Abstract
Abstract. Competition comes into prominence in health field as it is in all the fields in the world and in Turkey. The companies pursue the recently established information systems and market fit closely in order to increase the competitive power. Turkey is experiencing quite radical transformations in health-care sector during the last 10 years. In this sense, the objective of the study is to determine the usage level of Central Physician Appointment System (CPAS) within the scope of technology acceptance model. When the context of the model is examined, the degree of turning the positive perceptions such as benefits, convenience that the customers perceive from this technology when they came face to face with this technology, to attitudes and behaviors is measured. As a result of the research, the electronic appointment system, which has started to be applied within the health-care sector, was considered positively on the basis of benefits and convenience and in parallel with this the their attitudes behaviors were affected positively.
Keywords. Patient Satisfaction, Central Physician Appointment System,Technology Acceptance Model, Information Systems.
JEL. C38, I18, L88.
References
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour. Englewood Cliffs, NJ: Prentice-Hall.
Ak, B. (2009). Türkiye’de sağlık bilişimi, bir kişisel değerlendirme ve uluslararası bir başarı öyküsü: CorTTex. Akademik Bilişim’09-XI. Akademik Bilişim Konferansı Bildirileri, (pp.11-13).
Altunışık, R.C.R., Bayraktaroğlu, S., & Yıldırım, E.(2005). Sosyal bilimlerde araştırma yöntemleri: SPSS uygulamalı. Sakarya: Sakarya Kitabevi
Armstrong, J.S., & Overton, T. (1971). Brief vs. comprehensive descriptions in measuring intentions to purchase. Journal of Marketing Research, 8(1), 114-117. doi. 10.2307/3149740
Bertrand, M., & Bouchard, S. (2008). Applying the technology acceptance model to VR with people who are favorable to its use. Journal of Cyber Therapy & Rehabilitation, 1(2). 200-210.
Chen, L., Gillenson, L., & Sherrell, L. (2002). Enticing online consumers: an extended technology acceptance perspective, Information & Management, 39(8), 709–719. doi. 10.1016/S0378-7206(01)00127-6
Compeau, D., Higgins C.A., & Huff S. (1999). Social Cognitive Theory and Individual Reactions to Computing Technology: A Longitudinal Study. Management Information Systems Quarterly, 23(2), 145-158. doi. 10.2307/249749
Davis, F.D., Bagozzi R.P., & Warshaw P.R. (1989). User acceptance of computer technology: a comparison of 2 theoretical models. Management Science, 35(8), 982–1003. doi. 10.1287/mnsc.35.8.982
Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. Management Information Systems Quarterly, 13(3), 319–39. doi. 10.2307/249008
Duyck, P., Pynoo, B., Devolder, P., Voet, T., Adang, L., & Vercruysse, J. (2008). User acceptance of a picture archiving and communication system. Applying the unified theory of acceptance and use of technology in a radiological setting. Methods of Information Medicine, 47(2), 149–56. doi. http://dx.doi.org/10.3414/ME0477
Gentry, L., & Calantone, R. (2002). A comparison of three models to explain shop‐bot use on the web. Psychology & Marketing, 19(11), 945-956. doi. 10.1002/mar.10045
Gibson, S.G., & Seeman E.D. (2005). Predicting Acceptance of Electronic Medical Records: What Factors Matter Most? Proceedings of the 2009 Southeast Decision Sciences Institute Conference (pp. 18-20).
Han, S., Mustonen, P., Seppänen, M., & Kallio, M. (2005). Does fragmenting of working time and working space influence the acceptance of mobile technology? A case of Finnish physicians. Finland: Turku Centre for Computer Science.
Handy, J., Hunter, I., & Whiddett, R. (2001). User acceptance of interorganizational electronic medical records. Australasian Journal of Information Systems, 7(2), 103–107. doi. 10.1177/146045820100700208
Harris, M.F., Priddin, D., Ruscoe, W., Infante, F.A., & O'Toole, B.I. (2002). Quality of care provided by general practitioners using or not using Division-based diabetes registers. The Medical journal of Australia, 177(5), 250-252.
Kline, R.B. (1998). Principles and practice of structural equation modeling. UK: The Guilford Press.
Kuperman, G.J., Spurr, C., Flammini, S., Bates, D., & Glaser, J. (2000). A clinical information systems strategy for a large integrated delivery network. In Proceedings of the AMIA Symposium (p. 438). American Medical Informatics Association.
Lederer, A.L., Maupin, D.J., Sena, M.P., & Zhuang, Y. (2000). The technology acceptance model and the world wild web. Decision Support Systems, 29(3), 269-282. doi. 10.1016/S0167-9236(00)00076-2
Liu, L., & Ma, Q. (2006). Perceived system performance: a test of an extended technology acceptance model. ACM SIGMIS Database, 37(2-3), 51-59. doi. 10.1145/1161345.1161354
Özkan, A. (2003). Hastane İşletmelerinde Maliyetleme Yaklaşımları. Uludağ Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 22(2), 113-130.
Schepers, J., & Wetzels, M. (2007). A meta-analysis of the technology acceptance model: investigating subjective norm and moderation effects. Information & Management, 44(1), 90-103. doi. 10.1016/j.im.2006.10.007
Tan, J.K., & Hanna, J. (1994). Integrating health care with information technology: Knitting patient information through networking. Health Care Management Review, 19(2), 72-80.
Tung, F-C., & Chang S-C. (2008). Nursing students’ behavioral intention to use online courses: a questionnaire survey. International Journal of Nursing Studies, 45(9), 1299–1309. doi. 10.1016/j.ijnurstu.2007.09.011
Van Schaik, P., & Bettany-Saltikov, J.A.B., Warren, J.G. (2002). Clinical acceptance of a low cost portable system for postural assessment. Behavior & Information Technology, 21(1), 47–57. doi. 10.1080/01449290110107236
Venkatesh, V, & Davis, F.D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Sciences, 46(2), 186–204. doi. 10.1287/mnsc.46.2.186.11926
Wu, J-H., Shen W-S., Lin L-M., Greenes R.A., & Bates D.W. (2008). Testing the technology acceptance model for evaluating healthcare professionals’ intention to use an adverse event reporting system. International Journal for Quality in Health Care, 20(2), 123–9. doi. 10.1093/intqhc/mzm074
Yazıcıoğlu, Y., & Erdoğan, S. (2004). Spss uygulamalı bilimsel araştırma yöntemleri. Ankara: Detay Yayıncılık.
