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KMID : 0371420190960050209
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Annals of Surgical Treatment and Research
2019 Volume.96 No. 5 p.209 ~ p.215
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Implementation of a resident night float system in a surgery department in Korea for 6 months: electronic medical record-based big data analysis and medical staff survey
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Yu Hyeong-Won
Choi June-Young
Park Young-Suk
Park Hyung-Sub
Choi Young-Rok
Ahn Sang-Hoon
Kang Eun-Young
Oh Heung-Kwon
Kim Eun-Kyu
Cho Jai-Young
Kim Duck-Woo
Park Do-Joong
Yoon Yoo-Seok
Kang Sung-Bum
Kim Hyung-Ho
Han Ho-Seong
Lee Tae-Seung
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Abstract
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Purpose: To evaluate superiority of a night float (NF) system in comparison to a traditional night on-call (NO) system for surgical residents at a single institution in terms of efficacy, safety, and satisfaction.
Methods: A NF system was implemented from March to September 2017 and big data analysis from electronic medical records was performed for all patients admitted for surgery or contacted from the emergency room (ER). Parameters including vital signs, mortality, and morbidity rates, as well as promptness of response to ER calls, were compared against a comparable period (March to September 2016) during which a NO system was in effect. A survey was also performed for physicians and nurses who had experienced both systems.
Results: A total of 150,000 clinical data were analyzed. Under the NO and NF systems, a total of 3,900 and 3,726 patients were admitted for surgery. Mortality rates were similar but postoperative bleeding was significantly higher in the NO system (0.5% vs. 0.2%, P = 0.031). From the 1,462 and 1,354 patients under the NO and NF systems respectively, that required surgical consultation from the ER, the time to response was significantly shorter in the NF system (54.5 ± 70.7 minutes vs. 66.8 ± 83.8 minutes, P < 0.001). Both physicians (90.4%) and nurses (91.4%) agreed that the NF system was more beneficial.
Conclusion: This is the first report of a NF system using big data analysis in Korea, and potential benefits of this new system were observed in both ward and ER patient management.
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KEYWORD
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Night shift work, Residency, General surgery, Big data, Electronic health record
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