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Information Technology and Patient Health: Analyzing Outcomes, Populations, and Mechanisms

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  • Seth Freedman

    (School of Public and Environmental Affairs, Indiana University Author email: freedmas@indiana.edu)

  • Haizhen Lin

    (Kelley School of Business, Indiana University)

  • Jeffrey Prince

    (Kelley School of Business, Indiana University)

Abstract

We study the effect of hospital adoption of electronic medical records (EMRs) on health outcomes, focusing on patient safety indicators. We link data on hospital-level EMR adoption from the Healthcare Information and Management Systems Society (HIMSS) Analytics Database to patient-level data from the Nationwide Inpatient Sample, and we exploit within-hospital variation in EMR adoption over time. We find evidence that EMRs reduce the likelihood of adverse patient safety events, particularly for less complex patients. Our results point to decision support as the most likely mechanism driving our findings. We find the most consistent effects for the following: a technology with decision support features, outcomes likely to respond to decision support, and patient populations likely to benefit from decision support. In addition, these findings suggest the negligible impacts found by previous studies of the Medicare population and/or mortality do not apply in all settings.

Suggested Citation

  • Seth Freedman & Haizhen Lin & Jeffrey Prince, 2018. "Information Technology and Patient Health: Analyzing Outcomes, Populations, and Mechanisms," American Journal of Health Economics, MIT Press, vol. 4(1), pages 51-79, Winter.
    • Handle: RePEc:tpr:amjhec:v:4:y:2018:i:1:p:51-79
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    Cited by:

    1. Seth Freedman & Noah Hammarlund, 2019. "Electronic medical records and medical procedure choice: Evidence from cesarean sections," Health Economics, John Wiley & Sons, Ltd., vol. 28(10), pages 1179-1193, October.
    2. Seth Freedman & Haizhen Lin & Jeffrey Prince, 2018. "Does Competition Lead to Agglomeration or Dispersion in EMR Vendor Decisions?," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 53(1), pages 57-79, August.
    3. Gautam Gowrisankaran & Keith A. Joiner & Jianjing Lin, 2016. "How do Hospitals Respond to Payment Incentives?," NBER Working Papers 22873, National Bureau of Economic Research, Inc.

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    More about this item

    Keywords

    health information technology; technology diffusion; patient safety; decision support;
    All these keywords.

    JEL classification:

    • I19 - Health, Education, and Welfare - - Health - - - Other
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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