A method for the graphical modeling of relative temporal constraints

被引:11
|
作者
Mate, Sebastian [1 ]
Buerkle, Thomas [2 ]
Kapsner, Lorenz A. [1 ]
Toddenroth, Dennis [3 ]
Kampf, Marvin O. [1 ]
Sedlmayr, Martin [4 ]
Castellanos, Ixchel [5 ]
Prokosch, Hans-Ulrich [1 ,3 ]
Kraus, Stefan [3 ]
机构
[1] Univ Klinikum Erlangen, Med Ctr Informat & Commun Technol, Erlangen, Germany
[2] Bern Univ Appl Sci, Biel, Switzerland
[3] Friedrich Alexander Univ Erlangen Nurnberg FAU, Chair Med Informat, Erlangen, Germany
[4] Tech Univ Dresden, Carl Gustav Carus Fac Med, Inst Med Informat & Biometry, Dresden, Germany
[5] Univ Klinikum Erlangen, Dept Anesthesiol, Erlangen, Germany
关键词
Temporal queries; Phenotyping; Phenotyping algorithms; Patient cohort identification; Data integration; Data retrieval; ELECTRONIC HEALTH RECORDS; INTEGRATING BIOLOGY; CLINICAL-RESEARCH; ARDEN SYNTAX; PATTERNS; QUERY; KNOWLEDGE; VISUALIZATION; INFORMATICS; ABSTRACTION;
D O I
10.1016/j.jbi.2019.103314
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Searching for patient cohorts in electronic patient data often requires the definition of temporal constraints between the selection criteria. However, beyond a certain degree of temporal complexity, the non-graphical, form-based approaches implemented in current translational research platforms may be limited when modeling such constraints. In our opinion, there is a need for an easily accessible and implementable, fully graphical method for creating temporal queries. We aim to respond to this challenge with a new graphical notation. Based on Allen's time interval algebra, it allows for modeling temporal queries by arranging simple horizontal bars depicting symbolic time intervals. To make our approach applicable to complex temporal patterns, we apply two extensions: with duration intervals, we enable the inference about relative temporal distances between patient events, and with time interval modifiers, we support counting and excluding patient events, as well as constraining numeric values. We describe how to generate database queries from this notation. We provide a prototypical implementation, consisting of a temporal query modeling frontend and an experimental backend that connects to an i2b2 system. We evaluate our modeling approach on the MIMIC-III database to demonstrate that it can be used for modeling typical temporal phenotyping queries.
引用
收藏
页数:16
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