制定和实施机构增强恢复计划数据流程。

Mohamed A Seif, Brittany C Kruse, Cameron A Keramati, Thomas A Aloia, Ruth A Amaku, Shreyas Bhavsar, Kenneth R DeCarlo, Rose Joan D Erfe, Jarrod S Eska, Maria D Iniesta, Laura R Prakash, Tao Zhang, Vijaya Gottumukkala
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引用次数: 2

摘要

背景:随着临床实践中越来越多地实施增强恢复计划(erp),标准化的数据收集和报告在解决用于报告结果的指标异质性方面变得至关重要。利用电子健康记录(EHR)系统收集、分析和传播ERP数据是有机会的。目标:(i)将有关的ERP变量合并为单一的数据范围;为迅速检索数据创造一种方便和直观的查询工具。方法:我们回顾了9个已建立的团队数据库,找出共同的变量,创建一个标准的ERP数据字典。为了解决数据自动化问题,我们使用第三方商业智能工具来映射EHR系统中已识别的变量,将变量整合到单个ERP系统中。为了确定疗效,我们比较了4名经验丰富的研究协调员使用手动、五宇宙和ERP宇宙流程检索10名随机选择的手术患者的ERP数据的时间。结果:所有10例患者的手动、5 universe和ERP universe处理数据变量的总时间分别为510、111和76 min。从5 - Universe或手动过程转换到ERP Universe分别减少了32%和85%的时间。结论:ERP Universe在不增加运营成本或中断工作流程的情况下改善了收集、分析和报告ERP元素的时间。含义:手工数据抽象对资源造成了很大的负担。专门用于ERP数据抽象的单一工具的创建大大提高了临床医生和支持人员查询ERP协议遵守情况的效率。
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Development and implementation of an institutional enhanced recovery program data process.

Background: With increasing implementation of enhanced recovery programs (ERPs) in clinical practice, standardised data collection and reporting have become critical in addressing the heterogeneity of metrics used for reporting outcomes. Opportunities exist to leverage electronic health record (EHR) systems to collect, analyse, and disseminate ERP data. Objectives: (i) To consolidate relevant ERP variables into a singular data universe; (ii) To create an accessible and intuitive query tool for rapid data retrieval. Method: We reviewed nine established individual team databases to identify common variables to create one standard ERP data dictionary. To address data automation, we used a third-party business intelligence tool to map identified variables within the EHR system, consolidating variables into a single ERP universe. To determine efficacy, we compared times for four experienced research coordinators to use manual, five-universe, and ERP Universe processes to retrieve ERP data for 10 randomly selected surgery patients. Results: The total times to process data variables for all 10 patients for the manual, five universe, and ERP Universe processes were 510, 111, and 76 min, respectively. Shifting from the five-universe or manual process to the ERP Universe resulted in decreases in time of 32% and 85%, respectively. Conclusion: The ERP Universe improves time spent collecting, analysing, and reporting ERP elements without increasing operational costs or interrupting workflow. Implications: Manual data abstraction places significant burden on resources. The creation of a singular instrument dedicated to ERP data abstraction greatly increases the efficiency in which clinicians and supporting staff can query adherence to an ERP protocol.

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