突发公共卫生事件期间数据收集的优化——使用APACHE II评分的经验

ACI open Pub Date : 2019-01-01 DOI:10.1055/s-0039-1684001
Elizabeth White, Sarah Collins Rossetti, Neelima Karipineni, S. Maviglia, Raquel R Bartz, S. Bhagwanjee, J. P. Cobb, R. Rocha, B. Rocha
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引用次数: 1

摘要

摘要背景 在突发公共卫生事件中,实时获取准确的临床数据是一项挑战。美国重大疾病和伤害试验小组应急准备计划致力于改进这些准备工作。目标 我们的目标是创建一种电子急性生理学和慢性健康评估(APACHE)II数据收集工具,该工具(1)利用研究电子数据捕获(REDCap)自动化计算和逻辑,(2)可以在站点之间共享,(3)克服REDCap库中现有APACHE II工具的局限性,以及(4)建议在紧急情况下对数据收集工具进行更改。方法 APACHE II仪器是使用REDCap实现的。数据字段分为四个部分:年龄、急性生理学、格拉斯哥昏迷量表和慢性健康状况。可用性测试之后进行了两项初步评估:与现有APACHE II仪器的比较和模拟应急演习。后果 最后的仪器由34个数据字段组成。它产生了准确的APACHE II评分,并且比之前的两次实施更快完成(平均97.5 秒对323.5和183.5秒)。在模拟应急演习期间,该仪器在10个地点使用,创建了34份患者记录;完成仪器的中位时间为150.5秒。结论 该项目证明了提高数据采集仪器准确性和效率的可行性。未来的工作应侧重于扩展这些方法,以开发其他在紧急情况下使用的评分工具,并进行额外的测试,以确保在真正的紧急情况下可以使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization of Data Collection during Public Health Emergencies—Experience with APACHE II Score
Abstract Background Capturing accurate clinical data in real time is a challenge during public health emergencies. The United States Critical Illness and Injury Trials Group-Program for Emergency Preparedness is committed to improving these preparedness efforts. Objectives We aimed to create an electronic Acute Physiology and Chronic Health Evaluation (APACHE) II data collection instrument that (1) leverages Research Electronic Data Capture (REDCap) automated calculations and logic, (2) may be shared across sites, (3) overcomes limitations in existing APACHE II instruments in the REDCap library, and (4) suggests changes to be made to data collection instruments during emergencies. Methods The APACHE II instrument was implemented using REDCap. Data fields were divided into four sections: age, Acute Physiology, Glasgow Coma Scale, and chronic health status. Usability testing was followed by two preliminary evaluations: a comparison to existing APACHE II instruments and a simulated emergency exercise. Results The final instrument consisted of 34 data fields. It produced an accurate APACHE II score and was faster to complete than two previous implementations (average of 97.5 seconds vs. 323.5 and 183.5 seconds). During the simulated emergency exercise, the instrument was used at 10 sites to create 34 patient records; median time to complete the instrument was 150.5 seconds. Conclusion This project demonstrated feasibility of improving the accuracy and efficiency of a data collection instrument. Future efforts should focus on expanding these methods to develop other scoring tools for use during emergencies and additional testing to ensure it is ready for use during a real emergency.
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