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Querying Temporal Anomalies in Healthcare Information Systems and Beyond

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Advances in Databases and Information Systems (ADBIS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13389))

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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.

Supported by Ministère de l’Économie et de l’Innovation – Québec and by the Autonomous Province of Bozen-Bolzano with research call “Research Südtirol/Alto Adige 2019” (project Enabling Industrial-Strength, Open-Source Temporal Query Processing – ISTeP).

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Notes

  1. 1.

    See: https://www.postgresql.org/docs/current/functions-aggregate.html for PostgreSQL or https://docs.microsoft.com/en-us/u-sql/functions/aggregate/array-agg for MS SQLServer.

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Author information

Authors and Affiliations

  1. Université de Sherbrooke, Sherbrooke, Canada

    Christina Khnaisser

  2. Free University of Bozen-Bolzano, Bozen, Italy

    Hind Hamrouni, Anton Dignös & Johann Gamper

  3. Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany

    David B. Blumenthal

Authors
  1. Christina Khnaisser
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  2. Hind Hamrouni
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  3. David B. Blumenthal
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  4. Anton Dignös
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  5. Johann Gamper
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Corresponding author

Correspondence to Christina Khnaisser .

Editor information

Editors and Affiliations

  1. Politecnico di Torino, Turin, Italy

    Silvia Chiusano

  2. Politecnico di Torino, Turin, Italy

    Tania Cerquitelli

  3. Poznań University of Technology, Poznań, Poland

    Robert Wrembel

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Khnaisser, C., Hamrouni, H., Blumenthal, D.B., Dignös, 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. Lecture Notes in Computer Science, vol 13389. Springer, Cham. https://doi.org/10.1007/978-3-031-15740-0_16

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  • DOI: https://doi.org/10.1007/978-3-031-15740-0_16

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