Automated EHR score to predict COVID-19 outcomes at US Department of Veterans Affairs
Automated EHR score to predict COVID-19 outcomes at US Department of Veterans Affairs
复制标题
DOI：
10.1371/journal.pone.0236554
复制
发表时间：
2020-07-27
期刊：
影响因子：
3.7
通讯作者：
Curtin, Catherine M.
中科院分区：
文献类型：
--
作者：
Osborne, Thomas F.;Veigulis, Zachary P.;Curtin, Catherine M.
COVID-19的突然出现给退伍军人的护理带来了重大挑战。预测患者临床病程的能力的提高将有助于做出最佳护理决策、资源分配、家庭咨询以及安全放松距离限制的策略。护理评估需求 (CAN) 评分是退伍军人健康管理局 (VA) 内现有的风险评估工具，评分范围为 0 到 99，评分越高，风险越大。该模型最初是为非急性门诊患者设计的，是根据电子健康记录中的结构化数据变量自动计算的。这项对 2020 年 3 月 2 日至 2020 年 5 月 26 日期间诊断出患有 COVID-19 的 6591 名退伍军人进行的多中心回顾性研究旨在评估重新利用 CAN 评分作为客观和自动化风险评估工具的效用，以迅速增强诊断出患有 COVID-19 的退伍军人的临床决策。我们使用卡方独立检验对二分 CAN 1 年死亡率评分（高风险与低风险）和每个患者的结果进行了双变量分析。使用连续 CAN 评分的逻辑回归模型适合评估其对感兴趣结果的预测能力。结果表明，CAN 评分大于 50 分与 COVID-19 检测呈阳性后的以下结果显着相关：入院 (OR 4.6)、住院时间延长 (OR 4.5)、入住 ICU (3.1)、ICU 停留时间延长 (OR 2.9)、机械通气 (OR 2.6) 和死亡率 (OR 7.2)。重新利用 CAN 评分提供了一种对 COVID-19 退伍军人进行风险分层的有效方法。由于具有令人信服的统计结果和自动化，该工具非常适合在整个 VA 广泛使用，以增强临床决策。
The sudden emergence of COVID-19 has brought significant challenges to the care of Veterans. An improved ability to predict a patient's clinical course would facilitate optimal care decisions, resource allocation, family counseling, and strategies for safely easing distancing restrictions. The Care Assessment Need (CAN) score is an existing risk assessment tool within the Veterans Health Administration (VA), and produces a score from 0 to 99, with a higher score correlating to a greater risk. The model was originally designed for the nonacute outpatient setting and is automatically calculated from structured data variables in the electronic health record. This multisite retrospective study of 6591 Veterans diagnosed with COVID-19 from March 2, 2020 to May 26, 2020 was designed to assess the utility of repurposing the CAN score as objective and automated risk assessment tool to promptly enhance clinical decision making for Veterans diagnosed with COVID-19. We performed bivariate analyses on the dichotomized CAN 1-year mortality score (high vs. low risk) and each patient outcome using Chi-square tests of independence. Logistic regression models using the continuous CAN score were fit to assess its predictive power for outcomes of interest. Results demonstrated that a CAN score greater than 50 was significantly associated with the following outcomes after positive COVID-19 test: hospital admission (OR 4.6), prolonged hospital stay (OR 4.5), ICU admission (3.1), prolonged ICU stay (OR 2.9), mechanical ventilation (OR 2.6), and mortality (OR 7.2). Repurposing the CAN score offers an efficient way to risk-stratify COVID-19 Veterans. As a result of the compelling statistical results, and automation, this tool is well positioned for broad use across the VA to enhance clinical decision-making.