TY - GEN
T1 - Towards A Task Taxonomy of Visual Analysis of Electronic Health or Medical Record Data
AU - Bian, Xiaohui
AU - Kharrazi, Hadi
AU - Caban, Jesus J.
AU - He, Gaoqi
AU - Feng, Zhiquan
AU - Chen, Jian
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - We integrate literature- and data-driven task analysis methods to derive an initial task taxonomy for electronic health record (EHR) and electronic medical record (EMR) data analysis. An EHR (EMR) is a digital and longitudinal version of a patients health(medical) information and may include all key clinical events relevant to that persons health (medical) history, such as provider, demographics, progress notes, medicine, diagnosis, etc. Our goal is to arrive a task taxonomy for analyzing EHR (EMR) datasets because tasks play an important role in the design and evaluation of visualization techniques. Our method has three stages: data collection, task modelling, and task taxonomy summary. In data collection, we first survey related literature from the past two decades and extract typical tasks and corresponding data by extracting goals and scenarios of the particular work. We introduce multiple continuous relations to describe specific binary or multiple continuous relation-seeking tasks. Finally, we arrive an initial set of task types for EHR/EMR analysis that guide the design and evaluation of visualization techniques.
AB - We integrate literature- and data-driven task analysis methods to derive an initial task taxonomy for electronic health record (EHR) and electronic medical record (EMR) data analysis. An EHR (EMR) is a digital and longitudinal version of a patients health(medical) information and may include all key clinical events relevant to that persons health (medical) history, such as provider, demographics, progress notes, medicine, diagnosis, etc. Our goal is to arrive a task taxonomy for analyzing EHR (EMR) datasets because tasks play an important role in the design and evaluation of visualization techniques. Our method has three stages: data collection, task modelling, and task taxonomy summary. In data collection, we first survey related literature from the past two decades and extract typical tasks and corresponding data by extracting goals and scenarios of the particular work. We introduce multiple continuous relations to describe specific binary or multiple continuous relation-seeking tasks. Finally, we arrive an initial set of task types for EHR/EMR analysis that guide the design and evaluation of visualization techniques.
KW - data-driven method
KW - electronic health record
KW - literature-driven method
KW - Task taxonomy
KW - visualization task analysis
UR - https://www.scopus.com/pages/publications/85065925358
U2 - 10.1109/PIC.2018.8706292
DO - 10.1109/PIC.2018.8706292
M3 - 会议稿件
AN - SCOPUS:85065925358
T3 - Proceedings of the 2018 IEEE International Conference on Progress in Informatics and Computing, PIC 2018
SP - 281
EP - 286
BT - Proceedings of the 2018 IEEE International Conference on Progress in Informatics and Computing, PIC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th IEEE International Conference on Progress in Informatics and Computing, PIC 2018
Y2 - 14 December 2018 through 16 December 2018
ER -