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Updated: Feb 9, 2026

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Evaluation of a systematic methodology to detect in near real-time performance changes during electronic health
Tiago K Colicchio1, Guilherme Del Fiol1, Greg J Stoddard2
1Biomedical Informatics, University of Utah, Salt Lake City, UT.
Abstract:
Introduction. Although Electronic Health Record (EHR) adoption has increased in the U.S., our understanding of how it affects health care organizations is still limited. Current literature has produced mixed-results due to the use of simple, non-standardized measurements and poor research designs. Methods. We propose the use of a systematic methodology that combines measures of quality, productivity and safety processes, tracked over time using an interrupted time-series design with multiple control sites. Results. Our methodology successfully detected performance changes during an EHR implementation on 17 (77%) outcomes, including a significant increase in Emergency Department length of stay immediately after go live by 0.19 hours [95%CI (0.12, 0.27), p<0.001], and an improvement in time to complete radiology tests, which significantly decreased per month by 0.19 minutes [95%CI (-0.26, -0.12), p<0.001]. Conclusion. The proposed methodology was able to detect several changes immediately after an EHR implementation and over time. The method is a promising and robust approach to assessing the impact of EHR implementations on a wide range of health care quality, productivity, and safety care processes.
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