IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/16900.html
   My bibliography  Save this paper

Economics of Individualization in Comparative Effectiveness Research and a Basis for a Patient-Centered Health Care

Author

Listed:
  • Anirban Basu

Abstract

The United States aspires to use information from comparative effectiveness research (CER) to reduce waste and contain costs without instituting a formal rationing mechanism or compromising patient or physician autonomy with regard to treatment choices. With such ambitious goals, traditional combinations of research designs and analytical methods used in CER may lead to disappointing results. In this paper, I study how alternate regimes of comparative effectiveness information help shape the marginal benefits (demand) curve in the population and how such perceived demand curves impact decision-making at the individual patient level and welfare at the societal level. I highlight the need to individualize comparative effectiveness research in order to generate the true (normative) demand curve for treatments. I discuss methodological principles that guide research designs for such studies. Using an example of the comparative effect of substance abuse treatments on crime, I use novel econometric methods to salvage individualized information from an existing dataset.

Suggested Citation

  • Anirban Basu, 2011. "Economics of Individualization in Comparative Effectiveness Research and a Basis for a Patient-Centered Health Care," NBER Working Papers 16900, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:16900
    Note: EH
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w16900.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Basu, Anirban & Jena, Anupam B. & Philipson, Tomas J., 2011. "The impact of comparative effectiveness research on health and health care spending," Journal of Health Economics, Elsevier, vol. 30(4), pages 695-706, July.
    2. Yi Cheng & Donald A. Berry, 2007. "Optimal adaptive randomized designs for clinical trials," Biometrika, Biometrika Trust, vol. 94(3), pages 673-689.
    3. Heckman, James J. & Navarro, Salvador, 2007. "Dynamic discrete choice and dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 136(2), pages 341-396, February.
    4. Pauly, Mark V. & Held, Philip J, 1990. "Benign moral hazard and the cost-effectiveness analysis of insurance coverage," Journal of Health Economics, Elsevier, vol. 9(4), pages 447-461, December.
    5. Chalkley, Martin & Khalil, Fahad, 2005. "Third party purchasing of health services: Patient choice and agency," Journal of Health Economics, Elsevier, vol. 24(6), pages 1132-1153, November.
    6. Andrew M. Jones (ed.), 2006. "The Elgar Companion to Health Economics," Books, Edward Elgar Publishing, number 3572.
    7. Aaron A. Stinnett & John Mullahy, 1998. "Net Health Benefits," Medical Decision Making, , vol. 18(2_suppl), pages 68-80, April.
    8. Stinnett, Aaron A. & Paltiel, A. David, 1996. "Mathematical programming for the efficient allocation of health care resources," Journal of Health Economics, Elsevier, vol. 15(5), pages 641-653, October.
    9. James J. Heckman & Jeffrey A. Smith, 1998. "Evaluating the Welfare State," NBER Working Papers 6542, National Bureau of Economic Research, Inc.
    10. Anirban Basu, 2009. "Individualization at the Heart of Comparative Effectiveness Research: The Time for i-CER Has Come," Medical Decision Making, , vol. 29(6), pages 9-11, November.
    11. Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004. "How Much Should We Trust Differences-In-Differences Estimates?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(1), pages 249-275.
    12. A. D. Roy, 1951. "Some Thoughts On The Distribution Of Earnings," Oxford Economic Papers, Oxford University Press, vol. 3(2), pages 135-146.
    13. Jena, Anupam B. & Philipson, Tomas J., 2013. "Endogenous cost-effectiveness analysis and health care technology adoption," Journal of Health Economics, Elsevier, vol. 32(1), pages 172-180.
    14. Heckman, James J, 1978. "Dummy Endogenous Variables in a Simultaneous Equation System," Econometrica, Econometric Society, vol. 46(4), pages 931-959, July.
    15. Aaron A. Stinnett & John Mullahy, 1998. "Net Health Benefits: A New Framework for the Analysis of Uncertainty in Cost-Effectiveness Analysis," NBER Technical Working Papers 0227, National Bureau of Economic Research, Inc.
    16. Manski, Charles F., 1975. "Maximum score estimation of the stochastic utility model of choice," Journal of Econometrics, Elsevier, vol. 3(3), pages 205-228, August.
    17. Frank A. Sloan & Hirschel Kasper (ed.), 2008. "Incentives and Choice in Health Care," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262693658, December.
    18. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-620, September.
    19. J. P. Florens & J. J. Heckman & C. Meghir & E. Vytlacil, 2008. "Identification of Treatment Effects Using Control Functions in Models With Continuous, Endogenous Treatment and Heterogeneous Effects," Econometrica, Econometric Society, vol. 76(5), pages 1191-1206, September.
    20. Anirban Basu & David Meltzer, 2007. "Value of Information on Preference Heterogeneity and Individualized Care," Medical Decision Making, , vol. 27(2), pages 112-127, March.
    21. Heckman, James J, 1990. "Varieties of Selection Bias," American Economic Review, American Economic Association, vol. 80(2), pages 313-318, May.
    22. Dehejia, Rajeev H., 2005. "Program evaluation as a decision problem," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 141-173.
    23. Munkin, Murat K. & Trivedi, Pravin K., 2003. "Bayesian analysis of a self-selection model with multiple outcomes using simulation-based estimation: an application to the demand for healthcare," Journal of Econometrics, Elsevier, vol. 114(2), pages 197-220, June.
    24. Pauly, Mark V. & Blavin, Fredric E., 2008. "Moral hazard in insurance, value-based cost sharing, and the benefits of blissful ignorance," Journal of Health Economics, Elsevier, vol. 27(6), pages 1407-1417, December.
    25. Anirban Basu & A. David Paltiel & Harold A. Pollack, 2008. "Social costs of robbery and the cost‐effectiveness of substance abuse treatment," Health Economics, John Wiley & Sons, Ltd., vol. 17(8), pages 927-946, August.
    26. Manning, Willard G. & Marquis, M. Susan, 1996. "Health insurance: The tradeoff between risk pooling and moral hazard," Journal of Health Economics, Elsevier, vol. 15(5), pages 609-639, October.
    27. Heckman, James J. & Robb, Richard Jr., 1985. "Alternative methods for evaluating the impact of interventions : An overview," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 239-267.
    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. Manuel Antonio Espinoza & Andrea Manca & Karl Claxton & Mark Sculpher, 2018. "Social value and individual choice: The value of a choice‐based decision‐making process in a collectively funded health system," Health Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 28-40, February.
    2. Amy Finkelstein & Petra Persson & Maria Polyakova & Jesse M. Shapiro, 2022. "A Taste of Their Own Medicine: Guideline Adherence and Access to Expertise," American Economic Review: Insights, American Economic Association, vol. 4(4), pages 507-526, December.
    3. Rebecca Mary Myerson & Darius Lakdawalla & Lisandro D. Colantonio & Monika Safford & David Meltzer, 2018. "Effects of Expanding Health Screening on Treatment - What Should We Expect? What Can We Learn?," NBER Working Papers 24347, National Bureau of Economic Research, Inc.
    4. Basu Anirban, 2013. "Personalized Medicine in the Context of Comparative Effectiveness Research," Forum for Health Economics & Policy, De Gruyter, vol. 16(2), pages 107-120, June.
    5. Basu, Anirban & Jena, Anupam B. & Philipson, Tomas J., 2011. "The impact of comparative effectiveness research on health and health care spending," Journal of Health Economics, Elsevier, vol. 30(4), pages 695-706, July.
    6. Anirban Basu, 2012. "Estimating Person-Centered Treatment (PeT) Effects Using Instrumental Variables," NBER Working Papers 18056, National Bureau of Economic Research, Inc.
    7. Carl Bonander & Mikael Svensson, 2021. "Using causal forests to assess heterogeneity in cost‐effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 30(8), pages 1818-1832, August.
    8. Meliyanni Johar & Shiko Maruyama, 2014. "Does Coresidence Improve An Elderly Parent'S Health?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(6), pages 965-983, September.
    9. Evans, H. & Basu, A, 2011. "Exploring comparative effect heterogeneity with instrumental variables: prehospital intubation and mortality," Health, Econometrics and Data Group (HEDG) Working Papers 11/08, HEDG, c/o Department of Economics, University of York.
    10. Basu, Anirban, 2015. "Welfare implications of learning through solicitation versus diversification in health care," Journal of Health Economics, Elsevier, vol. 42(C), pages 165-173.
    11. Anirban Basu & Anupam B. Jena & Dana P. Goldman & Tomas J. Philipson & Robert Dubois, 2014. "Heterogeneity In Action: The Role Of Passive Personalization In Comparative Effectiveness Research," Health Economics, John Wiley & Sons, Ltd., vol. 23(3), pages 359-373, March.
    12. David D. Kim & Anirban Basu, 2017. "New Metrics for Economic Evaluation in the Presence of Heterogeneity: Focusing on Evaluating Policy Alternatives Rather than Treatment Alternatives," Medical Decision Making, , vol. 37(8), pages 930-941, November.
    13. Mark Pauly, 2015. "Cost‐effectiveness Analysis and Insurance Coverage: Solving a Puzzle," Health Economics, John Wiley & Sons, Ltd., vol. 24(5), pages 506-515, May.
    14. Rebecca Myerson & Darius Lakdawalla & Lisandro D. Colantonio & Monika Safford & David Meltzer, 2018. "Effects of expanding health screening on treatment – What should we expect? What can we learn?," Working Papers 2018-014, Human Capital and Economic Opportunity Working Group.
    15. Karl Claxton & Stephen Palmer & Louise Longworth & Laura Bojke & Susan Griffin & Claire McKenna & Marta Soares & Eldon Spackman & Jihee Youn, 2011. "Uncertainty, evidence and irrecoverable costs: Informing approval, pricing and research decisions for health technologies," Working Papers 069cherp, Centre for Health Economics, University of York.

    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. Basu, Anirban & Jena, Anupam B. & Philipson, Tomas J., 2011. "The impact of comparative effectiveness research on health and health care spending," Journal of Health Economics, Elsevier, vol. 30(4), pages 695-706, July.
    2. 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.
    3. 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.
    4. Cunha, Flavio & Heckman, James J., 2007. "Identifying and Estimating the Distributions of Ex Post and Ex Ante Returns to Schooling," Labour Economics, Elsevier, vol. 14(6), pages 870-893, December.
    5. James J. Heckman, 2008. "Econometric Causality," International Statistical Review, International Statistical Institute, vol. 76(1), pages 1-27, April.
    6. Basu, Anirban, 2015. "Welfare implications of learning through solicitation versus diversification in health care," Journal of Health Economics, Elsevier, vol. 42(C), pages 165-173.
    7. Dehejia, Rajeev H., 2005. "Program evaluation as a decision problem," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 141-173.
    8. Arthur Lewbel, 2019. "The Identification Zoo: Meanings of Identification in Econometrics," Journal of Economic Literature, American Economic Association, vol. 57(4), pages 835-903, December.
    9. van der Klaauw, Bas, 2014. "From micro data to causality: Forty years of empirical labor economics," Labour Economics, Elsevier, vol. 30(C), pages 88-97.
    10. Heckman, James J. & Lalonde, Robert J. & Smith, Jeffrey A., 1999. "The economics and econometrics of active labor market programs," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 31, pages 1865-2097, Elsevier.
    11. James J. Heckman, 2005. "Micro Data, Heterogeneity and the Evaluation of Public Policy Part 2," The American Economist, Sage Publications, vol. 49(1), pages 16-44, March.
    12. 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.
    13. 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, November.
    14. Heckman, James, 2001. "Accounting for Heterogeneity, Diversity and General Equilibrium in Evaluating Social Programmes," Economic Journal, Royal Economic Society, vol. 111(475), pages 654-699, November.
    15. James J. Heckman & Jeffrey A. Smith, 1999. "The Pre-Program Earnings Dip and the Determinants of Participation in a Social Program: Implications for Simple Program Evaluation Strategies," NBER Working Papers 6983, National Bureau of Economic Research, Inc.
    16. Jones A.M & Rice N, 2009. "Econometric Evaluation of Health Policies," Health, Econometrics and Data Group (HEDG) Working Papers 09/09, HEDG, c/o Department of Economics, University of York.
    17. Basu, A & Polsky, D & Manning, W G, 2008. "Use of propensity scores in non-linear response models: The case for health care expenditures," Health, Econometrics and Data Group (HEDG) Working Papers 08/11, HEDG, c/o Department of Economics, University of York.
    18. James J. Heckman, 2008. "The Principles Underlying Evaluation Estimators with an Application to Matching," Annals of Economics and Statistics, GENES, issue 91-92, pages 9-73.
    19. Carneiro, Pedro & Hansen, Karsten T. & Heckman, James J., 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice," IZA Discussion Papers 767, Institute of Labor Economics (IZA).
    20. Mingliang Li & Dale J. Poirier & Justin L. Tobias, 2004. "Do dropouts suffer from dropping out? Estimation and prediction of outcome gains in generalized selection models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(2), pages 203-225.

    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

    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:16900. 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.