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Monitoring and Prognosis System Based on the ICF for People with Traumatic Brain Injury

Author

Listed:
  • Laia Subirats

    (eHealth Department, Eurecat, Roc Boronat, 08018 Barcelona, Spain
    Universitat Autònoma de Barcelona, Campus UAB, 08193 Bellaterra, Spain)

  • Raquel Lopez-Blazquez

    (Institut Guttmann, Institut Universitari de Neurorehabilitació adscrit a la UAB, Camí de Can Ruti, SN 08916, Badalona, Spain)

  • Luigi Ceccaroni

    (1000001 Labs, Alzina 52, 08024 Barcelona, Spain)

  • Mariona Gifre

    (Institut Guttmann, Institut Universitari de Neurorehabilitació adscrit a la UAB, Camí de Can Ruti, SN 08916, Badalona, Spain)

  • Felip Miralles

    (eHealth Department, Eurecat, Roc Boronat, 08018 Barcelona, Spain)

  • Alejandro García-Rudolph

    (Institut Guttmann, Institut Universitari de Neurorehabilitació adscrit a la UAB, Camí de Can Ruti, SN 08916, Badalona, Spain)

  • Jose María Tormos

    (Institut Guttmann, Institut Universitari de Neurorehabilitació adscrit a la UAB, Camí de Can Ruti, SN 08916, Badalona, Spain)

Abstract

The objective of this research is to provide a standardized platform to monitor and predict indicators of people with traumatic brain injury using the International Classification of Functioning, Disability and Health, and analyze its potential benefits for people with disabilities, health centers and administrations. We developed a platform that allows automatic standardization and automatic graphical representations of indicators of the status of individuals and populations. We used data from 730 people with acquired brain injury performing periodic comprehensive evaluations in the years 2006–2013. Health professionals noted that the use of color-coded graphical representation is useful for quickly diagnose failures, limitations or restrictions in rehabilitation. The prognosis system achieves 41% of accuracy and sensitivity in the prediction of emotional functions, and 48% of accuracy and sensitivity in the prediction of executive functions. This monitoring and prognosis system has the potential to: (1) save costs and time, (2) provide more information to make decisions, (3) promote interoperability, (4) facilitate joint decision-making, and (5) improve policies of socioeconomic evaluation of the burden of disease. Professionals found the monitoring system useful because it generates a more comprehensive understanding of health oriented to the profile of the patients, instead of their diseases and injuries.

Suggested Citation

  • Laia Subirats & Raquel Lopez-Blazquez & Luigi Ceccaroni & Mariona Gifre & Felip Miralles & Alejandro García-Rudolph & Jose María Tormos, 2015. "Monitoring and Prognosis System Based on the ICF for People with Traumatic Brain Injury," IJERPH, MDPI, vol. 12(8), pages 1-16, August.
    • Handle: RePEc:gam:jijerp:v:12:y:2015:i:8:p:9832-9847:d:54345
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    References listed on IDEAS

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    1. Laia Subirats & Luigi Ceccaroni & Felip Miralles, 2012. "Knowledge Representation for Prognosis of Health Status in Rehabilitation," Future Internet, MDPI, vol. 4(3), pages 1-14, August.
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    Cited by:

    1. Bamel, Umesh & Talwar, Shalini & Pereira, Vijay & Corazza, Laura & Dhir, Amandeep, 2023. "Disruptive digital innovations in healthcare: Knowing the past and anticipating the future," Technovation, Elsevier, vol. 125(C).
    2. Laia Subirats & Natalia Reguera & Antonio Miguel Bañón & Beni Gómez-Zúñiga & Julià Minguillón & Manuel Armayones, 2018. "Mining Facebook Data of People with Rare Diseases: A Content-Based and Temporal Analysis," IJERPH, MDPI, vol. 15(9), pages 1-13, August.

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