Abstract
The history of patient classification in nursing dates back to the period of Florence Nightingale. The first and the foremost condition for providing quality nursing care, which is measured by care standards, and determined by number of hours of actual care, is the appropriate number of nurses. Patient classification criteria are discussed in this paper. Hybrid classification model based on learning vector quantization (LVQ) networks and self-organising maps (SOM) are purposed. It is possible to discus three types of experimental results. First result could be assessment of Braden scale and Mors scale by LVQ. Second result, the time for nursing logistics activities. The third is possibility to predict appropriate number of nurses for providing quality nursing care. This research was conducted on patients from Institute of Neurology, Clinical Centre of Vojvodina.
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References
Rimac, B., Bišćan, J.: Nursing Paradigm and Patient Safety. Medix 86, 167–170 (2010)
Twig, D., Duffield, C.: A Review of Workload Measures: A Context for a New Staffing Methodology in Western Australia. International Journal of Nursing Studies 46, 132–140 (2009)
Abraham, A., Corchado, E., Corchado, J.M.: Hybrid Learning Machines. Neurocomputing 72(13-15), 2729–2730 (2009)
Corchado, E., Abraham, A., de Carvalho, A.: Hybrid Intelligent Algorithms and Applications. Information Science 180(14), 2633–2634 (2010)
Derrac, J., García, S., Herrera, F.: A First Study on the Use of Coevolutionary Algorithms for Instance and Feature Selection. In: Corchado, E., Wu, X., Oja, E., Herrero, Á., Baruque, B. (eds.) HAIS 2009. LNCS(LNAI), vol. 5572, pp. 557–564. Springer, Heidelberg (2009)
Sarnecki, A., Haas, S., Stevens, K.A., Willemsen, J.: Design and Implementation of a Patient Clasification System for Rehabilitation Nursing. Journal of Nursing Administration 28(3), 35–43 (1998)
Vries, G.: Nursing Workload Measurement as management Information. European Journal of Operational Research 29, 199–208 (1987)
Martins, P.A., Arantes, E.C., Forcella, H.T.: Patient Classification System in Psychiatric Nursing: Clinical Validation. Journal of School Nursing 42(2), 223–241 (2008)
Williams, S., Crouch, R.: Emergency Department Patient Classification System: A Systematic Review. Accident and Emergency Nursing 14(3), 160–170 (2006)
Giovannetti, P.: Understanding patient classification systems. Journal of Nursing Administration 9(2), 4–9 (1979)
Ćorluka, V.: Standardized care purport – new nursing care quality. Health Care 34(3), 25–35 (2005)
Warstler, M.E.: Cyclic work schedules and a nonnurse coordinator of staffing. Journal of Nursing Administration 3(6), 45–51 (1973)
Wills, E.M.: Grand Nursing Theories Based on Human Needs. In: McEwen, M., Wills, E. (eds.) Theoretical Based for Nursing. Lippincot Williams & Wilkins (2007)
Ćorluka, V., Aleksić, Ž., Savićević, M.: Instruction on Record Keeping in Health Protection, Family Care, Field Nurse Care and Health Care. Federal Institute for Health Improvement and Protection, Beograd (2000)
Croatian Chamber of Medical Nurses. Patient Classification According to Their Health Care Needs (2006), http://www.hkms.hr
Milutinović, D., Martinov-Cvejin, M., Simić, S.: Padovi i povrede hospitalizovanih pacijenata kao pokazatelji kvaliteta rada bolnice. Medicinski pregled LXII (5-6), 249–257 (2009)
Torrecilla, J., Rojo, E., Oliet, M., Domínguez, J.C., Rodrínguez, F.: Self-Organizing Maps and Learning Vector Quantization Networks as Tools to Identify Vegetable Oils and Detect adulterations of Extra Virgin Olive Oil. In: Pierucci, S. (ed.) ESCAPE, vol. 20, Elsevier, Amsterdam (2010)
Simić, D., Kovačević, I., Simić, S.: Insolvency Prediction for Assessing Corporate Financial Health. Logic Journal of IGPL (2011), doi:10.1093/jigpal/jzr009
Wozniak, M., Zmyslony, M.: Designing Fusers on the Basis of Discriminants – Evolutionary and Neural Methods of Training. In: Graña Romay, M., Corchado, E., Garcia Sebastian, M.T. (eds.) HAIS 2010. LNCS(LNAI), vol. 6076, pp. 590–597. Springer, Heidelberg (2010)
Simin, D., Milutinović, D., Brestovački, B., Simić, S., Cigić, T.: Attitude of health science students towards interprofesional education. HealthMED Journal 4(2), 461–469 (2010)
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Simić, D., Milutinović, D., Simić, S., Suknaja, V. (2011). Hybrid Patient Classification System in Nursing Logistics Activities. In: Corchado, E., Kurzyński, M., Woźniak, M. (eds) Hybrid Artificial Intelligent Systems. HAIS 2011. Lecture Notes in Computer Science(), vol 6679. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21222-2_51
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DOI: https://doi.org/10.1007/978-3-642-21222-2_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21221-5
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