Noussa-Yao Joseph, Heudes Didier, Degoulet Patrice
INSERM UMR 1138, Equipe 22, Centre de Recherche des Cordeliers.
Stud Health Technol Inform. 2018;255:45-49.
Standards Data Warehouse has been implemented in many hospitals. It has enormous potential to improve performance measurement and health care quality. Accessing, organizing, and using these data to optimize clinical coding are evolving challenges for hospital systems. This paper describes development of a coding data warehouse based Entities-Attribute-Value (EAV) that we created by importing data from the clinical data warehouse (CDW) of public hospital. In particular, it focuses on design, implementation, and evaluation of the warehouse. Moreover, it defines the rules to convert a conceptual model of coding into an EAV logical model and his implementation using integrating biology and the bedside (i2b2). We evaluate it using data research mono and multi-criteria and then calculate the precision of our model. The result shows that, the coding data warehouse provides with good accuracy, an association of diagnostic code and medical act closer the patient's clinical landscape. Doctors without knowledge of coding rules could use this information to optimize and improve the diagnostic coding.
标准数据仓库已在许多医院实施。它在改善绩效评估和医疗质量方面具有巨大潜力。对于医院系统而言，访问、组织和使用这些数据以优化临床编码是不断演变的挑战。本文描述了我们通过从公立医院的临床数据仓库（CDW）导入数据而创建的基于实体-属性-值（EAV）的编码数据仓库的开发。特别是，它专注于该仓库的设计、实施和评估。此外，它定义了将编码概念模型转换为EAV逻辑模型的规则以及使用整合生物学与床边医学（i2b2）的实现方法。我们使用单标准和多标准数据研究对其进行评估，然后计算我们模型的精度。结果表明，编码数据仓库具有良好的准确性，诊断代码与医疗行为的关联更贴近患者的临床情况。不了解编码规则的医生可以使用此信息来优化和改进诊断编码。
