@inproceedings{b8a758ae774e466ebf204a9e01ab5de2,
title = "Toward automatic reporting of infectious diseases",
abstract = "Accurate, complete, and timely disease surveillance data are vital for disease control. We report a national scale effort to automatically extract information from electronic medical records as well as electronic laboratory systems. The extracted information is then transferred to the centers of disease control after a proper confirmation process. The coverage rates of the automated reporting systems are over 50%. Not only is the workload of surveillance greatly reduced, but also reporting is completed in near real-time. From our experiences, a system sustainable strategy, well-defined working plan, and multifaceted team coordination work effectively. Knowledge management reduces the cost to maintain the system. Training courses with hands-on practice and reference documents are useful for LOINC adoption.",
keywords = "Electronic health records, Logical observation identifiers names and codes, Public health surveillance",
author = "Tsao, {Hsiao Mei} and Chang, {Chi Ming} and Chuang, {Jen Hsiang} and Liu, {Ding Ping} and Pan, {Mei Lien} and Wang, {Da Wei}",
note = "Publisher Copyright: {\textcopyright} 2017 International Medical Informatics Association (IMIA) and IOS Press.; 16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017 ; Conference date: 21-08-2017 Through 25-08-2017",
year = "2017",
doi = "10.3233/978-1-61499-830-3-808",
language = "English",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press",
pages = "808--812",
editor = "Zhao Dongsheng and Gundlapalli, {Adi V.} and Jaulent Marie-Christine",
booktitle = "MEDINFO 2017",
address = "荷蘭",
}