一种用于回顾性识别体外膜肺氧合（ECMO）患者连续性肾脏替代治疗（CRRT）启动情况的检索算法的推导与验证
Derivation and Validation of a Search Algorithm to Retrospectively Identify CRRT Initiation in the ECMO Patients.
作者信息
Guru Pramod K, Singh Tarun D, Passe Melissa, Kashani Kianoush B, Schears Gregory J, Kashyap Rahul
机构信息
Department Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic , Rochester, MN, USA.
Department of Neurology, Division of Critical Care, Mayo Clinic , Rochester, MN, USA.
出版信息
Appl Clin Inform. 2016 Jun 29;7(2):596-603. doi: 10.4338/ACI-2015-12-RA-0183. eCollection 2016.
BACKGROUND
The role of extracorporeal membrane oxygenation (ECMO) in refractory cardiorespiratory failure is gaining momentum with recent advancements in technology. However, the need for dialysis modes such as continuous renal replacement therapy (CRRT) has also increased in the management for acute kidney injury. Establishing the exact timing of CRRT initiation in these patients from the electronic medical record is vital for automated data extraction for research and quality improvement efforts.
OBJECTIVES
We aimed to derive and validate an automated Electronic Health Records (EHR) search strategy for CRRT initiation in patients receiving ECMO.
METHODS
We screened 488 patients who received ECMO and a total of 213 patients underwent CRRT. We evaluated random 120 patients, 60 for derivation and 60 for validation cohorts. Following implementation of eligibility criteria, the algorithm was derived in 55 out of 120 ECMO/CRRT patients. The search algorithm was developed using first-time chart entry of 'access pressure drop' at CRRT initiation. The algorithm was then validated in an independent subset of 52 patients from the same time period. The overall agreement between electronic search algorithm and a comprehensive manual medical record review in the derivation and validation subsets, using 'access pressure drop' as the reference standard, was compared to assess CRRT initiation time.
RESULTS
In the derivation subset (N=55), the automated electronic search strategy achieved an excellent agreement with manual search (κ =0.99, 54 were identified electronically, and 55 upon manual review). There was no time difference observed in 49/54(89%) patients, while in the remaining 5 (9%) patients time difference was within 15 minutes. In the validation cohort (N=52), agreement was 100 % (κ = 1.0, both methods identified 52 patients). Out of 52 patients, 47 (90%) had no time difference between the methods, for the remaining 5 (10%) patients, differences were within 15 minutes.
CONCLUSIONS
The use of an electronic search strategy resulted in determining an accurate CRRT initiation time among ECMO patients.
背景
随着技术的最新进展，体外膜肺氧合（ECMO）在难治性心肺衰竭中的作用越来越重要。然而，在急性肾损伤的管理中，对诸如连续性肾脏替代治疗（CRRT）等透析模式的需求也有所增加。从电子病历中确定这些患者开始CRRT的确切时间对于研究和质量改进工作的自动数据提取至关重要。
目的
我们旨在推导并验证一种用于接受ECMO治疗的患者开始CRRT的自动电子健康记录（EHR）搜索策略。
方法
我们筛选了488例接受ECMO治疗的患者，共有213例患者接受了CRRT。我们评估了随机抽取的120例患者，其中60例用于推导队列，60例用于验证队列。在实施纳入标准后，在120例ECMO/CRRT患者中的55例中推导出了该算法。使用CRRT开始时首次记录的“通路压力降”来开发搜索算法。然后在同一时期的52例独立患者子集中对该算法进行验证。以“通路压力降”作为参考标准，比较推导子集和验证子集中电子搜索算法与全面的手动病历审查之间的总体一致性，以评估CRRT开始时间。
结果
在推导子集中（N = 55），自动电子搜索策略与手动搜索达成了极好的一致性（κ = 0.99，通过电子方式识别出54例，通过手动审查识别出55例）。49/54（89%）的患者未观察到时间差异，而其余5例（9%）患者的时间差异在15分钟内。在验证队列中（N = 52），一致性为100%（κ = 1.0，两种方法均识别出52例患者）。在52例患者中，47例（90%）两种方法之间没有时间差异，其余5例（10%）患者的差异在15分钟内。
结论
使用电子搜索策略能够准确确定ECMO患者开始CRRT的时间。
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