From the Department of Family Medicine, Carver College of Medicine, University of Iowa, Iowa City, IA (JMD, KP, BTL); Department of Epidemiology, College of Public Health, University of Iowa, Iowa City, IA (BTL).
J Am Board Fam Med. 2021 Jan-Feb;34(1):49-60. doi: 10.3122/jabfm.2021.01.200417.
Electronic health records (EHRs) are often leveraged in medical research to recruit study participants efficiently. The purpose of this study was to validate and refine the logic of an EHR algorithm for identifying potentially eligible participants for a comparative effectiveness study of fecal immunochemical tests (FITs), using colonoscopy as the standard.
An Epic report was built to identify patients who met the eligibility criteria to recruit patients having a screening or surveillance colonoscopy. With the goal of maximizing the number of potentially eligible patients that could be recruited, researchers, with the assistance of information technology and scheduling staff, developed the algorithm for identifying potential subjects in the EHR. Two validation methods, descriptive statistics and manual verification, were used.
The algorithm was refined over 3 iterations leading to the following criteria being used for generating the report: Age, Appointment Made On/Cancel Date, Appointment Procedure, Contact Type, Date Range, Encounter Departments, ICD-10 codes, and Patient Type. Appointment Serial Number/Contact Serial Number were output fields that allowed the tracking of cancellations and reschedules.
Development of an EHR algorithm saved time in that most individuals ineligible for the study were excluded before patient medical record review. Running daily reports that included cancellations and rescheduled appointments allowed for maximum recruitment in a time frame appropriate for the use of the FITs. This algorithm demonstrates that refining the algorithm iteratively and adding cancellations and reschedules of colonoscopies increased the accuracy of reaching all potential patients for recruitment.
电子健康记录(EHR)经常被用于医学研究中,以有效地招募研究参与者。本研究的目的是验证和完善一种用于识别粪便免疫化学检测(FIT)比较有效性研究中潜在合格参与者的 EHR 算法的逻辑,以结肠镜检查作为标准。
构建了一个 Epic 报告,以确定符合招募条件的患者,这些患者正在接受筛查或监测结肠镜检查。为了最大限度地增加可招募的潜在合格患者数量,研究人员在信息技术和调度人员的协助下,在 EHR 中开发了用于识别潜在受试者的算法。使用了两种验证方法,描述性统计和手动验证。
算法经过 3 次迭代进行了改进,从而确定了用于生成报告的以下标准:年龄、预约日期/取消日期、预约程序、联系方式、日期范围、就诊科室、ICD-10 代码和患者类型。预约序列号/联系序列号是输出字段,允许跟踪取消和重新安排。
开发 EHR 算法节省了时间,因为在对患者病历进行审查之前,已经排除了大多数不符合研究条件的人。运行包括取消和重新安排预约的每日报告,可以在适合使用 FIT 的时间框架内实现最大招募。该算法表明,通过反复改进算法并添加结肠镜检查的取消和重新安排,可以提高招募所有潜在患者的准确性。