Information Systems for Detecting and Managing Acute Kidney Injury

描述（由申请人提供）： 急性肾损伤（阿基）是住院患者的常见并发症，预示着死亡率增加3-5倍，成本增加，并可能终身依赖透析。虽然临床决策支持系统（CDSS）以前曾协助慢性肾脏疾病的医疗管理，但CDSS尚未验证识别阿基并促进早期医疗干预的方法。我们建议使用通常在电子病历中可用的实验室和床边测量来开发阿基检测算法。我们将根据专家肾脏学审查小组的判断验证算法，并使用最新发布的阿基分期标准。作为第二步，我们计划创建模型（使用传统和机器学习方法），通过合并合并症，入院诊断和暴露于肾毒性治疗来预测阿基的进展。一旦定义了早期阿基的电子标准，我们将建立和评估用于管理早期阿基的全院CDSS。其目的是预防阿基进展以及低钾血症、酸血症和药物毒性的相关并发症。

DESCRIPTION (provided by applicant): Acute Kidney Injury (AKI) is a common complication among hospitalized patients and heralds a 3-5 fold increase in mortality, increased costs, and potential lifelong dependence on dialysis. While clinical decision support systems (CDSS) have previously assisted with the medical management of chronic kidney disease, there has been no validated approach for a CDSS to identify AKI and facilitate a medical intervention at an early stage. We propose to develop an AKI detection algorithm using laboratory and bedside measurements that are typically available in electronic medical records. We will validate the algorithm against the judgment of an expert nephrology review panel and use the latest published standards for AKI staging. As a second step, we plan to create models (using both traditional and machine learning approaches) that predict progression of AKI by incorporating comorbidities, admission diagnoses, and exposure to nephrotoxic therapies. Once the electronic criteria for early AKI are defined, we will build and evaluate a hospital-wide CDSS for managing early AKI. The goal is to prevent AKI progression and the associated complications of hypokalemia, acidemia, and medication toxicity.