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首页> 外文会议>Annual Hawaii International Conference on System Sciences >Data Mining in Healthcare Information Systems: Case Study of a Veterans' Administration Spinal Cord Injury Population
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Data Mining in Healthcare Information Systems: Case Study of a Veterans' Administration Spinal Cord Injury Population

机译：医疗保健信息系统中的数据挖掘：退伍军人脊髓损伤人口的案例研究

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摘要

In the following paper the process of knowledge generation from the Veterans Administration healthcare information system is explored. This inquiry is concerned with predicting length of stay of a subset of the total patient population, specifically those with spinal cord injuries (SCI). Although SCI patients do not present large numbers, they are outliers in the healthcare system due to extended hospital stays and high costs for treatment. Predicting length of stay can increase efficiencies and effectiveness in resource allocation thus lowering cost. The following research is the first of its kind to use nursing diagnosis and neural networks to predict length of stay. Background material on SCI and the knowledge discovery process is introduced. The entire data mining process is described beginning with data gathering followed by cleaning, aggregation, and integration. Issues faced while conducting the research are discussed. Results of artificial neural networks used to predict length of stay are presented.
机译：在下文中，探讨了退伍军人管理医疗保健信息系统的知识生成过程。该查询涉及预测总患者人群的父目的留下长度，特别是脊髓损伤（SCI）的患者。虽然SCI患者没有大量的数量，但由于延长医院的医院保持和治疗成本高，它们是医疗保健系统的异常值。预测保持时间长度可以提高资源分配的效率和有效性，从而降低成本。以下研究是首先使用护理诊断和神经网络来预测逗留时间。介绍了SCI的背景材料和知识发现过程。整个数据挖掘过程将首先以数据收集开始，然后是清洁，聚合和集成。讨论了进行研究时面临的问题。介绍了用于预测停留时间的人工神经网络的结果。

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