Soares Neelkamal, Singhal Sorabh, Kloosterman Casey, Bailey Teresa
Perspect Health Inf Manag. 2021 Mar 15;18(Spring):1f. eCollection 2021 Spring.
Erroneous electronic health record (EHR) data capture is a barrier to preserving data integrity. We assessed the impact of an interdisciplinary process in minimizing EHR data loss from prescription orders. We implemented a three-step approach to reduce data loss due to missing medication doses: Step 1-A data analyst updated the request code to optimize data capture; Step 2-A pharmacist and physician identified variations in EHR prescription workflows; and Step 3-The clinician team determined daily doses for patients with multiple prescriptions in the same encounter. The initial report contained 1421 prescriptions, with 377 (26.5 percent) missing dosages. Missing dosages reduced to 361 (26.3 percent) prescriptions following Step 1, and twenty-three (1.7 percent) records after Step 2. After Step 3, 1210 prescriptions remained, including 16 (1.3 percent) prescriptions missing doses. Prescription data is susceptible to missing values due to multiple data capture workflows. Our approach minimized data loss, improving its validity in retrospective research.
错误的电子健康记录（EHR）数据采集是维护数据完整性的一个障碍。我们评估了一个跨学科流程在最小化处方医嘱中EHR数据丢失方面的影响。我们实施了一个三步方法来减少因漏服药物剂量导致的数据丢失：第一步——一名数据分析师更新请求代码以优化数据采集；第二步——一名药剂师和一名医生识别EHR处方工作流程中的差异；第三步——临床医生团队确定同一就诊中开具多张处方的患者的每日剂量。初始报告包含1421条处方，其中377条（26.5%）有漏服剂量。第一步后，漏服剂量的处方减少到361条（26.3%），第二步后减少到23条（1.7%）记录。第三步后，剩下1210条处方，其中16条（1.3%）处方有漏服剂量。由于多种数据采集工作流程，处方数据容易出现缺失值。我们的方法最小化了数据丢失，提高了其在回顾性研究中的有效性。
