Abstract
In general, quality of life is the perceived quality of an individual’s daily life, that is, an assessment of their well-being or lack thereof. Life quality of individuals is very important for involves several factors such as social, economic, psychological, spiritual or medical state. The information technologies can help with the management of the services for the healthcare of chronic patients. It was developed and implemented a Quality of Life platform using information technologies and with application of statistical methods to access the information of clinical data of patients with cancer from otorhinolaryngology and Head and Neck services of an oncologic institution. The sample was composed of 3013 patients. The results show that there are variables with significant predictors for the Quality of Life: years of smoking (p value 0.049) and size of the tumor (p value < 0.001). In conclusion statistical methods allow having access to additional information helping the physicians to be able to know the quality of life and produce a well-informed clinical decision.
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References
Marchibroda, J.M.: The impact of health information technology on collaborative chronic care management. J. Manag. Care Pharm. 14(2 suppl.), 3–11 (2008)
Tenório, J., Hummel, A., Sdepanian, V., Pisa, I., Marin, H.F.: Experiências internacionais da aplicação de sistemas de apoio à decisão clínica em gastroenterologia. J. Health Inf. 3(1), 27–31 (2011)
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. In: Annual International Conference of the IEEE Eng. in Medicine and Biology Society, EMBC 2009, September 3-6, pp. 5633–5636 (2009)
Parrella, A., Dalton, C.B., Pearce, R., Litt, B.: ASPREN surveillance system for influenza-like illness: A comparison with FluTracking and the National Notifiable Diseases Surveillance System. Australian Family Physician 38(11), 932–936 (2009)
Berner, E.S.: Clinical decision support system: State of the Art. AHRQ Publication, nº 09.0069 – EF. Agency for Healhcare Research and Quality, Rockville, Maryland (2009)
Balfour, D.C., Evans, S., Januska, J., Lee, H.Y., Lewis, S.J., Nolan, S.R., Noga, M., Stemple, C., Thapar, K.: Health information technology - results from a roundtable discussion. Journal of Managed Care Pharmacy 15(1 suppl. A), 10–17 (2009)
Rogausch, A., Sigle, J., Seibert, A., Thüring, S., Kochen, M., Himmel, M.: Feasibility and acceptance of electronic quality of life assessment in general practice: an implementation study. Health and Quality of Life Outcomes (2009)
Pagliari, C., Donnan, P., Morrison, J., Ricketts, I., Gregor, P., Sullivan, F.: Adoption and perception of electronic clinical communications in Scotland. Inform. Prim. Care 13(2), 97–104 (2005)
Tantivess, S., Teerawattananon, Y., 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)
Sivic, S., Gojkovic, L., Huseinagic, S.: Evaluation of an information system model for primary health care. Stud. Health Technol. Inform. 150, 106–110 (2009)
Stevanović, R., Stanić, A., Varga, S.: Information system in primary health care. Acta Med. Croatica 59(3), 209–212 (2005)
Adini, B., Peleg, K., Cohen, R., Laor, D.: A national system for disseminating information on victims during mass casualty incidents. Disasters 34(2), 542–551 (2010)
Daniel, C., García, R.M., Bourquard, K., Henin, D., Schrader, T., Della Mea, V., Gilbertson, J., Beckwith, B.A.: Standards to support information systems integration in anatomic pathology. Arch. Pathol. Lab. Med. 133(11), 1841–1849 (2009)
Deshpande, K., Ganz, A.: DiNAR: Health monitoring of IT systems in emergency response. In: Conference Proceedings IEEE Eng. Med. Biol. Soc., vol. 1, pp. 1699–1702 (2009)
McFarlane, A., Wielgosz, A.: Strengthening information systems for heart health in Canada. Can. J. Cardiol. 25(11), 631–634 (2009)
Gonçalves, J., Rocha, Á.: Decision support system for quality of life in head and neck oncology patients. Head & Neck Oncology 4(3), 1–9 (2012)
Randall, E., Schumacker, P.: Item Response Theory. Applied Measurement Associates (2005)
Castro, S.: Teoria de Resposta ao Item: aplicação na avaliação de sintomas depressivos. PhD Thesis Univ. Fed. Rio Grande do Sul (2008)
Mead, R.: The Measurement Theory of Georg Rasch. Data Recognition Corporation (2008)
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Faria, B.M., Gonçalves, J., Reis, L.P., Rocha, Á. (2015). A Platform for Assessing Cancer Patients’ Quality of Life. In: Rocha, A., Correia, A., Costanzo, S., Reis, L. (eds) New Contributions in Information Systems and Technologies. Advances in Intelligent Systems and Computing, vol 354. Springer, Cham. https://doi.org/10.1007/978-3-319-16528-8_6
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DOI: https://doi.org/10.1007/978-3-319-16528-8_6
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