Information Systems for Detecting and Managing Acute Kidney Injury

用于检测和管理急性肾损伤的信息系统

• 批准号: 7925794
• 负责人: Joseph F. Peterson
• 金额: $ 33.05万
• 依托单位: VANDERBILT UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-30 至 2012-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7925794
• 关键词: Acute; Acute Renal Failure with Renal Papillary Necrosis; Address; Admission activity; Adopted; Adverse event; Algorithms; Capital; Caring; Characteristics; Chronic; Chronic Kidney Failure; Clinical; Clinical Decision Support Systems; Code; Comorbidity; Complication; Computer Assisted; Computerized Medical Record; Consult; Creatinine; Data; Databases; Decision Support Model; Decision Support Systems; Dependence; Detection; Diagnosis; Dialysis procedure; Documentation; Dose; Early treatment; Electrolytes; Electronics; Exposure to; Failure; Fluid Balance; Funding; Generic Drugs; Glomerular Filtration Rate; Goals; Guidelines; Hospital Mortality; Hospitals; Hypokalemia; Individual; Information Systems; Injury; Institution; Intervention; Investments; Judgment; Kidney; Laboratories; Lead; Machine Learning; Maintenance; Measurement; Medical; Methods; Modeling; Monitor; Nephrology; Nephrotoxic; Outcome; Output; Patients; Pattern; Performance; Pharmaceutical Preparations; Phase; Physiological; Population; Predictive Value; Process; Provider; Publishing; Reaction Time; Renal function; Research; Research Project Grants; Rifles; Risk; Serum; Staging; Stream; Structure; Syndrome; System; Time; Toxic effect; Urine; Work; base; care systems; cohort; computerized; computerized tools; cost; improved; mortality; prevent; programs; prospective; repository; response

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.

描述（由申请人提供）： 急性肾损伤 (AKI) 是住院患者的常见并发症，预示着死亡率增加 3-5 倍、费用增加以及可能终生依赖透析。虽然临床决策支持系统 (CDSS) 以前曾协助慢性肾脏病的医疗管理，但目前还没有有效的方法让 CDSS 识别 AKI 并促进早期医疗干预。我们建议使用电子病历中通常提供的实验室和床边测量数据来开发 AKI 检测算法。我们将根据肾病学专家评审小组的判断来验证算法，并使用最新发布的 AKI 分期标准。第二步，我们计划创建模型（使用传统和机器学习方法），通过结合合并症、入院诊断和肾毒性治疗来预测 AKI 的进展。一旦定义了早期 AKI 的电子标准，我们将建立并评估全院范围内用于管理早期 AKI 的 CDSS。目标是预防 AKI 进展以及低钾血症、酸血症和药物毒性等相关并发症。