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Hastane Bilgi Yönetim Sistemi Teknolojilerinin Kabulünü Etkileyen Faktörlerin Belirlenmesi: Bir Kamu Hastanesi Örneği

Yıl 2025, Cilt: 27 Sayı: 2, 610 - 630, 18.06.2025

Serkan Demirdöğen

https://doi.org/10.32709/akusosbil.1322250

Öz

Hastane bilgi yönetimi sistemleri (HBYS) günümüzde birçok hastanede kullanılmaktadır. Bu sistemlerin kullanımının hastanelerin verimliliği ve hastaların memnuniyetini arttırması beklenmektedir. Hastalar ile ilgili bilgilerin toplanması, düzenlenmesi ve ilgili çalışanlar tarafında kullanılmasını sağlayan bu sistemler etkin bir hastane yönetimi için büyük önem taşımaktadır. Sistemlerin benimsenmesi ve kullanımında sorunların ortaya çıkmaması için kullanıcıların bilgi sistemlerinin gelişim ve değerlendirme süreçlerine katılımı büyük önem taşımaktadır. Kullanıcıların sisteme ilişkin görüşlerinin elde edilmesi, sistemlerin iyi bir şekilde gelişiminin sağlanması ve kullanıcılar tarafından kolay bir şekilde benimsenmesi açısından kritik rol oynamaktadır. Sistemlerin daha etkin kullanımına katkı sağlamayı hedefleyen bu çalışma ile HBYS teknolojilerinin sağlık çalışanları tarafından kabulünde etkili olan faktörlerin belirlenmesini amaçlamaktadır. Bu amaç doğrultusunda hazırlanan anket formu 2022 yılı Mayıs-Temmuz ayları arasında bir kamu hastanesinde çalışan hemşireler üzerinde uygulanmıştır. Araştırmanın sonuçlarına göre kişisel, teknolojik ve organizasyonel faktörlerin algılanan fayda ve algılanan kullanım kolaylığı değişkenlerini pozitif ve anlamlı bir şekilde etkilediği belirlenmiştir. Aynı zamanda çalışmada algılanan fayda ve algılanan kullanım kolaylığı değişkenlerinin teknoloji kabulünü pozitif ve anlamlı bir şekilde etkilediği tespit edilmiştir.

Anahtar Kelimeler

Hastane bilgi yönetim sistemleri teknoloji kabul modeli yapısal eşitlik modeli

Teşekkür

Katkılarınızdan dolayı teşekkür eder, saygılar sunarım.

Kaynakça

  • Aggelidis, V. P. ve Chatzoglou, P. D. (2012). Hospital information systems: measuring end user computing satisfaction (EUCS). Journal of Biomedical Informatics, 45(3), 566-579. doi:10.1016/j.jbi.2012.02.009.
  • Ahmadi, H., Nilashi, M., Shahmoradi, L., Ibrahim, O., Sadoughi, F., Alizadeh, M. ve Alizadeh, A. (2018). The moderating effect of hospital size on inter and intra-organizational factors of hospital information system adoption. Technological Forecasting and Social Change, 134, 124-149. doi:10.1016/j.techfore.2018.05.021.
  • Ahn, H. ve Park, E. (2022). Determinants of consumer acceptance of mobile healthcare devices: An application of the concepts of technology acceptance and coolness. Telematics and Informatics, 70. doi:10.1016/j.tele.2022.101810.
  • Alexandra, S., Handayani, P. W. ve Azzahro, F. (2021). Indonesian hospital telemedicine acceptance model: The influence of user behavior and technological dimensions. Heliyon, 7(12). doi:10.1016/j.heliyon.2021.e08599.
  • Alolayyan, M. N., Alyahya, M. S., Alalawin, A. H., Shoukat, A. ve Nusairat, F. T. (2020). Health information technology and hospital performance the role of health information quality in teaching hospitals. Heliyon, 6(10). doi:10.1016/j.heliyon.2020.e05040.
  • Alsalman, D., Alumran, A., Alrayes, S., Althumairi, A., Almubarak, S., Alrawiai, S. ve Alanzi, T. (2021). Implementation status of health information systems in hospitals in the eastern province of Saudi Arabia. Informatics in Medicine Unlocked, 22. doi:10.1016/j.imu. 2020.100499.
  • Barzegari, S., Ghazisaeedi, M., Askarian, F., Jesmi, A., Gandomani, H. ve Hasani, A. (2020). Hospital information system acceptance among the educational hospitals. Journal of Nursing and Midwifery Sciences, 7(3), 186. doi:10.4103/jnms.jnms_8_20.
  • Barzekar, H., Ebrahimzadeh, F., Luo, J., Karami, M., Robati, Z. ve Goodarzi, P. (2019). Adoption of hospital information system among nurses: A technology acceptance model approach. Acta Informatica Medica, 27(5), 305-310. doi:10.5455/aim.2019.27.305-310.
  • Baudier, P., Kondrateva, G., Ammi, C., Chang, V. ve Schiavone, F. (2021). Patients’ perceptions of teleconsultation during COVID-19: A cross-national study. Technological Forecasting and Social Change, 163. doi:10.1016/j.techfore.2020.120510.
  • Chen, R. F. ve Hsiao, J. L. (2012). An investigation on physicians’ acceptance of hospital information systems: A case study. International Journal of Medical Informatics, 81(12), 810-820. doi:10.1016/j.ijmedinf.2012.05.003.
  • Cimperman, M., Makovec Brenčič, M. ve Trkman, P. (2016). Analyzing older users’ home telehealth services acceptance behavior-applying an extended UTAUT model. International Journal of Medical Informatics, 90, 22-31. doi:10.1016/j.ijmedinf.2016.03.002.
  • Cohen, J. F., Coleman, E. ve Kangethe, M. J. (2016). An importance-performance analysis of hospital information system attributes a nurses’ perspective. International Journal of Medical Informatics, 86, 82-90. doi:10.1016/j.ijmedinf.2015.10.010.
  • Davis, F. D., Bagozzi, R. P. ve Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003. doi:10.1287/mnsc.35.8.982.
  • Dhagarra, D., Goswami, M. ve Kumar, G. (2020). Impact of trust and privacy concerns on technology acceptance in healthcare: An indian perspective. International Journal of Medical Informatics, 141, 104164. doi:10.1016/J.IJMEDINF.2020.104164.
  • Gholampour, A., Jamshidi, M. H. M., Habibi, A., Dehkordi, N. M. ve Ebrahimi, P. (2020). The impact of hospital information system on nurses’ satisfaction in iranian public hospitals: The moderating role of computer literacy. Journal of Information Technology Management, 12(4), 141-159. doi:10.22059/jitm.2020.299802.2491.
  • Handayani, P. W., Hidayanto, A. N., Pinem, A. A., Hapsari, I. C., Sandhyaduhita, P. I. ve Budi, I. (2017). Acceptance model of a hospital information system. International Journal of Medical Informatics, 99, 11-28. doi:10.1016/j.ijmedinf.2016.12.004.
  • Hoque, M. R. ve Bao, Y. (2015). Cultural influence on adoption and use of e-health: Evidence in Bangladesh. Telemedicine and e-Health, 21(10), 845-851. doi:10.1089/tmj.2014.0128.
  • Hu, P. J., Chau, P. Y. K., Liu Sheng, O. R. ve Tam, K. Y. (1999). Examining the Technology Acceptance Model Using Physician Acceptance of Telemedicine Technology. Source: Journal of Management Information Systems, Fall (C. 16).
  • Ismail, N. I., Abdullah, N. H. ve Shamsuddin, A. (2015). Adoption of Hospital Information System (HIS) in Malaysian Public Hospitals. Procedia - Social and Behavioral Sciences, 172, 336-343. doi:10.1016/j.sbspro.2015.01.373.
  • Kalaycı, Ş. (2006). SPSS Uygulamalı Çok Değişkenli İstatistik Teknikleri. (Ş.Kalaycı, Ed.) (2.bs.). Ankara: Asil Yayın Dağıtım Ltd. Şti.
  • Kamal, S. A., Shafiq, M. ve Kakria, P. (2020). Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM). Technology in Society, 60. doi:10.1016/j.techsoc.2019.101212.
  • Khajouei, R., Abbasi, R. ve Mirzaee, M. (2018). Errors and causes of communication failures from hospital information systems to electronic health record: A record-review study. International Journal of Medical Informatics, 119, 47-53. doi:10.1016/j.ijmedinf.2018.09. 004.
  • Kim, T. B. ve Ho, C. T. B. (2021). Validating the moderating role of age in multi-perspective acceptance model of wearable healthcare technology. Telematics and Informatics, 61. doi:10.1016/j.tele.2021.101603.
  • Kuo, K. M., Liu, C. F., Talley, P. C. ve Pan, S. Y. (2018). Strategic improvement for quality and satisfaction of hospital information systems. Journal of Healthcare Engineering, 2018. doi:10.1155/2018/3689618.
  • Kusumawati, N. I. ve Sulistyawati, S. (2018). Acceptance of Health Information System for Public Health Centre in North Borneo, Indonesia. International Journal of Public Health Science (IJPHS), 7(3), 168-174. doi:10.11591/ijphs.v7i3.14315ˆ168.
  • Kwak, Y., Seo, Y. H. ve Ahn, J.-W. (2022). Nursing students’ intent to use AI-based healthcare technology: Path analysis using the unified theory of acceptance and use of technology. Nurse Education Today, 119, 105541. doi:10.1016/j.nedt.2022.105541.
  • Liang, C., Gu, D., Tao, F., Jain, H. K., Zhao, Y. ve Ding, B. (2017). Influence of mechanism of patient-accessible hospital information system implementation on doctor – patient relationships: A service fairness perspective. Information and Management, 54(1), 57-72. doi:10.1016/j.im.2016.03.010.
  • Lim, J. S. ve Zhang, J. (2022). Adoption of AI-driven personalization in digital news platforms: An integrative model of technology acceptance and perceived contingency. Technology in Society, 69. doi:10.1016/j.techsoc.2022.101965.
  • Lin, F., Fofanah, S. S. ve Liang, D. (2011). Assessing citizen adoption of e-Government initiatives in Gambia: A validation of the technology acceptance model in information systems success. Government Information Quarterly, 28(2), 271-279. doi:10.1016/j.giq.2010.09.004.
  • Lin, H. C. (2014). An investigation of the effects of cultural differences on physicians’ perceptions of information technology acceptance as they relate to knowledge management systems. Computers in Human Behavior, 38, 368-380. doi:10.1016/J.CHB.2014.05.001.
  • Lin, Y., Luo, J., Cai, S. ve Rong, K. (2016). Exploring The Service Quality in The E-Commerce Context: A Triadic View. Industrial Management and Data Systems, 116(3), 388 - 415. Doi:10.1108/IMDS-04-2015-0116.
  • Lin, Z. (2017). The overall perception of telemedicine and ıntention to use telemedicine services: A comparison between frequent travelers and non frequent travelers (Yayımlanmamış yüksek lisans tezi). Faculty of the Graduate School of Cornell University.
  • Liu, J., Luo, X., Liu, X., Li, N., Xing, M., Gao, Y. ve Liu, Y. (2022). Rural residents’ acceptance of clean heating: An extended technology acceptance model considering rural residents’ livelihood capital and perception of clean heating. Energy and Buildings, 267. doi: 10.1016/j.enbuild.2022.112154.
  • Luyten, J. ve Marneffe, W. (2021). Examining the acceptance of an integrated Electronic Health Records system: Insights from a repeated cross-sectional design. International Journal of Medical Informatics, 150. doi:10.1016/j.ijmedinf.2021.104450.
  • Ly, B. ve Ly, R. (2022). Internet banking adoption under Technology Acceptance Model Evidence from Cambodian users. Computers in Human Behavior Reports, 7. doi:10.1016/j. chbr.2022.100224.
  • Markazi-Moghaddam, N., Kazemi, A. ve Alimoradnori, M. (2019). Using the importance-performance analysis to improve hospital information system attributes based on nurses’ perceptions. Informatics in Medicine Unlocked, 17. doi:10.1016/j.imu.2019.100251.
  • Melas, C. D., Zampetakis, L. A., Dimopoulou, A. ve Moustakis, V. (2011). Modeling the acceptance of clinical information systems among hospital medical staff: An extended TAM model. Journal of Biomedical Informatics, 44(4), 553-564. doi:10.1016/j.jbi.2011.01.009.
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Determining the Factors Affecting the Adoption of Hospital Information Management System Technologies: A Public Hospital Example

Yıl 2025, Cilt: 27 Sayı: 2, 610 - 630, 18.06.2025

Serkan Demirdöğen

https://doi.org/10.32709/akusosbil.1322250

Öz

Hospital information management systems (HIMS) are used in many hospitals today. The use of these systems is expected to increase the efficiency of hospitals and the satisfaction of patients. These systems, which enable the collection, organization and use of information about patients, are of great importance for an effective hospital management. It is of great importance that users participate in the development and evaluation processes of information systems so that problems do not arise in the adoption and use of systems. Obtaining users' views on the system plays a critical role in ensuring good development of the systems and easy adoption by users. Aiming to contribute to the more effective use of systems, this study aims to determine the factors that affect the acceptance of HIMS technologies by healthcare professionals. The questionnaire form prepared for this purpose was applied to nurses working in a public hospital between May and July 2022. According to the results of the research, it was determined that personal, technological and organizational factors positively and significantly affect the variables of perceived usefulness and perceived ease of use. At the same time, it was determined that the variables of perceived usefulness and perceived ease of use affect technology acceptance positively and significantly.

Anahtar Kelimeler

Hospital information management systems technology acceptance model structural equation model

Kaynakça

  • Aggelidis, V. P. ve Chatzoglou, P. D. (2012). Hospital information systems: measuring end user computing satisfaction (EUCS). Journal of Biomedical Informatics, 45(3), 566-579. doi:10.1016/j.jbi.2012.02.009.
  • Ahmadi, H., Nilashi, M., Shahmoradi, L., Ibrahim, O., Sadoughi, F., Alizadeh, M. ve Alizadeh, A. (2018). The moderating effect of hospital size on inter and intra-organizational factors of hospital information system adoption. Technological Forecasting and Social Change, 134, 124-149. doi:10.1016/j.techfore.2018.05.021.
  • Ahn, H. ve Park, E. (2022). Determinants of consumer acceptance of mobile healthcare devices: An application of the concepts of technology acceptance and coolness. Telematics and Informatics, 70. doi:10.1016/j.tele.2022.101810.
  • Alexandra, S., Handayani, P. W. ve Azzahro, F. (2021). Indonesian hospital telemedicine acceptance model: The influence of user behavior and technological dimensions. Heliyon, 7(12). doi:10.1016/j.heliyon.2021.e08599.
  • Alolayyan, M. N., Alyahya, M. S., Alalawin, A. H., Shoukat, A. ve Nusairat, F. T. (2020). Health information technology and hospital performance the role of health information quality in teaching hospitals. Heliyon, 6(10). doi:10.1016/j.heliyon.2020.e05040.
  • Alsalman, D., Alumran, A., Alrayes, S., Althumairi, A., Almubarak, S., Alrawiai, S. ve Alanzi, T. (2021). Implementation status of health information systems in hospitals in the eastern province of Saudi Arabia. Informatics in Medicine Unlocked, 22. doi:10.1016/j.imu. 2020.100499.
  • Barzegari, S., Ghazisaeedi, M., Askarian, F., Jesmi, A., Gandomani, H. ve Hasani, A. (2020). Hospital information system acceptance among the educational hospitals. Journal of Nursing and Midwifery Sciences, 7(3), 186. doi:10.4103/jnms.jnms_8_20.
  • Barzekar, H., Ebrahimzadeh, F., Luo, J., Karami, M., Robati, Z. ve Goodarzi, P. (2019). Adoption of hospital information system among nurses: A technology acceptance model approach. Acta Informatica Medica, 27(5), 305-310. doi:10.5455/aim.2019.27.305-310.
  • Baudier, P., Kondrateva, G., Ammi, C., Chang, V. ve Schiavone, F. (2021). Patients’ perceptions of teleconsultation during COVID-19: A cross-national study. Technological Forecasting and Social Change, 163. doi:10.1016/j.techfore.2020.120510.
  • Chen, R. F. ve Hsiao, J. L. (2012). An investigation on physicians’ acceptance of hospital information systems: A case study. International Journal of Medical Informatics, 81(12), 810-820. doi:10.1016/j.ijmedinf.2012.05.003.
  • Cimperman, M., Makovec Brenčič, M. ve Trkman, P. (2016). Analyzing older users’ home telehealth services acceptance behavior-applying an extended UTAUT model. International Journal of Medical Informatics, 90, 22-31. doi:10.1016/j.ijmedinf.2016.03.002.
  • Cohen, J. F., Coleman, E. ve Kangethe, M. J. (2016). An importance-performance analysis of hospital information system attributes a nurses’ perspective. International Journal of Medical Informatics, 86, 82-90. doi:10.1016/j.ijmedinf.2015.10.010.
  • Davis, F. D., Bagozzi, R. P. ve Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003. doi:10.1287/mnsc.35.8.982.
  • Dhagarra, D., Goswami, M. ve Kumar, G. (2020). Impact of trust and privacy concerns on technology acceptance in healthcare: An indian perspective. International Journal of Medical Informatics, 141, 104164. doi:10.1016/J.IJMEDINF.2020.104164.
  • Gholampour, A., Jamshidi, M. H. M., Habibi, A., Dehkordi, N. M. ve Ebrahimi, P. (2020). The impact of hospital information system on nurses’ satisfaction in iranian public hospitals: The moderating role of computer literacy. Journal of Information Technology Management, 12(4), 141-159. doi:10.22059/jitm.2020.299802.2491.
  • Handayani, P. W., Hidayanto, A. N., Pinem, A. A., Hapsari, I. C., Sandhyaduhita, P. I. ve Budi, I. (2017). Acceptance model of a hospital information system. International Journal of Medical Informatics, 99, 11-28. doi:10.1016/j.ijmedinf.2016.12.004.
  • Hoque, M. R. ve Bao, Y. (2015). Cultural influence on adoption and use of e-health: Evidence in Bangladesh. Telemedicine and e-Health, 21(10), 845-851. doi:10.1089/tmj.2014.0128.
  • Hu, P. J., Chau, P. Y. K., Liu Sheng, O. R. ve Tam, K. Y. (1999). Examining the Technology Acceptance Model Using Physician Acceptance of Telemedicine Technology. Source: Journal of Management Information Systems, Fall (C. 16).
  • Ismail, N. I., Abdullah, N. H. ve Shamsuddin, A. (2015). Adoption of Hospital Information System (HIS) in Malaysian Public Hospitals. Procedia - Social and Behavioral Sciences, 172, 336-343. doi:10.1016/j.sbspro.2015.01.373.
  • Kalaycı, Ş. (2006). SPSS Uygulamalı Çok Değişkenli İstatistik Teknikleri. (Ş.Kalaycı, Ed.) (2.bs.). Ankara: Asil Yayın Dağıtım Ltd. Şti.
  • Kamal, S. A., Shafiq, M. ve Kakria, P. (2020). Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM). Technology in Society, 60. doi:10.1016/j.techsoc.2019.101212.
  • Khajouei, R., Abbasi, R. ve Mirzaee, M. (2018). Errors and causes of communication failures from hospital information systems to electronic health record: A record-review study. International Journal of Medical Informatics, 119, 47-53. doi:10.1016/j.ijmedinf.2018.09. 004.
  • Kim, T. B. ve Ho, C. T. B. (2021). Validating the moderating role of age in multi-perspective acceptance model of wearable healthcare technology. Telematics and Informatics, 61. doi:10.1016/j.tele.2021.101603.
  • Kuo, K. M., Liu, C. F., Talley, P. C. ve Pan, S. Y. (2018). Strategic improvement for quality and satisfaction of hospital information systems. Journal of Healthcare Engineering, 2018. doi:10.1155/2018/3689618.
  • Kusumawati, N. I. ve Sulistyawati, S. (2018). Acceptance of Health Information System for Public Health Centre in North Borneo, Indonesia. International Journal of Public Health Science (IJPHS), 7(3), 168-174. doi:10.11591/ijphs.v7i3.14315ˆ168.
  • Kwak, Y., Seo, Y. H. ve Ahn, J.-W. (2022). Nursing students’ intent to use AI-based healthcare technology: Path analysis using the unified theory of acceptance and use of technology. Nurse Education Today, 119, 105541. doi:10.1016/j.nedt.2022.105541.
  • Liang, C., Gu, D., Tao, F., Jain, H. K., Zhao, Y. ve Ding, B. (2017). Influence of mechanism of patient-accessible hospital information system implementation on doctor – patient relationships: A service fairness perspective. Information and Management, 54(1), 57-72. doi:10.1016/j.im.2016.03.010.
  • Lim, J. S. ve Zhang, J. (2022). Adoption of AI-driven personalization in digital news platforms: An integrative model of technology acceptance and perceived contingency. Technology in Society, 69. doi:10.1016/j.techsoc.2022.101965.
  • Lin, F., Fofanah, S. S. ve Liang, D. (2011). Assessing citizen adoption of e-Government initiatives in Gambia: A validation of the technology acceptance model in information systems success. Government Information Quarterly, 28(2), 271-279. doi:10.1016/j.giq.2010.09.004.
  • Lin, H. C. (2014). An investigation of the effects of cultural differences on physicians’ perceptions of information technology acceptance as they relate to knowledge management systems. Computers in Human Behavior, 38, 368-380. doi:10.1016/J.CHB.2014.05.001.
  • Lin, Y., Luo, J., Cai, S. ve Rong, K. (2016). Exploring The Service Quality in The E-Commerce Context: A Triadic View. Industrial Management and Data Systems, 116(3), 388 - 415. Doi:10.1108/IMDS-04-2015-0116.
  • Lin, Z. (2017). The overall perception of telemedicine and ıntention to use telemedicine services: A comparison between frequent travelers and non frequent travelers (Yayımlanmamış yüksek lisans tezi). Faculty of the Graduate School of Cornell University.
  • Liu, J., Luo, X., Liu, X., Li, N., Xing, M., Gao, Y. ve Liu, Y. (2022). Rural residents’ acceptance of clean heating: An extended technology acceptance model considering rural residents’ livelihood capital and perception of clean heating. Energy and Buildings, 267. doi: 10.1016/j.enbuild.2022.112154.
  • Luyten, J. ve Marneffe, W. (2021). Examining the acceptance of an integrated Electronic Health Records system: Insights from a repeated cross-sectional design. International Journal of Medical Informatics, 150. doi:10.1016/j.ijmedinf.2021.104450.
  • Ly, B. ve Ly, R. (2022). Internet banking adoption under Technology Acceptance Model Evidence from Cambodian users. Computers in Human Behavior Reports, 7. doi:10.1016/j. chbr.2022.100224.
  • Markazi-Moghaddam, N., Kazemi, A. ve Alimoradnori, M. (2019). Using the importance-performance analysis to improve hospital information system attributes based on nurses’ perceptions. Informatics in Medicine Unlocked, 17. doi:10.1016/j.imu.2019.100251.
  • Melas, C. D., Zampetakis, L. A., Dimopoulou, A. ve Moustakis, V. (2011). Modeling the acceptance of clinical information systems among hospital medical staff: An extended TAM model. Journal of Biomedical Informatics, 44(4), 553-564. doi:10.1016/j.jbi.2011.01.009.
  • Nilashi, M., Ahmadi, H., Ahani, A., Ravangard, R. ve Ibrahim, O. bin. (2016). Determining the importance of Hospital Information System adoption factors using Fuzzy Analytic Network Process (ANP). Technological Forecasting and Social Change, 111, 244 - 264. doi:10.1016/ j.techfore.2016.07.008.
  • Ong, A. K. S., Kurata, Y. B., Castro, S. A. D. G., de Leon, J. P. B., dela Rosa, H. v. ve Tomines, A. P. J. (2022). Factors influencing the acceptance of telemedicine in the Philippines. Technology in Society, 70, 102040. doi:10.1016/J.TECHSOC.2022.102040.
  • Pai, F. Y. ve Huang, K. I. (2011). Applying the Technology Acceptance Model to the introduction of healthcare information systems. Technological Forecasting and Social Change, 78(4), 650 - 660. doi:10.1016/j.techfore.2010.11.007.
  • Prasanna, R. ve Huggins, T. J. (2016). Factors affecting the acceptance of information systems supporting emergency operations centres. Computers in Human Behavior, 57, 168-181. doi: 10.1016/j.chb.2015.12.013.
  • Rajak, M. ve Shaw, K. (2021). An extension of technology acceptance model for Health user adoption. Technology in Society, 67, 101800. doi:10.1016/J.TECHSOC.2021.101800.
  • Rho, M. J., Choi, I. young ve Lee, J. (2014). Predictive factors of telemedicine service acceptance and behavioral intention of physicians. International Journal of Medical Informatics, 83(8), 559-571. doi:10.1016/j.ijmedinf.2014.05.005.
  • Rochmah, T. N., Fakhruzzaman, M. N. ve Yustiawan, T. (2020). Hospital staff acceptance toward management information systems in Indonesia. Health Policy and Technology, 9(3), 268-270. doi:10.1016/J.HLPT.2020.07.004.
  • Shanmugavel, N., Alagappan, C. ve Balakrishnan, J. (2022). Acceptance of electric vehicles: A dual-factor approach using social comparison theory and technology acceptance model. Research in Transportation Business and Management. doi:10.1016/j.rtbm.2022.100842.
  • Shanmugavel, N. ve Micheal, M. (2022). Exploring the marketing related stimuli and personal innovativeness on the purchase intention of electric vehicles through Technology Acceptance Model. Cleaner Logistics and Supply Chain, 3. doi:10.1016/j.clscn.2022.100029.
  • Taheri, F., D’Haese, M., Fiems, D. ve Azadi, H. (2022). The intentions of agricultural professionals towards diffusing wireless sensor networks: Application of technology acceptance model in Southwest Iran. Technological Forecasting and Social Change, 185, 122075. doi:10.1016/j.techfore.2022.122075.
  • Talukder, M. S., Sorwar, G., Bao, Y., Ahmed, J. U. ve Palash, M. A. S. (2020). Predicting antecedents of wearable healthcare technology acceptance by elderly: A combined SEM-Neural Network approach. Technological Forecasting and Social Change, 150. doi:10.1016/ J.Techfore.2019.119793.
  • Wang, H., Tao, D., Yu, N. ve Qu, X. (2020). Understanding consumer acceptance of healthcare wearable devices: An integrated model of UTAUT and TTF. International Journal of Medical Informatics, 139. doi:10.1016/J.IJMEDINF.2020.104156.
  • Wang, N., Tian, H., Zhu, S. ve Li, Y. (2022). Analysis of public acceptance of electric vehicle charging scheduling based on the technology acceptance model. Energy, 258. doi:10.1016/j. energy.2022.124804.
  • Wu, W., Wu, Y. J. ve Wang, H. (2021). Perceived city smartness level and technical information transparency: The acceptance intention of health information technology during a lockdown. Computers in Human Behavior, 122. doi:10.1016/j.chb.2021.106840.
  • Yang, H., Guo, X., Peng, Z. ve Lai, K. H. (2021). The antecedents of effective use of hospital information systems in the chinese context: A mixed-method approach. Information Processing and Management, 58(2). doi:10.1016/j.ipm.2020.102461.
  • Zhou, M., Zhao, L., Kong, N., Campy, K. S., Qu, S. ve Wang, S. (2019). Factors influencing behavior intentions to telehealth by Chinese elderly: An extended TAM model. International Journal of Medical Informatics, 126, 118-127. doi:10.1016/j.ijmedinf.2019.04.001.
Toplam 53 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Bilgi Sistemleri Geliştirme Metodolojileri ve Uygulamaları, Bilgi Sistemleri Kullanıcı Deneyimi Tasarımı ve Geliştirme, Bilgi Sistemleri Organizasyonu ve Yönetimi
Bölüm İktisadi ve İdari Bilimler
Yazarlar

Serkan Demirdöğen 0000-0001-9134-7154

Yayımlanma Tarihi 18 Haziran 2025
Gönderilme Tarihi 3 Temmuz 2023
Yayımlandığı Sayı Yıl 2025 Cilt: 27 Sayı: 2

Kaynak Göster

APA Demirdöğen, S. (2025). Hastane Bilgi Yönetim Sistemi Teknolojilerinin Kabulünü Etkileyen Faktörlerin Belirlenmesi: Bir Kamu Hastanesi Örneği. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 27(2), 610-630. https://doi.org/10.32709/akusosbil.1322250
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