Querying Temporal Anomalies in Healthcare Information Systems and Beyond

Khnaisser C, Hamrouni H, Blumenthal DB, Dignoes A, Gamper J (2022)

Publication Language: English

Publication Status: Published

Publication Type: Conference contribution, Conference Contribution

Publication year: 2022

Publisher: Springer International Publishing

Series: Lecture Notes in Computer Science

City/Town: Cham

Book Volume: 13389

Pages Range: 209--222

Conference Proceedings Title: Advances in Databases and Information Systems (ADBIS 2022)

Event location: Turin IT

ISBN: 9783031157394

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

Abstract

Finding anomalies in temporal relational databases is a difficult and challenging task, in particular if data is integrated from different sources. The problem is especially pressing in healthcare information systems, where temporal anomalies can pinpoint critical events such as erroneous drug administration or prescription. In this paper, we define three different temporal anomalies, which we call temporal redundancy, contradiction, and incompleteness. We define two different operators for each of these anomalies: the retrieval operator to retrieve all tuples of a relation that cause anomalous behaviour, and the labelling operator to annotate a temporal relation with additional information that marks normal and anomalous tuples. Finally, we present and evaluate different implementation techniques for the two operators for relational database systems.

Authors with CRIS profile

David Blumenthal Professur für Biomedical Network Science

Involved external institutions

Free University of Bozen - Bolzano IT Italy (IT) Université de Sherbrooke CA Canada (CA)

How to cite

APA:

Khnaisser, C., Hamrouni, H., Blumenthal, D.B., Dignoes, A., & Gamper, J. (2022). Querying Temporal Anomalies in Healthcare Information Systems and Beyond. In Chiusano S, Cerquitelli T, Wrembel R (Eds.), Advances in Databases and Information Systems (ADBIS 2022) (pp. 209--222). Turin, IT: Cham: Springer International Publishing.

MLA:

Khnaisser, Christina, et al. "Querying Temporal Anomalies in Healthcare Information Systems and Beyond." Proceedings of the 26th European Conference on Advances in Databases and Information Systems (ADBIS 2022), Turin Ed. Chiusano S, Cerquitelli T, Wrembel R, Cham: Springer International Publishing, 2022. 209--222.

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