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Journal of Medical Systems

, 39:114 | Cite as

A Clinical Support System Based on Quality of Life Estimation

  • Brígida Mónica FariaEmail author
  • Joaquim Gonçalves
  • Luis Paulo Reis
  • Álvaro Rocha
Patient Facing Systems
Part of the following topical collections:
  1. Health Information Systems & Technologies

Abstract

Quality of life is a concept influenced by social, economic, psychological, spiritual or medical state factors. More specifically, the perceived quality of an individual’s daily life is an assessment of their well-being or lack of it. In this context, information technologies may help on the management of services for healthcare of chronic patients such as estimating the patient quality of life and helping the medical staff to take appropriate measures to increase each patient quality of life. This paper describes a Quality of Life estimation system developed using information technologies and the application of data mining algorithms to access the information of clinical data of patients with cancer from Otorhinolaryngology and Head and Neck services of an oncology institution. The system was evaluated with a sample composed of 3013 patients. The results achieved show that there are variables that may be significant predictors for the Quality of Life of the patient: years of smoking (p value 0.049) and size of the tumor (p value < 0.001). In order to assign the variables to the classification of the quality of life the best accuracy was obtained by applying the John Platt’s sequential minimal optimization algorithm for training a support vector classifier. In conclusion data mining techniques allow having access to patients additional information helping the physicians to be able to know the quality of life and produce a well-informed clinical decision.

Keywords

Quality of life Cancer Information technologies Clinical support system Data mining 

Notes

Acknowledgments

This work was funded by QoLis - Quality of Life Platform Project, N°2013/34034 QREN SI I&DT, (NUP, NORTE-07-0202-FEDER-034Ú34). The authors also acknowledge: LIACC (PEst-OE/EEI/UI0027/2014).

References

  1. 1.
    Marchibroda, J. M., The impact of health information technology on collaborative chronic care management. J. Manag. Care Pharm. 14(2 Suppl):3–11, 2008.Google Scholar
  2. 2.
    Tenório, J., Hummel, A., Sdepanian, V., Pisa, I., and Marin, H. F., Experiências internacionais da aplicação de sistemas de apoio à decisão clínica em gastroenterologia. J Health Inf 3(1):27–31, 2011.Google Scholar
  3. 3.
    Georga, E., Protopappas, V., Guillen, A., Fico, G., Ardigo, D., Arredondo, M. T., Exarchos T. P., Polyzos, D., Fotiadis, D. I., Data mining for blood glucose prediction and knowledge discovery in diabetic patients: The METABO diabetes modeling and management system, Eng. in Medicine and Biology Society, EMBC 2009. Annual International Conference of the IEEE, pp. 5633-5636, 2009.Google Scholar
  4. 4.
    Parrella, A., Dalton, C. B., Pearce, R., and Litt, J. C. B., ASPREN surveillance system for influenza-like illness: A comparison with FluTracking and the National Notifiable Diseases Surveillance System. Aust. Fam. Physician 38(11):932–936, 2009.PubMedGoogle Scholar
  5. 5.
    Berner, E. S., Clinical decision support system: State of the Art. AHRQ Publication, n° 09.0069 – EF. Agency for Healhcare Research and Quality, Rockville, 2009.Google Scholar
  6. 6.
    Balfour, D. C., Evans, S., Januska, J., Lee, H. Y., Lewis, S. J., Nolan, S. R., Noga, M., Stemple, C., and Thapar, K., Health information technology - results from a roundtable discussion. J. Manag. Care Pharm. 15(1 Suppl A):10–17, 2009.PubMedGoogle Scholar
  7. 7.
    Rogausch, A., Sigle, J., Seibert, A., Thüring, S., Kochen, M., and Himmel, M., Feasibility and acceptance of electronic quality of life assessment in general practice: an implementation study. Health Qual. Life Outcomes 7:51, 2009.PubMedCentralCrossRefPubMedGoogle Scholar
  8. 8.
    Pagliari, C., Donnan, P., Morrison, J., Ricketts, I., Gregor, P., and Sullivan, F., Adoption and perception of electronic clinical communications in Scotland. Inform. Prim. Care 13(2):97–104, 2005.PubMedGoogle Scholar
  9. 9.
    Tantivess, S., Teerawattananon, Y., and Mills, A., Strengthening cost-effectiveness analysis in Thailand through the establishment of the health intervention and technology assessment program. Pharmacoeconomics 27(11):931–945, 2009.CrossRefPubMedGoogle Scholar
  10. 10.
    Sivic, S., Gojkovic, L., and Huseinagic, S., Evaluation of an information system model for primary health care. Stud. Health Technol. Inform. 150:106–110, 2009.PubMedGoogle Scholar
  11. 11.
    Stevanović, R., Stanić, A., and Varga, S., Information system in primary health care. Acta Med. Croatica 59(3):209–212, 2005.PubMedGoogle Scholar
  12. 12.
    Adini, B., Peleg, K., Cohen, R., and Laor, D., A national system for disseminating information on victims during mass casualty incidents. Disasters 34(2):542–551, 2010.CrossRefPubMedGoogle Scholar
  13. 13.
    Daniel, C., García, R. M., Bourquard, K., Henin, D., Schrader, T., Della Mea, V., Gilbertson, J., and Beckwith, B. A., Standards to support information systems integration in anatomic pathology. Arch. Pathol. Lab. Med. 133(11):1841–1849, 2009.PubMedGoogle Scholar
  14. 14.
    Deshpande, K., and Ganz, A., DiNAR: Health monitoring of IT systems in emergency response. Conf Proc IEEE Eng Med Biol Soc 1:1699–1702, 2009.Google Scholar
  15. 15.
    McFarlane, A., and Wielgosz, A., Strengthening information systems for heart health in Canada. Can. J. Cardiol. 25(11):631–634, 2009.PubMedCentralCrossRefPubMedGoogle Scholar
  16. 16.
    Pimentel, F., Qualidade de Vida do Doente Oncológico. De autor, 2003.Google Scholar
  17. 17.
    Brereton, N., Bodger, K., Kamm, M. A., Hodgkins, P., Yan, S., and Akehurst, R., A cost-effectiveness analysis of MMX mesalazine compared with mesalazine in the treatment of mild-to-moderate ulcerative colitis from a UK perspective. J. Med. Econ. 13(1):148–161, 2010.CrossRefPubMedGoogle Scholar
  18. 18.
    Moraes, E., Campos, G. N., Figlie, N. B., Laranjeira, R., and Ferraz, M. B., Introductory concepts of health economics and the social impact of the alcohol misuse. Rev. Bras. Psiquiatr. 28:321–325, 2006.CrossRefPubMedGoogle Scholar
  19. 19.
    Faria, B. M., Gonçalves, J., Reis, L. P., and Rocha, A., A platform for assessing cancer patients’ quality of life. Adv Intell Syst Comput 354:51–61, 2015. Springer, vol 2.CrossRefGoogle Scholar
  20. 20.
    Gonçalves, J., and Rocha, Á., Decision support system for quality of life in head and neck oncology patients. Head Neck Oncol. 4(3):1–9, 2012.Google Scholar
  21. 21.
    Randall E, Schumacker P (2005) Item response theory. Applied Measurement Associates.Google Scholar
  22. 22.
    Castro, S., Teoria de Resposta ao Item: Aplicação na avaliação de sintomas depressivos. PhD Thesis Univ. Fed. Rio Grande do Sul, 2008.Google Scholar
  23. 23.
    Mead, R., The Measurement Theory of Georg Rasch. Data Recognition Corporation, 2008.Google Scholar
  24. 24.
    Rapidminer, Available at: http://rapidminer.com/, Consulted in: April 2015.
  25. 25.
    Zhang, H., The Optimality of Naive Bayes. Faculty of Computer Science, University of New Brunswick, Frederic-ton, New Brunswick, Canada, American Association for Artificial Intelligence, 2004.Google Scholar
  26. 26.
    Platt, J., Machines using sequential minimal optimization. In: Schoelkopf, B., Burges, C., and Smola, A. (Eds.), Advances in Kernel Methods - Support Vector Learning, 1998.Google Scholar
  27. 27.
    Keerthi, S. S., Shevade, S. K., Bhattacharyya, C., and Murthy, K. R. K., Improvements to Platt’s SMO Algorithm for SVM Classifier Design. Neural Comput. 13(3):637–649, 2001.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Brígida Mónica Faria
    • 1
    • 2
    Email author
  • Joaquim Gonçalves
    • 1
    • 3
  • Luis Paulo Reis
    • 1
    • 4
  • Álvaro Rocha
    • 1
    • 5
  1. 1.LIACC – Lab. Inteligência Artificial e Ciência de ComputadoresPortoPortugal
  2. 2.ESTSP/IPP – Esc. Sup. Tecnologia da Saúde do Porto/Instituto Politécnico do PortoVila Nova de GaiaPortugal
  3. 3.EST/IPCA – Esc. Superior de Tecnologia/Instituto Politécnico do Cávado e do AveVila FrescainhaPortugal
  4. 4.Departamento de Sistemas de InformaçãoEEUM – Escola de Engenharia da Universidade do MinhoGuimarãesPortugal
  5. 5.Departamento de Engenharia InformáticaUniversidade de CoimbraCoimbraPortugal

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