Querying Temporal Anomalies in Healthcare Information Systems and Beyond

Khnaisser, Christina; Hamrouni, Hind; Blumenthal, David B.; Dignös, Anton; Gamper, Johann

doi:10.1007/978-3-031-15740-0_16

Cited by 2 publications

(2 citation statements)

References 23 publications

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“…In UHF, the verification of these inconsistencies are expressed simply and efficiently either at the time of import to prevent inconsistencies or at the time of quality check to detect temporal anomalies. 28…”

Section: Methodsmentioning

confidence: 99%

“…Especially in healthcare information systems, temporal anomalies in relational databases may be indicative of the poor quality of the temporal data. In a recent work, 28 the authors defined generic queries to retrieve the anomalous tuples from a dataset or to label the tuples in a dataset with an indication of whether they are anomalous or not.…”

Section: Introductionmentioning

confidence: 99%

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Building ontology-based temporal databases for data reuse: An applied example on hospital organizational structures

Khnaisser,

Looten,

Lavoie

et al. 2024

Health Informatics J

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Keeping track of data semantics and data changes in the databases is essential to support retrospective studies and the reproducibility of longitudinal clinical analysis by preventing false conclusions from being drawn from outdated data. A knowledge model combined with a temporal model plays an essential role in organizing the data and improving query expressiveness across time and multiple institutions. This paper presents a modelling framework for temporal relational databases using an ontology to derive a shareable and interoperable data model. The framework is based on: OntoRela an ontology-driven database modelling approach and Unified Historicization Framework a temporal database modelling approach. The method was applied to hospital organizational structures to show the impact of tracking organizational changes on data quality assessment, healthcare activities and data access rights. The paper demonstrated the usefulness of an ontology to provide a formal, interoperable, and reusable definition of entities and their relationships, as well as the adequacy of the temporal database to store, trace, and query data over time.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Building ontology-based temporal databases for data reuse: An applied example on hospital organizational structures

Khnaisser,

Looten,

Lavoie

et al. 2024

Health Informatics J

Self Cite

View full text Add to dashboard Cite

show abstract

Efficiently Labeling and Retrieving Temporal Anomalies in Relational Databases

Khnaisser,

Hamrouni,

Blumenthal

et al. 2024

Inf Syst Front

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Time and temporal constraints are implicit in most databases. To facilitate data analysis and quality assessment, a database should provide explicit operations to identify the violation of temporal constraints. Against this background, the purpose of this paper is threefold: (1) we identify and provide a formal definition of five common anomalies in temporal databases, (2) we propose two new relational operations that allow, respectively, to label anomalous tuples in and to retrieve the anomalous tuples from a dataset, and (3) we provide three different SQL implementations of these operations for current relational database management systems. The healthcare domain is used to illustrate the usage and utility of the temporal anomalies. Finally, an experimental evaluation on real-world and synthetic data analyses the performance of the different implementations of the anomaly operators.

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Querying Temporal Anomalies in Healthcare Information Systems and Beyond

Cited by 2 publications

References 23 publications

Building ontology-based temporal databases for data reuse: An applied example on hospital organizational structures

Building ontology-based temporal databases for data reuse: An applied example on hospital organizational structures

Efficiently Labeling and Retrieving Temporal Anomalies in Relational Databases

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