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Temporal Change in Alert Override Rate with a Minimally Interruptive Clinical Decision Support on a Next-Generation Electronic Medical Record

1
Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul 06355, Korea
2
Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul 03080, Korea
3
Department of Emergency Medicine, Samsung Medical Center, Seoul 06355, Korea
4
Department of Nursing, Sahmyook University, School of Nursing, Institution of Healthcare Resource, Seoul 01795, Korea
*
Author to whom correspondence should be addressed.
Medicina 2020, 56(12), 662; https://doi.org/10.3390/medicina56120662
Received: 11 November 2020 / Revised: 25 November 2020 / Accepted: 29 November 2020 / Published: 30 November 2020
Background and objectives: The aim of this study is to describe the temporal change in alert override with a minimally interruptive clinical decision support (CDS) on a Next-Generation electronic medical record (EMR) and analyze factors associated with the change. Materials and Methods: The minimally interruptive CDS used in this study was implemented in the hospital in 2016, which was a part of the new next-generation EMR, Data Analytics and Research Window for Integrated kNowledge (DARWIN), which does not generate modals, ‘pop-ups’ but show messages as in-line information. The prescription (medication order) and alerts data from July 2016 to December 2017 were extracted. Piece-wise regression analysis and linear regression analysis was performed to determine the temporal change and factors associated with it. Results: Overall, 2,706,395 alerts and 993 doctors were included in the study. Among doctors, 37.2% were faculty (professors), 17.2% were fellows, and 45.6% trainees (interns and residents). The overall override rate was 61.9%. There was a significant change in an increasing trend at month 12 (p < 0.001). We found doctors’ positions and specialties, along with the number of alerts and medication variability, were significantly associated with the change. Conclusions: In this study, we found a significant temporal change of alert override. We also found factors associated with the change, which had statistical significance. View Full-Text
Keywords: decision support systems; clinical; electronic health records; medical order entry systems; drug therapy; computer-assisted decision support systems; clinical; electronic health records; medical order entry systems; drug therapy; computer-assisted
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MDPI and ACS Style

Cha, W.C.; Jung, W.; Yu, J.; Yoo, J.; Choi, J. Temporal Change in Alert Override Rate with a Minimally Interruptive Clinical Decision Support on a Next-Generation Electronic Medical Record. Medicina 2020, 56, 662. https://doi.org/10.3390/medicina56120662

AMA Style

Cha WC, Jung W, Yu J, Yoo J, Choi J. Temporal Change in Alert Override Rate with a Minimally Interruptive Clinical Decision Support on a Next-Generation Electronic Medical Record. Medicina. 2020; 56(12):662. https://doi.org/10.3390/medicina56120662

Chicago/Turabian Style

Cha, Won C.; Jung, Weon; Yu, Jaeyong; Yoo, Junsang; Choi, Jinwook. 2020. "Temporal Change in Alert Override Rate with a Minimally Interruptive Clinical Decision Support on a Next-Generation Electronic Medical Record" Medicina 56, no. 12: 662. https://doi.org/10.3390/medicina56120662

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