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

Seth Freedman, Haizhen Lin and Jeffrey Prince
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Haizhen Lin: Kelley School of Business, Indiana University

American Journal of Health Economics, 2018, vol. 4, issue 1, 51-79

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.

Keywords: health information technology; technology diffusion; patient safety; decision support (search for similar items in EconPapers)
JEL-codes: I19 O33 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (3)

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Related works:
Journal Article: Information Technology and Patient Health: Analyzing Outcomes, Populations, and Mechanisms (2018)
Working Paper: Information Technology and Patient Health: Analyzing Outcomes, Populations, and Mechanisms (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:ucp:amjhec:v:4:y:2018:i:1:p:51-79

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