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Predictability and Predictiveness in Health Care Spending

  • Randall P. Ellis

    ()

    (Department of Economics, Boston University)

  • Thomas G. McGuire

    (Harvard University)

This paper re-examines the relation between the predictability of health care spending and incentives due to adverse selection. Within an explicit model of health plan decisions about service levels, we show that predictability (how well spending on certain services can be anticipated), predictiveness (how well the predicted levels of certain services contemporaneously co-vary with total health care spending), and demand responsiveness all matter for adverse selection incentives. The product of terms involving these three measures of predictability, predictiveness, and demand responsiveness define an empirical index of the direction and magnitude of selection incentives. We quantify the relative magnitude of adverse selection incentives bearing on various types of health care services in Medicare. Our results are consistent with other research on service-level selection. The index of incentives can readily be applied to data from other payers.

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Paper provided by Boston University - Department of Economics in its series Boston University - Department of Economics - Working Papers Series with number WP2006-001.

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Length: 38pages
Date of creation: Jan 2006
Date of revision:
Handle: RePEc:bos:wpaper:wp2006-001
Contact details of provider: Postal: 270 Bay State Road, Boston, MA 02215
Phone: 617-353-4389
Fax: 617-353-4449
Web page: http://www.bu.edu/econ/

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  1. Frank, Richard G. & Glazer, Jacob & McGuire, Thomas G., 2000. "Measuring adverse selection in managed health care," Journal of Health Economics, Elsevier, vol. 19(6), pages 829-854, November.
  2. Keeler, Emmett B. & Carter, Grace & Newhouse, Joseph P., 1998. "A model of the impact of reimbursement schemes on health plan choice," Journal of Health Economics, Elsevier, vol. 17(3), pages 297-320, June.
  3. Yujing Shen & Randall P. Ellis, 2002. "How profitable is risk selection? A comparison of four risk adjustment models," Health Economics, John Wiley & Sons, Ltd., vol. 11(2), pages 165-174.
  4. Glazer, Jacob & McGuire, Thomas G., 2002. "Setting health plan premiums to ensure efficient quality in health care: minimum variance optimal risk adjustment," Journal of Public Economics, Elsevier, vol. 84(2), pages 153-173, May.
  5. Cao, Zhun & McGuire, Thomas G., 2003. "Service-level selection by HMOs in Medicare," Journal of Health Economics, Elsevier, vol. 22(6), pages 915-931, November.
  6. Buntin, Melinda Beeuwkes & Zaslavsky, Alan M., 2004. "Too much ado about two-part models and transformation?: Comparing methods of modeling Medicare expenditures," Journal of Health Economics, Elsevier, vol. 23(3), pages 525-542, May.
  7. Joseph P. Newhouse, 2004. "Pricing the Priceless: A Health Care Conundrum," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262640589, June.
  8. Yujing Shen & Randall P. Ellis, 1999. "Cost-Minimizing Risk Adjustment," Papers 0097, Boston University - Industry Studies Programme.
  9. Michelle M. Mello & Sally C. Stearns & Edward C. Norton, 2002. "Do Medicare HMOs still reduce health services use after controlling for selection bias?," Health Economics, John Wiley & Sons, Ltd., vol. 11(4), pages 323-340.
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