Soleimani Jalal, Marquez Alberto, Fathma Sawsan, Weister Timothy J, Barwise Amelia K
Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, USA.
Anesthesia Clinical Research Unit (ACRU), Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, USA.
SAGE Open Med. 2022 May 17;10:20503121221098146. doi: 10.1177/20503121221098146. eCollection 2022.
The objective of this derivation and validation study was to develop and validate a search strategy algorithm to detect patients who used professional interpreter services.
We identified all adults who had at least one intensive care unit admission during their hospital stay across the Mayo Clinic Enterprise between 1 January 2015 and 30 June 2020. Three random subsets of 100 patients were extracted from 60,268 patients to develop the search strategy algorithm. Two physician reviewers conducted gold standard manual chart review and any discrepancies were resolved by a third reviewer. These results were compared with the search strategy algorithm each time it was refined. Sensitivity and specificity were calculated during each phase by comparing the search strategy results to the reference gold standard for both derivation cohorts and the final validation cohort.
The first search strategy resulted in a sensitivity of 100% and a specificity of 89%. The second revised search strategy achieved a sensitivity of 100% and a specificity of 87%. The final version of the search strategy was applied to the validation subset and sensitivity and specificity were 100% and 89%, respectively.
We derived and validated a search strategy algorithm to assess interpreter use among hospitalized patients. Using a search strategy algorithm with high sensitivity and specificity can reduce the time required to abstract data from the electronic medical records compared with manual data abstraction.
本推导与验证研究的目的是开发并验证一种搜索策略算法,以检测使用专业口译服务的患者。
我们确定了2015年1月1日至2020年6月30日期间梅奥诊所企业内住院期间至少有一次重症监护病房入院记录的所有成年人。从60268名患者中提取了三个各100名患者的随机子集,以开发搜索策略算法。两名医生审阅者进行了金标准人工病历审查,任何差异均由第三名审阅者解决。每次改进搜索策略算法时,都会将这些结果与之进行比较。通过将搜索策略结果与推导队列和最终验证队列的参考金标准进行比较,在每个阶段计算敏感性和特异性。
第一个搜索策略的敏感性为100%,特异性为89%。第二个修订后的搜索策略的敏感性为100%,特异性为87%。搜索策略的最终版本应用于验证子集,敏感性和特异性分别为100%和89%。
我们推导并验证了一种搜索策略算法,以评估住院患者对口译员的使用情况。与人工数据提取相比,使用具有高敏感性和特异性的搜索策略算法可以减少从电子病历中提取数据所需的时间。