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Hemşirelikte Puslu Mantığın Kullanımı

Year 2014, Volume: 1 Issue: 2, 68 - 76, 27.11.2015

Fatma Öz Bahanur Malak

Abstract

Hemşirelerin uygulamalarını gerçekleştirirken kararlarını hemşirelik felsefesine uygun olarak vermeleri, bakım kalitesini yükseltecek yöntemleri öğrenmeleri önemlidir. Hemşirelik ile ilişkisi yakın zamanda belirlenen puslu mantık, hemşirelik uygulamalarının felsefi konularına uygun olup, öznellik ve nesnellik arasındaki çatışmayı çözmeye, karmaşık hemşirelik fenomenlerinin bağlamsal anlamlarını kavramaya yardım eder. Hemşirelik uygulamalarındaki soruların siyah ve beyaz yanıtları arasındaki gri alanlara ilgi duyan puslu mantık, var olan ancak adlandırılamayan belirsizliklerin tanımlanmasını sağlar. Dereceli olan terimleri ifade eden puslu küme “bir özelliğe sahip olma” ile “bir özelliğe sahip olmama” arasındaki sınırın keskin olmadığını açıklayan kavramların anlaşılmasına olanak tanır. Klinik karar verme bilgiyi sentez ederek ayırabilmeyi ve seçeneklerin içinden en iyiyi seçerek uygulamaya koymayı gerektirir. Sonuç olarak, günümüz sağlık bakım ortamlarında çalışan hemşireler süreklilik gösteren bakımı verirken daha hızlı, akılcı ve karmaşık kararlar alarak çalışmak zorundadır. Uzman hemşirelere uygulamalarında doğru bir şekilde nasıl karar vereceklerini açıklayan puslu mantığın karar verme sürecinde güçlü bir yöntem olduğu düşünülür. Böylece, puslu mantık verilen kararlara eş zamanlı olarak destek, daha az önyargılı kararlar, zamanında daha kaliteli sağlık bakımı ve daha olumlu hasta sonuçları sağlar.

Anahtar Kelimeler: Hemşirelik, hemşire, klinik karar verme, puslu mantık, puslu düşünme

Keywords

Hemşirelik hemşire klinik karar verme puslu mantık puslu düşünme

References

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  • 2. Zadeh LA. Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets and Systems 1997; 90: 111-127.
  • 3. Türk Dil Kurumu Güncel Türkçe Sözlük. Erişim Adresi: www.tdkterim.gov.tr/bts/. Erişim Tarihi: 28.02.2013.
  • 4. Jensen R and Lopes MHBM. Nursing and Fuzzy Logic: an Integrative. Latino-Am. Enfermagem 2011 Jan-Feb; 19(1): 195-202.
  • 5. Yüksel Y. Puslu Mantık ve Felsefi Arka Planı. İstanbul Üniversitesi Sosyal Bilimler Enstitüsü Felsefe Anabilim Dalı, Yayınlanmamış Doktora Tezi, İstanbul, 2006. 6. Rolfe G. Science, abduction, and the fuzzy nurse: an exploration of expertise. Journal of Advanced Nursing 1997; 25: 1070–1075.
  • 7. Ural Ş, Özer M, Koç A, Şen A, Hacibekiroğlu G (editörler). “Puslu (Fuzzy) Mantık”, Mantık, Matematik ve Felsefe, I. Ulusal Sempozyumu 26-28 Eylül 2003 Assos-Çanakkale, T.C. İstanbul Kültür Üniversitesi Yayınları, İstanbul, 2004, s. 43-60.
  • 8. Im EO and Chee W. Nursing Philosophy 2003; 4: 53–60.
  • 9. Yıldırım B ve Özkahraman Ş. Hemşirelikte karar verme süreci. Electronic Journal of Vocational Colleges 2011 May/Mayıs; 165-173.
  • 10. Kaya H. Karar Verme ve Hemşirelik Eğitimi. Hemşirelik Bülteni 2000; 12(46):75-80.
  • 11. Thompson C and Dowding D. Decision making and judgement in nursing – an introduction. http:// books.google.com.tr/books, Churchill livingstone, 2002; 48-52.
  • 12. Ramnarayan P, Britto J. Paediatric clinical decision support systems. Arch Dis Child 2002; 87: 361-362.
  • 13. Lopes MHBM, Ortega NRS, Massad E, Marin HF. Model for differential nursing diagnosis of alterations in urinary elimination based on fuzzy logic. Comput Inform Nurs 2009; 27(5): 324-9.
  • 14. Innocent PR, John RI, Garibaldi JM. The fuzzy medical group at the centre for computational intelligence. Artificial Intelligence in Medicine 2001; 21(1-3):163-70.
  • 15. Playle JF. Humanism and positivism in nursing: contradictions and conflicts. Journal of Advanced Nursing 1995; 22: 979–984.
  • 16. Christensen M, Hewitt-Taylor J. From expert to tasks, expert nursing practice redefined? J Clin Nurs 2006; 15(12): 1531-9.
  • 17. Christensen M, Hewitt-Taylor J. Defining the expert ICU nurse. Intensive Crit Care Nurs 2006; 22(5): 301-7.
  • 18. Cave P. Fuzzy thinking. Journal of Advanced Nursing 1998; 28(2): 274-279.
  • 19. Abbod MF, Keyserlingk D, Linkens DA, Mahfouf M. Survey of utilisation of fuzzy technology in Medicine and Healthcare. Fuzzy Sets and Systems 2001; 120: 331–349.
  • 20. Nii M, Yamaguchi T, Mori Y, Takahashi Y, Uchinuno A, Sakashita R. Nursing-care text classification using additional term information from Web. 2011 IEEE International Conference on Fuzzy Systems; 2011 June 27-30, Taipei, Taiwan.
  • 21. Bosque EM. Symbiosis of nurse and machine through fuzzy logic: improved specificity of a neonatal pulse oximeter alarm Advances in Nursing Science 1995; 18(2): 67-75.
  • 22. Bosque EM. Pulse oximetry and intuition in the neonatal intensive care unit. Critical Care Nursing Clinics of North America 1995; 7(2): 219-25.
  • 23. Im EO, Chee W. Decision support computer program for cancer pain management. Comput Inform Nurs 2003; 21(1): 12-21.
  • 24. Chase JG, Agogue F, Starfinger C, Lam Z, Shaw GM, Rudge AD et al. Quantifying agitation in sedated ICU patients using digital imaging. Computer Methods and Programs in Biomedicine 2004; 76(2): 131- 41.
  • 25. Chase JG, Starfinger C, Lam Z, Agogue F, Shaw GM. Quantifying agitation in sedated ICU patients using heart rate and blood pressure. Physiological Measurement 2004; 25(4): 1037-51.
  • 26. Belal SY, Taktak AF, Nevill A, Spencer A. An intelligent ventilation and oxygenation management system in neonatal intensive care using fuzzy trend template fitting. Physiol Meas 2005; 26(4): 555-70.
  • 27. Blackwood B. Commentary: Nemoto T et al. (1999). Automatic control of pressure support mechanical ventilation using fuzzy logic. Nurs Crit Care 2008; 13(3):178-9.
  • 28. Anderson D, Luke RH, Keller JM, Skubic M, Rantz M, Aud M. Linguistic summarization of video for fall detection using voxel person and fuzzy logic. Comput Vis Image Underst 2009; 113(1): 80-9.
  • 29. Liatsos C, Hadjileontiadis LJ, Theocharis S, Petridou E, Margeli A, Skaltsas S, et al. Using higher-order crossings to distinguish liver regeneration indices in hepatectomized diabetic and non-diabetic rats. J Gastroenterol Hepatol 2005; 20(1): 126-34.
  • 30. Wang WL, Chang HJ, Liu AC, Chen YW. Research into care quality criteria for long-term care institutions. J Nurs Res 2007; 15(4): 255-64.
  • 31. Topaloğlu Ş, Selim H. Nurse scheduling using fuzzy modeling approach. Fuzzy Sets and Systems 2010; 161: 1543–1563.
  • 32. Eskandari A, Ziarati K. Nurse rostering using fuzzy logic: A case study. Journal of Industrial Engineering International 2008 July; 4(7): 69-82.

Year 2014, Volume: 1 Issue: 2, 68 - 76, 27.11.2015

Fatma Öz Bahanur Malak

Abstract

References

  • 1. Zadeh LA. From Computing with Numbers to Computing with Words – From Manipulation of Measurements to Manipulation of Perception. IEEE Transactions on Circuits and Systems 1999; 45(1):105-119.
  • 2. Zadeh LA. Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets and Systems 1997; 90: 111-127.
  • 3. Türk Dil Kurumu Güncel Türkçe Sözlük. Erişim Adresi: www.tdkterim.gov.tr/bts/. Erişim Tarihi: 28.02.2013.
  • 4. Jensen R and Lopes MHBM. Nursing and Fuzzy Logic: an Integrative. Latino-Am. Enfermagem 2011 Jan-Feb; 19(1): 195-202.
  • 5. Yüksel Y. Puslu Mantık ve Felsefi Arka Planı. İstanbul Üniversitesi Sosyal Bilimler Enstitüsü Felsefe Anabilim Dalı, Yayınlanmamış Doktora Tezi, İstanbul, 2006. 6. Rolfe G. Science, abduction, and the fuzzy nurse: an exploration of expertise. Journal of Advanced Nursing 1997; 25: 1070–1075.
  • 7. Ural Ş, Özer M, Koç A, Şen A, Hacibekiroğlu G (editörler). “Puslu (Fuzzy) Mantık”, Mantık, Matematik ve Felsefe, I. Ulusal Sempozyumu 26-28 Eylül 2003 Assos-Çanakkale, T.C. İstanbul Kültür Üniversitesi Yayınları, İstanbul, 2004, s. 43-60.
  • 8. Im EO and Chee W. Nursing Philosophy 2003; 4: 53–60.
  • 9. Yıldırım B ve Özkahraman Ş. Hemşirelikte karar verme süreci. Electronic Journal of Vocational Colleges 2011 May/Mayıs; 165-173.
  • 10. Kaya H. Karar Verme ve Hemşirelik Eğitimi. Hemşirelik Bülteni 2000; 12(46):75-80.
  • 11. Thompson C and Dowding D. Decision making and judgement in nursing – an introduction. http:// books.google.com.tr/books, Churchill livingstone, 2002; 48-52.
  • 12. Ramnarayan P, Britto J. Paediatric clinical decision support systems. Arch Dis Child 2002; 87: 361-362.
  • 13. Lopes MHBM, Ortega NRS, Massad E, Marin HF. Model for differential nursing diagnosis of alterations in urinary elimination based on fuzzy logic. Comput Inform Nurs 2009; 27(5): 324-9.
  • 14. Innocent PR, John RI, Garibaldi JM. The fuzzy medical group at the centre for computational intelligence. Artificial Intelligence in Medicine 2001; 21(1-3):163-70.
  • 15. Playle JF. Humanism and positivism in nursing: contradictions and conflicts. Journal of Advanced Nursing 1995; 22: 979–984.
  • 16. Christensen M, Hewitt-Taylor J. From expert to tasks, expert nursing practice redefined? J Clin Nurs 2006; 15(12): 1531-9.
  • 17. Christensen M, Hewitt-Taylor J. Defining the expert ICU nurse. Intensive Crit Care Nurs 2006; 22(5): 301-7.
  • 18. Cave P. Fuzzy thinking. Journal of Advanced Nursing 1998; 28(2): 274-279.
  • 19. Abbod MF, Keyserlingk D, Linkens DA, Mahfouf M. Survey of utilisation of fuzzy technology in Medicine and Healthcare. Fuzzy Sets and Systems 2001; 120: 331–349.
  • 20. Nii M, Yamaguchi T, Mori Y, Takahashi Y, Uchinuno A, Sakashita R. Nursing-care text classification using additional term information from Web. 2011 IEEE International Conference on Fuzzy Systems; 2011 June 27-30, Taipei, Taiwan.
  • 21. Bosque EM. Symbiosis of nurse and machine through fuzzy logic: improved specificity of a neonatal pulse oximeter alarm Advances in Nursing Science 1995; 18(2): 67-75.
  • 22. Bosque EM. Pulse oximetry and intuition in the neonatal intensive care unit. Critical Care Nursing Clinics of North America 1995; 7(2): 219-25.
  • 23. Im EO, Chee W. Decision support computer program for cancer pain management. Comput Inform Nurs 2003; 21(1): 12-21.
  • 24. Chase JG, Agogue F, Starfinger C, Lam Z, Shaw GM, Rudge AD et al. Quantifying agitation in sedated ICU patients using digital imaging. Computer Methods and Programs in Biomedicine 2004; 76(2): 131- 41.
  • 25. Chase JG, Starfinger C, Lam Z, Agogue F, Shaw GM. Quantifying agitation in sedated ICU patients using heart rate and blood pressure. Physiological Measurement 2004; 25(4): 1037-51.
  • 26. Belal SY, Taktak AF, Nevill A, Spencer A. An intelligent ventilation and oxygenation management system in neonatal intensive care using fuzzy trend template fitting. Physiol Meas 2005; 26(4): 555-70.
  • 27. Blackwood B. Commentary: Nemoto T et al. (1999). Automatic control of pressure support mechanical ventilation using fuzzy logic. Nurs Crit Care 2008; 13(3):178-9.
  • 28. Anderson D, Luke RH, Keller JM, Skubic M, Rantz M, Aud M. Linguistic summarization of video for fall detection using voxel person and fuzzy logic. Comput Vis Image Underst 2009; 113(1): 80-9.
  • 29. Liatsos C, Hadjileontiadis LJ, Theocharis S, Petridou E, Margeli A, Skaltsas S, et al. Using higher-order crossings to distinguish liver regeneration indices in hepatectomized diabetic and non-diabetic rats. J Gastroenterol Hepatol 2005; 20(1): 126-34.
  • 30. Wang WL, Chang HJ, Liu AC, Chen YW. Research into care quality criteria for long-term care institutions. J Nurs Res 2007; 15(4): 255-64.
  • 31. Topaloğlu Ş, Selim H. Nurse scheduling using fuzzy modeling approach. Fuzzy Sets and Systems 2010; 161: 1543–1563.
  • 32. Eskandari A, Ziarati K. Nurse rostering using fuzzy logic: A case study. Journal of Industrial Engineering International 2008 July; 4(7): 69-82.
There are 31 citations in total.

Details

Primary Language Turkish
Journal Section Articles
Authors

Fatma Öz

Bahanur Malak

Publication Date November 27, 2015
Submission Date November 27, 2015
Published in Issue Year 2014 Volume: 1 Issue: 2

Cite

Vancouver Öz F, Malak B. Hemşirelikte Puslu Mantığın Kullanımı. JOHUFON. 2015;1(2):68-76.
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