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Influence, Information Overload, and Information Technology in Health Care

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  • James B. Rebitzer
  • Mari Rege
  • Christopher Shepard

Abstract

We investigate whether information technology can help physicians more efficiently acquire new knowledge in a clinical environment characterized by information overload. Our analysis makes use of data from a randomized trial as well as a theoretical model of the influence that information technology has on the acquisition of new medical knowledge. Although the theoretical framework we develop is conventionally microeconomic, the model highlights the non-market and non-pecuniary influence activities that have been emphasized in the sociological literature on technology diffusion. We report three findings. First, empirical evidence and theoretical reasoning suggests that computer based decision support will speed the diffusion of new medical knowledge when physicians are coping with information overload. Secondly, spillover effects will likely lead to "underinvestment" in this decision support technology. Third, alternative financing strategies common to new information technology, such as the use of marketing dollars to pay for the decision support systems, may lead to undesirable outcomes if physician information overload is sufficiently severe and if there is significant ambiguity in how best to respond to the clinical issues identified by the computer.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 14159.

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Date of creation: Jul 2008
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Handle: RePEc:nbr:nberwo:14159

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  1. Cutler, David M. & Huckman, Robert S., 2003. "Technological development and medical productivity: the diffusion of angioplasty in New York state," Journal of Health Economics, Elsevier, vol. 22(2), pages 187-217, March.
  2. Duggan, Mark, 2005. "Do new prescription drugs pay for themselves?: The case of second-generation antipsychotics," Journal of Health Economics, Elsevier, vol. 24(1), pages 1-31, January.
  3. Nancy Beaulieu & David M. Cutler & Katherine Ho, 2006. "The Business Case for Diabetes Disease Management for Managed Care Organizations," NBER Chapters, in: Frontiers in Health Policy Research, Volume 9 National Bureau of Economic Research, Inc.
  4. Erik Brynjolfsson & Lorin M. Hitt, 2000. "Beyond Computation: Information Technology, Organizational Transformation and Business Performance," Journal of Economic Perspectives, American Economic Association, vol. 14(4), pages 23-48, Fall.
  5. Jonathan Skinner & Elliott Fisher & John E. Wennberg, 2001. "The Efficiency of Medicare," NBER Working Papers 8395, National Bureau of Economic Research, Inc.
    • Jonathan S. Skinner & Elliott S. Fisher & John Wennberg, 2005. "The Efficiency of Medicare," NBER Chapters, in: Analyses in the Economics of Aging, pages 129-160 National Bureau of Economic Research, Inc.
  6. Cutler, David & Huckman, Robert, 2003. "Technological Development and Medical Productivity: The Diffusion of Angioplasty in New York State," Scholarly Articles 2664291, Harvard University Department of Economics.
  7. Charles E. Phelps, 1992. "Diffusion of Information in Medical Care," Journal of Economic Perspectives, American Economic Association, vol. 6(3), pages 23-42, Summer.
  8. Javitt, Jonathan C. & Rebitzer, James B. & Reisman, Lonny, 2008. "Information technology and medical missteps: Evidence from a randomized trial," Journal of Health Economics, Elsevier, vol. 27(3), pages 585-602, May.
  9. Phelps, Charles E., 2000. "Information diffusion and best practice adoption," Handbook of Health Economics, in: A. J. Culyer & J. P. Newhouse (ed.), Handbook of Health Economics, edition 1, volume 1, chapter 5, pages 223-264 Elsevier.
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