Nutritional diagnosis of emergency patients in the context of diagnosis related groups and artificial intelligence. [J]. Journal of Southwest Medical University 46(6):473-478(2023)
DOI:
Nutritional diagnosis of emergency patients in the context of diagnosis related groups and artificial intelligence. [J]. Journal of Southwest Medical University 46(6):473-478(2023) DOI: 10.3969/j.issn.2096-3351.2023.06.003.
Nutritional diagnosis of emergency patients in the context of diagnosis related groups and artificial intelligence
摘要
营养风险或营养不良在急诊患者中普遍存在,可导致病死风险上升并造成疾病负担加重。但迄今为止,在急诊领域中,对营养风险的关注度明显低于其他专科。2016年多个国际性营养组织提出了全球领导人营养不良倡议(Global Leadership Initiative on Malnutrition,GLIM)。GLIM自提出以来,发展迅速,已成为进行营养诊断的主要方法学工具。与此同时,疾病诊断相关分组(diagnosis related groups,DRGs)在中国已经快速普及,并成为新一轮医改的重要内容。在DRGs背景下,营养不良的诊断和干预对患者具有重要的临床和经济学意义。本文将基于GLIM标准结合DRGs的时代背景,从急诊患者的营养风险筛查、营养不良诊断、临床经济学效益以及急诊患者营养评估的未来发展方向等多方面的应用与研究进展进行评述,以期为广大急诊医务人员更好的理解急诊患者的营养评估提供借鉴。
Abstract
Nutritional risk and malnutrition are commonly found among emergency patients,which can increase the risk of mortality and further burden the disease. However,in the field of emergency medicine,the attention given to nutritional risk has been significantly lower compared to other specialties. In 2016,several international nutrition organizations proposed the Global Leadership Initiative on Malnutrition (GLIM) as a comprehensive approach. Since its inception,GLIM has rapidly developed into a major methodological tool for nutritional diagnosis. At the same time,diagnosis-related groups (DRGs) have been widely implemented in China and have become an important aspect of healthcare reform. Within the context of DRGs,the diagnosis and intervention of malnutrition hold significant clinical and economic implications for patients. This article aims to review various aspects including nutritional risk screening,malnutrition diagnosis,clinical and economic benefits,as well as future directions for nutritional assessment of emergency patients,taking into account the frameworks of both DRGs and GLIM. The goal is to provide valuable insights for emergency healthcare professionals to better understand nutritional assessment in the emergency department.
关键词
急诊疾病诊断相关分组全球领导人营养不良倡议机器学习5G技术
Keywords
EmergencyDiagnosis related groupsGlobal Leadership Initiative on MalnutritionMachine learning5G communication technology