, doctors do not apply observables to target testing to the highest risk patients, substantially reducing simulated test yields.

Suggested Citation

  • Jason Abaluck & Leila Agha & Christopher Kabrhel & Ali Raja & Arjun Venkatesh, 2014. "Negative Tests and the Efficiency of Medical Care: What Determines Heterogeneity in Imaging Behavior?," NBER Working Papers 19956, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:19956
    Note: AG HC HE PE
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    File URL: http://www.nber.org/papers/w19956.pdf
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    References listed on IDEAS

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    1. Emily Oster & Ira Shoulson & E. Ray Dorsey, 2013. "Optimal Expectations and Limited Medical Testing: Evidence from Huntington Disease," American Economic Review, American Economic Association, vol. 103(2), pages 804-830, April.
    2. Thomas J. Kane & Douglas O. Staiger, 2008. "Estimating Teacher Impacts on Student Achievement: An Experimental Evaluation," NBER Working Papers 14607, National Bureau of Economic Research, Inc.
    3. Alan M. Garber & Jonathan Skinner, 2008. "Is American Health Care Uniquely Inefficient?," Journal of Economic Perspectives, American Economic Association, vol. 22(4), pages 27-50, Fall.
    4. Lewis, Jeffrey B. & Linzer, Drew A., 2005. "Estimating Regression Models in Which the Dependent Variable Is Based on Estimates," Political Analysis, Cambridge University Press, vol. 13(04), pages 345-364, September.
    5. Doyle Jr., Joseph J. & Ewer, Steven M. & Wagner, Todd H., 2010. "Returns to physician human capital: Evidence from patients randomized to physician teams," Journal of Health Economics, Elsevier, vol. 29(6), pages 866-882, December.
    6. Janet Currie & W. Bentley MacLeod, 2017. "Diagnosing Expertise: Human Capital, Decision Making, and Performance among Physicians," Journal of Labor Economics, University of Chicago Press, vol. 35(1), pages 1-43.
    7. Klein, Roger W & Spady, Richard H, 1993. "An Efficient Semiparametric Estimator for Binary Response Models," Econometrica, Econometric Society, vol. 61(2), pages 387-421, March.
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    Cited by:

    1. Rudy Douven & Minke Remmerswaal & Robin Zoutenbier, 2015. "Do Extrinsically Motivated Mental Health Care Providers Have Better Treatment Outcomes?," CPB Discussion Paper 319, CPB Netherlands Bureau for Economic Policy Analysis.
    2. Alexander, Diane, 2017. "How do Doctors Respond to Incentives? Unintended Consequences of Paying Doctors to Reduce Costs," Working Paper Series WP-2017-9, Federal Reserve Bank of Chicago.
    3. Gautam Gowrisankaran & Keith A. Joiner & Pierre-Thomas L├ęger, 2017. "Physician Practice Style and Healthcare Costs: Evidence from Emergency Departments," NBER Working Papers 24155, National Bureau of Economic Research, Inc.
    4. Janet Currie & W. Bentley MacLeod, 2017. "Diagnosing Expertise: Human Capital, Decision Making, and Performance among Physicians," Journal of Labor Economics, University of Chicago Press, vol. 35(1), pages 1-43.

    More about this item

    JEL classification:

    • I0 - Health, Education, and Welfare - - General
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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