IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this paper

The Impact of Health Information Technology on Hospital Productivity

Listed author(s):
  • Jinhyung Lee
  • Jeffrey S. McCullough
  • Robert J. Town

The US health care sector is, by most accounts, extraordinarily inefficient. Health information technology (IT) has been championed as a tool that can transform health care delivery. Recently, the federal government has taken an active role in promoting health IT diffusion. There is little systematic analysis of the causal impact of health IT on productivity or whether private and public returns to health IT diverge thereby justifying government intervention. We estimate the parameters of a value-added hospital production function correcting for endogenous input choices in order to assess the private returns hospitals earn from health IT. Despite high marginal products, the potential benefits from expanded IT adoption are modest. Over the span of our data, health IT inputs increased by more than 210% and contributed about 6% to the increase in value-added. Virtually all the increase in value-added is attributable to the increased use of inputs{there was little change in hospital multi-factor productivity. Not-for-profits invested more heavily and differently in IT than for-profit hospitals. Finally, we find no evidence of labor complementarities or network externalities from health IT.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.nber.org/papers/w18025.pdf
Download Restriction: no

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 18025.

as
in new window

Length:
Date of creation: Apr 2012
Publication status: published as The impact of health information technology on hospital productivity Jinhyung Lee; Jeffrey S. Mccullough; Robert J. Town (Profiled Author: Jeffrey S McCullough) RAND Journal of Economics. 2013;44(3):545-568.
Handle: RePEc:nbr:nberwo:18025
Note: HC PR
Contact details of provider: Postal:
National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.

Phone: 617-868-3900
Web page: http://www.nber.org
Email:


More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as
in new window


  1. Daron Acemoglu & Amy Finkelstein, 2008. "Input and Technology Choices in Regulated Industries: Evidence from the Health Care Sector," Journal of Political Economy, University of Chicago Press, vol. 116(5), pages 837-880, October.
  2. Stephen Bond & Måns Söderbom, 2005. "Adjustment Costs and the Identification of Cobb Douglas Production Functions," Economics Papers 2005-W04, Economics Group, Nuffield College, University of Oxford.
  3. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
  4. Susan Athey & Scott Stern, 2002. "The Impact of Information Technology on Emergency Health Care Outcomes," RAND Journal of Economics, The RAND Corporation, vol. 33(3), pages 399-432, Autumn.
  5. Cutler, David & Landrum, Mary Beth & Huckman, Robert, 2004. "The Role of Information in Medical Markets: An Analysis of Publicly Reported Outcomes in Cardiac Surgery," Scholarly Articles 2640582, Harvard University Department of Economics.
  6. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
  7. Katz, Michael L & Shapiro, Carl, 1986. "Technology Adoption in the Presence of Network Externalities," Journal of Political Economy, University of Chicago Press, vol. 94(4), pages 822-841, August.
  8. Gautam Gowrisankaran & Joanna Stavins, 2004. "Network Externalities and Technology Adoption: Lessons from Electronic Payments," RAND Journal of Economics, The RAND Corporation, vol. 35(2), pages 260-276, Summer.
  9. Ackerberg, Daniel & Caves, Kevin & Frazer, Garth, 2006. "Structural identification of production functions," MPRA Paper 38349, University Library of Munich, Germany.
  10. Olley, G Steven & Pakes, Ariel, 1996. "The Dynamics of Productivity in the Telecommunications Equipment Industry," Econometrica, Econometric Society, vol. 64(6), pages 1263-1297, November.
  11. Nicholas Bloom & Raffaella Sadun & John Van Reenen, 2012. "Americans Do IT Better: US Multinationals and the Productivity Miracle," American Economic Review, American Economic Association, vol. 102(1), pages 167-201, February.
  12. Horwitz, Jill R. & Nichols, Austin, 2009. "Hospital ownership and medical services: Market mix, spillover effects, and nonprofit objectives," Journal of Health Economics, Elsevier, vol. 28(5), pages 924-937, September.
  13. Agha, Leila, 2014. "The effects of health information technology on the costs and quality of medical care," Journal of Health Economics, Elsevier, vol. 34(C), pages 19-30.
  14. Borzekowski, Ron, 2009. "Measuring the cost impact of hospital information systems: 1987-1994," Journal of Health Economics, Elsevier, vol. 28(5), pages 938-949, September.
  15. David M. Cutler & Robert S. Huckman & Mary Beth Landrum, 2004. "The Role of Information in Medical Markets: An Analysis of Publicly Reported Outcomes in Cardiac Surgery," American Economic Review, American Economic Association, vol. 94(2), pages 342-346, May.
  16. Kevin J. Stiroh, 2002. "Information Technology and the U.S. Productivity Revival: What Do the Industry Data Say?," American Economic Review, American Economic Association, vol. 92(5), pages 1559-1576, December.
  17. Ann Bartel & Casey Ichniowski & Kathryn Shaw, 2007. "How Does Information Technology Affect Productivity? Plant-Level Comparisons of Product Innovation, Process Improvement, and Worker Skills," The Quarterly Journal of Economics, Oxford University Press, vol. 122(4), pages 1721-1758.
  18. Erik Brynjolfsson & Lorin Hitt, 1996. "Paradox Lost? Firm-Level Evidence on the Returns to Information Systems Spending," Management Science, INFORMS, vol. 42(4), pages 541-558, April.
  19. David, Guy & Lindrooth, Richard C. & Helmchen, Lorens A. & Burns, Lawton R., 2014. "Do hospitals cross-subsidize?," Journal of Health Economics, Elsevier, vol. 37(C), pages 198-218.
  20. Stephen Bond & Måns Söderbom, 2005. "Adjustment Costs and the Identification of Cobb Douglas Production Functions," Economics Series Working Papers 2005-W04, University of Oxford, Department of Economics.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:18025. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ()

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.