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Umedicine: A System for Clinical Practice Support and Data Analysis

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10494))

Abstract

Recording patient clinical data in a comprehensive and easy way is very important for health care providers. However, and although there are information systems to facilitate the storage and access to patient data, many records are still in paper. Even when data is stored electronically, systems often are complex to use and do not provide means to gather statistical information about a population of patients, thus limiting the usefulness of the data. Physicians often give up searching for relevant information to support their medical decisions because the task is too time-consuming. This paper proposes Umedicine, a web-based software application in Portuguese that addresses current limitations of clinical information systems. Umedicine is an application for physicians, patients and administrative staff that keeps clinical data (e.g., symptoms, clinical examination results, and treatments prescribed) up to date on a database in a structured way. It also provides easy and quick access to a large amount of clinical data collected over time. Furthermore, Umedicine supports the application of a particular clustering algorithm and a visualization module for analyzing patient time-series data, to identify evolution patterns. Preliminary user tests revealed promising results, showing that users were able to identify the evolution of groups of patients over time and their common characteristics.

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Notes

  1. 1.

    https://spring.io/.

  2. 2.

    https://tiles.apache.org/.

  3. 3.

    https://spring.io.

  4. 4.

    We are aware that synthetic data may not have the same behaviour as real data, but our goal was to identify groups of patients.

  5. 5.

    http://www.glintt.com/.

  6. 6.

    https://www.imed.com.pt/.

  7. 7.

    http://www.medicineone.net/.

  8. 8.

    https://iclinic.com.br/.

  9. 9.

    https://hidoctor.com.br/.

  10. 10.

    http://medicaleconomics.modernmedicine.com/medical-economics/content/tags/top100ehrs/top-100-ehr-companies-part-1-4.

  11. 11.

    https://store.cerner.com/items/2.

  12. 12.

    https://www.eclinicalworks.com/.

  13. 13.

    http://www.snomed.org.

  14. 14.

    http://loinc.org.

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Acknowledgements

This work was supported by national funds through Fundação para a Ciência e a Tecnologia (FCT) with reference UID/CEC/50021/2013 (INESC-ID) and UID/CEC/00408/2013 (LASIGE).

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Correspondence to Helena Galhardas .

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Lages, N.F., Caetano, B., Fonseca, M.J., Pereira, J.D., Galhardas, H., Farinha, R. (2017). Umedicine: A System for Clinical Practice Support and Data Analysis. In: Begoli, E., Wang, F., Luo, G. (eds) Data Management and Analytics for Medicine and Healthcare. DMAH 2017. Lecture Notes in Computer Science(), vol 10494. Springer, Cham. https://doi.org/10.1007/978-3-319-67186-4_9

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  • DOI: https://doi.org/10.1007/978-3-319-67186-4_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67185-7

  • Online ISBN: 978-3-319-67186-4

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