Hagen John, Klein Lazar, Miller Ethan, Solomon Shirley
Chief of Surgery, and Medical Director of Bariatrics at the Humber River Hospital, as well as a faculty member of the University of Toronto's MIS fellowship training program. He can be reached by email at
A surgeon at Humber River Hospital.
Healthc Q. 2020 May;23(SP):9-13. doi: 10.12927/hcq.2020.26177.
The digitalization of healthcare information provides hospitals with the ability to gain insight into patterns and associations pertaining to disease and management. Using bariatric patient data as an example provided an opportunity to explore the potential of electronic medical record (EMR) data to generate insights.
The aim of this study was to extract EMR data pertaining to bariatric patient information as a means to explore predictive factors of weight loss post-bariatric surgery.
We conducted a retrospective cohort study of patients undergoing bariatric surgery between January 1, 2018, and April 30, 2019, at Humber River Hospital. Multiple linear regression was used to examine whether age, pre-surgery body mass index (BMI), comorbidities and mental health disorders predicted higher weight loss 6 months following bariatric surgery.
A total of 502 patients were included in the final analysis. Age (ß = 0.04 [95% CI 0.01, 0.06], p = 0.005), baseline BMI (ß = -0.16 [95% CI -0.19, -0.13], p = <0.0001) and diabetes (ß = 0.82 [95% CI 0.23, 1.42], p = 0.007) were associated with weight loss six months post-bariatric surgery.
EMRs are a rich source of data with the potential to generate insights that can lead to improved care.
医疗保健信息的数字化使医院能够深入了解与疾病和管理相关的模式及关联。以肥胖症患者数据为例，提供了一个探索电子病历（EMR）数据产生见解潜力的机会。
本研究的目的是提取与肥胖症患者信息相关的电子病历数据，作为探索肥胖症手术后体重减轻预测因素的一种手段。
我们对2018年1月1日至2019年4月30日在亨伯河医院接受肥胖症手术的患者进行了一项回顾性队列研究。使用多元线性回归来检验年龄、术前体重指数（BMI）、合并症和心理健康障碍是否能预测肥胖症手术后6个月体重减轻更多。
共有502名患者纳入最终分析。年龄（β = 0.04 [95%置信区间0.01, 0.06]，p = 0.005）、基线BMI（β = -0.16 [95%置信区间 -0.19, -0.13]，p = <0.0001）和糖尿病（β = 0.82 [95%置信区间0.23, 1.42]，p = 0.007）与肥胖症手术后6个月的体重减轻相关。
电子病历是丰富的数据来源，有潜力产生可改善护理的见解。
