• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Health services management research: an official journal of the Association of University Programs in Health Administration >Patient length of stay and mortality prediction: A survey
【24h】

Patient length of stay and mortality prediction: A survey

机译：病人住院时间和死亡率预测:A调查

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Over the past few years, there has been increased interest in data mining and machine learning methods to improve hospital performance, in particular hospitals want to improve their intensive care unit statistics by reducing the number of patients dying inside the intensive care unit. Research has focused on prediction of measurable outcomes, including risk of complications, mortality and length of hospital stay. The length of stay is an important metric both for healthcare providers and patients, influenced by numerous factors. In particular, the length of stay in critical care is of great significance, both to patient experience and the cost of care, and is influenced by factors specific to the highly complex environment of the intensive care unit. The length of stay is often used as a surrogate for other outcomes, where those outcomes cannot be measured; for example as a surrogate for hospital or intensive care unit mortality. The length of stay is also a parameter, which has been used to identify the severity of illnesses and healthcare resource utilisation. This paper examines a range of length of stay and mortality prediction applications in acute medicine and the critical care unit. It also focuses on the methods of analysing length of stay and mortality prediction. Moreover, the paper provides a classification and evaluation for the analytical methods of the length of stay and mortality prediction associated with a grouping of relevant research papers published in the years 1984 to 2016 related to the domain of survival analysis. In addition, the paper highlights some of the gaps and challenges of the domain.
机译：在过去的几年里,一直在增加数据挖掘和机器学习的兴趣改善医院绩效的方法,特定的医院要提高他们的通过减少重症监护室统计数据在密集的死亡的患者数量护理单元。可衡量的结果,包括的风险并发症,死亡率和医院的长度留下来。对医疗服务提供者和病人,受众多因素的影响。在重症监护的长度是伟大的病人的经验和意义护理成本,受因素的影响特定的高度复杂的环境重症监护室。用作其他结果,代孕这些结果无法衡量;医院或重症监护室的代理死亡率。参数,用来识别严重的疾病和医疗资源利用率。停留时间和死亡率的预测应用程序在急性医学和至关重要的护理单元。分析住院时间和死亡率预测。分类和评价分析保持和死亡率的长度的方法预测与相关的分组研究论文发表在1984年2016年相关领域的生存分析。此外,本文突出一些差距和挑战的领域。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号