Öz
Değerlendirme Tıp bilişimi için oldukça önemli bir olgudur. Yatırımcılar ve yöneticiler, sistemlerini geliştirebilmek için, zayıf ve güçlü yönlerini bilmek isterler. Bilimsel literatürde birçok hastane bilgi sistemi değerlendirme platformu önerilmiştir. Sağlık, bulanık mantık kullanımına çok uygun olmasına rağmen bunlardan hiçbiri bulanık mantık metodolojilerini kullanmamaktadır. Bizim önerdiğimiz değerlendirme platformu bulanık mantığın klasik değerlendirme metotları ile arasındaki farkı incelemek üzere kullanılmıştır. Sonuçlar hem net sayılar kullanılarak hesaplanmış hem de bulanık mantık kullanılarak hesaplanmış, aradaki fark incelenmiştir. 17 değerlendirme değişkeninden sekizi istatiksel olarak anlamlı olarak farklı çıkmıştır. Bu sonuç bize bulanık ortamlarda net sayılar ile yapılan değerlendirmelerde hassasiyet kaybı olacağını göstermektedir. Bulanık mantık kullanımı ile, net olmayan sınırları da dikkate almasından dolayı, daha gerçekçi değerlendirmeler yapmamıza yardımcı olacağı sonucuna varılmıştır.
Anahtar Kelimeler
Hastane Bilgi Sistemi Bulanık Mantık Değerlendirme Kullanıcı Beklentisi Cronbach´s Alpha Ki-kare
Kaynakça
- Al-Yaseen H., Al-Jaghoub S., Al-Shorbaji M., & Salim M.(2010). Post-Implementation Evaluation of HealthCare Information Systems in Developing Countries. The Electronic Journal Information Systems Evaluation 13(1), 9-16.
- Ammenwerth E., Gräber S., Herrmann G., Bürkle T., & König J. (2003). Evaluation of health information systems—problems and challenges. International Journal of Medical Informatics 71,125-135.
- Ammenwerth E., Iller C. & Mahler C. (2006). IT-adoption and the interaction of task, technology and individuals: a fit framework and a case study. BMC Medical Informatics and Decision Making, 6, 1-113.
- Chen M.F., Tzeng G.H., & Ding C.G. (2008). Combining fuzzy AHP with MDS in identifying the preference similarity of alternatives. Applied Soft Computing 8(1),110–117.
- Chen Y. , & Chang K. (2006). Applying Fuzzy Multi-criteria Decision Method to Evaluate Key Capabilities of Taiwan Motion Picture Companies. Proceedings of the 2006 Joint Conference on Information Sciences, JCIS 2006, Kaohsiung, Taiwan, 123-137.
- Chen Y., Richard Y.K., Fung A., & Tang J. (2006). Rating technical attributes in fuzzy QFD by integrating fuzzy weighted average method and fuzzy expected value operator. European Journal of Operational Research 174,1553–1566.
- Dadone P. (2001). Design Optimization of Fuzzy Logic Systems. Phd dissertation, 1-35.
- Dixon D.R. (2006). The behavioral side of information technology. International Journal of Medical Informatics 56,117-130.
- Gürsel G., Zayim N., Gülkesen K.H., Arifoğlu A., & Saka O. (2014) . A new approach in the evaluation of hospital information systems. Turkish Journal of Electrical Engineering & Computer Sciences, 22(1), 214-222.
- Heeks R. (2006). Health information systems: Failure, success and improvisation. International Journal of Medical Informatics 75,125-13.7.
- Goodhue D.L., Klein B.D., & March ST. (2008). User evaluations of IS as surrogates for objective performance. Information and Management 38,87-101.
- Furubo J.E., Rist R.C., & Sandahl R. (2002). International Atlas of Evaluation. London: Transaction Publishers. 1–26.
- Laarhoven P.J.M., & Pedrycz W. A. (1983). Ffuzzy extension of Saaty’s priority theory. Fuzzy Sets and Systems 11,229–241.
- Lazm A., & Wahab N. A. (2010) . Fuzzy Decision Making Approcah in Evaluating Ferry Service Quality Management. Research and Practice 2(1),94-107.
- Lee M.S., San Y.H., & Hsu Y.R. (2011). A study of the key success factors of the ecotourism industry in Taiwan. African Journal of Business Management 5(2),627-640.
- Lin C.T., & Chen Y.T. (2004) . Bid/no-bid decision-making – a fuzzy linguistic approach. International Journal of Project Management 22,585–593.
- Kazanjian A., & Green A.J. (2002). Beyond effectiveness: the evaluation of information systems using a comprehensive health technology assessment framework. Computers in Biology and Medicine 32,165–177.
- Kushniruk A.W., & Patel V. (2004). Cognitive and usability engineering methods for the evaluation of clinical information systems. Journal of Biomedical Informatics 37,56–76.
- Protti D. A. (2002). A proposal to use a balanced scorecard to evaluate Information for Health: an information strategy for the modern NHS (1998–2005). Computers in Biology and Medicine, 32,221–236.
- Raj P.A., & Kumar D.N. (1999). Ranking alternatives with fuzzy weights using maximizing set and minimizing set. Fuzzy Sets and Systems 105,365-375.
- Shaw N.T. (2002). CHEATS: a generic information communication technology (ICT) evaluation framework. Computed Biology and Medicine 32,209-220.
- Yusof M.M., Kuljis J., Papzafeiropoulou A., & Stergioulas L.K. (2008). An evaluation framework for Health Information Systems: human, organization and technology-fit factors (HOT-fit). International Journal of Medical Informatics. 77,386-398.
- Zadeh L.A. (1965). Fuzzy Sets, Information and Control. 8, 338-352.
Öz
Evaluation is an important subject for medical informatics domain. The investors and managers need to know the success level and poor sides of their information system to make improvements. There are many evaluation frameworks proposed for healthcare in the literature. Although healthcare is very suitable, none of the existing evaluation frameworks employ fuzzy logic methodologies. Our proposed expectation based evaluation framework in the previous work for hospital information systems is used for examining the difference and contribution of fuzzy logic use in evaluation. The results of the framework are recomputed both by crisp computation method. The difference between fuzzy and crisp computation is examined. The study shows that use of fuzzy logic makes a difference. Eight 8 of the 17 variables appeared to have statistically significant difference. Using crisp values in evaluation may result in loss of precision. We believe that fuzzy logic helps to obtain a more realistic evaluation by taking blurred boundaries into consideration.
Anahtar Kelimeler
Hospital Information System Fuzzy logic Evaluation User Expectation Cronbach´s Alpha chi-square
Kaynakça
- Al-Yaseen H., Al-Jaghoub S., Al-Shorbaji M., & Salim M.(2010). Post-Implementation Evaluation of HealthCare Information Systems in Developing Countries. The Electronic Journal Information Systems Evaluation 13(1), 9-16.
- Ammenwerth E., Gräber S., Herrmann G., Bürkle T., & König J. (2003). Evaluation of health information systems—problems and challenges. International Journal of Medical Informatics 71,125-135.
- Ammenwerth E., Iller C. & Mahler C. (2006). IT-adoption and the interaction of task, technology and individuals: a fit framework and a case study. BMC Medical Informatics and Decision Making, 6, 1-113.
- Chen M.F., Tzeng G.H., & Ding C.G. (2008). Combining fuzzy AHP with MDS in identifying the preference similarity of alternatives. Applied Soft Computing 8(1),110–117.
- Chen Y. , & Chang K. (2006). Applying Fuzzy Multi-criteria Decision Method to Evaluate Key Capabilities of Taiwan Motion Picture Companies. Proceedings of the 2006 Joint Conference on Information Sciences, JCIS 2006, Kaohsiung, Taiwan, 123-137.
- Chen Y., Richard Y.K., Fung A., & Tang J. (2006). Rating technical attributes in fuzzy QFD by integrating fuzzy weighted average method and fuzzy expected value operator. European Journal of Operational Research 174,1553–1566.
- Dadone P. (2001). Design Optimization of Fuzzy Logic Systems. Phd dissertation, 1-35.
- Dixon D.R. (2006). The behavioral side of information technology. International Journal of Medical Informatics 56,117-130.
- Gürsel G., Zayim N., Gülkesen K.H., Arifoğlu A., & Saka O. (2014) . A new approach in the evaluation of hospital information systems. Turkish Journal of Electrical Engineering & Computer Sciences, 22(1), 214-222.
- Heeks R. (2006). Health information systems: Failure, success and improvisation. International Journal of Medical Informatics 75,125-13.7.
- Goodhue D.L., Klein B.D., & March ST. (2008). User evaluations of IS as surrogates for objective performance. Information and Management 38,87-101.
- Furubo J.E., Rist R.C., & Sandahl R. (2002). International Atlas of Evaluation. London: Transaction Publishers. 1–26.
- Laarhoven P.J.M., & Pedrycz W. A. (1983). Ffuzzy extension of Saaty’s priority theory. Fuzzy Sets and Systems 11,229–241.
- Lazm A., & Wahab N. A. (2010) . Fuzzy Decision Making Approcah in Evaluating Ferry Service Quality Management. Research and Practice 2(1),94-107.
- Lee M.S., San Y.H., & Hsu Y.R. (2011). A study of the key success factors of the ecotourism industry in Taiwan. African Journal of Business Management 5(2),627-640.
- Lin C.T., & Chen Y.T. (2004) . Bid/no-bid decision-making – a fuzzy linguistic approach. International Journal of Project Management 22,585–593.
- Kazanjian A., & Green A.J. (2002). Beyond effectiveness: the evaluation of information systems using a comprehensive health technology assessment framework. Computers in Biology and Medicine 32,165–177.
- Kushniruk A.W., & Patel V. (2004). Cognitive and usability engineering methods for the evaluation of clinical information systems. Journal of Biomedical Informatics 37,56–76.
- Protti D. A. (2002). A proposal to use a balanced scorecard to evaluate Information for Health: an information strategy for the modern NHS (1998–2005). Computers in Biology and Medicine, 32,221–236.
- Raj P.A., & Kumar D.N. (1999). Ranking alternatives with fuzzy weights using maximizing set and minimizing set. Fuzzy Sets and Systems 105,365-375.
- Shaw N.T. (2002). CHEATS: a generic information communication technology (ICT) evaluation framework. Computed Biology and Medicine 32,209-220.
- Yusof M.M., Kuljis J., Papzafeiropoulou A., & Stergioulas L.K. (2008). An evaluation framework for Health Information Systems: human, organization and technology-fit factors (HOT-fit). International Journal of Medical Informatics. 77,386-398.
- Zadeh L.A. (1965). Fuzzy Sets, Information and Control. 8, 338-352.
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Bölüm | Research Article |
| Yazarlar | |
| Yayımlanma Tarihi | 1 Nisan 2017 |
| Gönderilme Tarihi | 1 Nisan 2017 |
| Yayımlandığı Sayı | Yıl 2017 Cilt: 8 Sayı: 27 |
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