围手术期医疗数据质量管理平台的设计与实现

Jie Cao, Ju Zhang, Xiaoguang Lin, An Long Sun
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引用次数: 0

摘要

目前,中国每年有6000多万例住院手术,积累了数亿条医疗数据记录。其多样性、快速性等特点使得围手术期医疗数据难以符合统一的标准,造成普遍存在的质量问题。许多问题逃避了简单的检查,因为为手术生成的数据来自多个数据流。为此,本文设计围手术期医疗数据质量管理平台,统一多源数据,解决交叉参考发现的问题。通过用时间逻辑表示交叉引用的数据规则,实现了围手术期医疗数据质量检验、数据质量控制和数据标注的综合工作平台。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and Implementation of a Perioperative Medical Data Quality Management Platform
At present, there are more than 60 million hospitalized surgeries each year in China, and hundreds of millions of medical data records have been accumulated. The diversity, speed and other characteristics make it confounding for perioperative medical data to comply with consistent standards, resulting in widespread quality problems. Many issues escape simple inspections because the data generated for surgeries are from multiple data streams. Hence perioperative medical data quality management platform is designed in this paper to unite data from multiple sources and address issues discovered from cross-referencing. By representing cross-referencing data rules with temporal logic, it implements a comprehensive work platform for data quality inspection, data quality control and data annotation of perioperative medical data.
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