Citywide quality of health information system through text mining of electronic health records

被引：0
作者：
Anastasia A. Funkner
Michil P. Egorov
Sergey A. Fokin
Gennady M. Orlov
Sergey V. Kovalchuk
机构：
[1] ITMO University,
[2] Medical Information and Analytical Center,undefined
[3] Sokolov North-Western District Scientific and Clinical Center,undefined
来源：
Applied Network Science | / 6卷
关键词：
Health information system; Electronic health record; Unstructured data; Natural language processing; Data completeness; Machine learning;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
A system of hospitals in large cities can be considered a large and diverse but interconnected system. Widely applied in hospitals, electronic health records (EHR) are crucially different from each other because of the use of different health information systems, internal hospital rules, and individual behavior of physicians. The unstructured (textual) data of EHR is rarely used to assess the citywide quality of healthcare. Within the study, we analyze EHR data, particularly textual unstructured data, as a reflection of the complex multi-agent system of healthcare in the city of Saint Petersburg, Russia. Through analyzing the data collected by the Medical Information and Analytical Center, a method was proposed and evaluated for identifying a common structure, understanding the diversity, and assessing information quality in EHR data through the application of natural language processing techniques.
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