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Evaluation of Acceptance of Hospital Information Management System Among Nurses Through Technology Acceptance Model

Yıl 2024, Cilt: 8 Sayı: 2, 99 - 118, 06.01.2025
https://doi.org/10.52148/ehta.1520164

Öz

Hospital Information Management System (HIMS) has widely been used by healthcare professionals, especially nurses working in hospitals. The aim of this study is to evaluate the factors affecting the adoption of HIMS. The external factors included in this conceptual model were taken from the Information System Success Model (ISSM) and incorporated into updated Technology Acceptance Model (TAM). A total of 401 nurses from public and private hospitals in Türkiye participated in this cross-sectional study. Statistical Package for the Social Sciences (SPSS) 25software package was used for data analysis. In this study, descriptive statistics, correlation and path analysis and structure equation modeling using AMOS were used. Among all the external factors included in this study model, only system quality was found to have a positive and significant effect on perceived ease of use and perceived usefulness. Service quality has a positive and significant effect only on perceived usefulness, while information quality does not have any positive and significant effect on perceived ease of use and perceived usefulness. Perceived ease of use and perceived usefulness have a positive and significant effect on usage intention. Perceived ease of use has a positive and significant effect on perceived usefulness. This research model helped identify the factors that influence hospital information management system acceptance among nurses and how these factors can be improved to influence users' intention to use in the future. In conclusion, there is always room for improvement regarding HIMS to improve patient care.

Etik Beyan

The ethics of the study was approved by the Toros University Scientific Research and Publication Ethics Committee on 26.04.2023 with the decree no 54.

Destekleyen Kurum

None

Kaynakça

  • Adams, D. A., Nelson, R. R., & Todd, P. A. (1992). Perceived usefulness, ease of use, and usage of information technology: a replication. MIS Q 16:227–47.
  • Aggarwal, L.M. (2017). Advances in medical technology and its impact on health care in developing countries. Int J Radiol Radiat Ther., 2 (2):55‒56.
  • Ali, B., & Younes, B. (2013). The impact of information systems on user performance: exploratory study. Journal of Knowledge Management, Economics and Information Technology. ScientificPapers.org, vol. 3(2), pages 1-10, April. https://ideas.repec.org/a/spp/jkmeit/1369.html, Access Date July 19, 2024.
  • Alnawafleh, E.A.T., Tambi, A.M.A., Abdullah, A.A., Alsheikh, G.A.A., & Ghazali, P.L. (2018). The impact of service quality, subjective norms, and voluntariness on acceptance of provider’s mobile telecommunication service in Jordan. International Journal of Engineering & Technology 7 (4.34): 149-152.
  • Al-Otaibi, J., Tolma, E., Alali, W., Alhuwail, D., & Aljunid, S.M. (2022). The Factors contributing to physicians’ current use of and satisfaction with electronic health records in Kuwait’s public healthcare: Cross-sectional Questionnaire Study. JMIR Med. Inform. 10, e36313.
  • Alquraini, H., Alhashem, A.M., Shah, M.A., & Chowdhury, R.I. (2007). Factors influencing nurses’ attitudes towards the use of computerized health information systems in Kuwaiti hospitals. Journal of Advanced Nursing, 57(4), 375Y381.
  • Alsyouf, A., Masa’Deh, R., Albugami, M., Al-Bsheish, M., Lutfi, A., & Alsubahi, N. (2021). Risk of fear and anxiety in utilising health app surveillance due to COVID-19: Gender Differences Analysis. Risks, 9, 179.
  • Alsyouf, A., Lutfi, A., Al-Bsheish, M., Jarrar, M. T., Al-Mugheed, K., & Almaiah, M. A. et al. (2022). A. Exposure detection application.s acceptance: The case of COVID-19. Int.
  • Ballantine, J., Bonner, M., Levy, M., Martin, A., Munro, I., & Powell, P. (1996). The 3-D model of information systems success: The search for the dependent variable continues. Information Resource Management Journal, 9(4), 5–14
  • Barchielli, C., Marullo, Bonciani, M., & Vainieri, M. (2021). Nurses and the acceptance of innovations in technology-intensive contexts: the need for tailored management strategies J. BMC Health Services Research 21:639
  • Barzekar, H., Ebrahimzadeh, F., Luo, J., Karami, M., Zahra Robati, Z., & Goodarzi, P. (2019). Adoption of hospital information system among nurses: a technology acceptance model approach. Acta Inform (5): 305-310.
  • Bentler, P.M. (1990). Comparative fit indexes in structural model. Psychological Bulletin, 107, 2: 238-246.
  • Chang, S.S., Lou, S.J., Cheng, S.R., & Lin, C.L. (2015). Exploration of usage behavioral model construction for university library electronic resources’, The Electronic Library, (33) 2: 292–307.
  • Chayomchai, A., Phonsari, W., Jungit, A., Boongapim, R., & Suwannapusit, R. (2020). Factors affecting acceptance and use of online technology in Thai people during Covid-19 quarantine time, Management Science Letters 10: 3009-3016.
  • Chen, F., Curran, P.J., Bollen, K.A., Kirby, J., & Paxton, P. (2008). An empirical evaluation of the use of fixed cutoff points in RMSEA test statistic in structural equation models. Sociological Methods & Research, 36(4), 462-494.
  • Cheng, Y.M. (2012). Effects of quality antecedents on e-learning acceptance. Internet Research 22(3), 361–390.
  • Chimento-Díaz, S., Sánchez-García, P., Franco-Antonio, C., Santano-Mogena, E., Espino-Tato, I., & Cordovilla-Guardia, S. (2022). Factors associated with the acceptance of new technologies for ageing in place by people over 64 years of Age. Int. J. Environ. Res. Public Health,19, 2947.
  • Chuttur M. (2009). Working Papers on Information Systems. Overview of the technology acceptance model: Origins, developments, and future directions URL: https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1289&context=sprouts_all (Access Date January 05. 2024).
  • Collins, A.S. (2008). Preventing Health Care–Associated Infections. In: Hughes RG, editor. Patient Safety and Quality: an evidence‑based handbook for nurses. Rockville (MD): Agency for Healthcare Research and Quality (US). http://www.ncbi.nlm.nih.gov/books/ NBK268., Access Date July 20, 2024.
  • Davis, F.D. (1985). A Technology Acceptance Model for Empirically Testing New End-User Information Systems: Theory and Results. Massachusetts Institute of Technology. http://hdl.handle.net/1721.1/15192., Access Date January 20, 2024.
  • Davis, F.D., Bagozzi, R.P., & Warshaw, P.R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35, 982-1003.
  • Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q.13(3): 319–34.
  • DeLone, W.H., & McLean, E.R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1): 60-95.
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Teknoloji Kabul Modeli Aracılığıyla Hemşireler Arasında Hastane Bilgi Yönetim Sisteminin Kabulünün Değerlendirilmesi

Yıl 2024, Cilt: 8 Sayı: 2, 99 - 118, 06.01.2025
https://doi.org/10.52148/ehta.1520164

Öz

Hastane Bilgi Yönetim Sistemi (HBYS), özellikle hastanelerde çalışan hemşireler tarafından yaygın olarak kullanılmaktadır. Bu çalışmanın amacı, HBYS'nin benimsenmesini etkileyen faktörleri değerlendirmektir. Bu kavramsal modelde yer alan dışsal faktörler, Bilgi Sistemleri Başarı Modeli'nden (ISSM) alınmış ve güncellenmiş Teknoloji Kabul Modeli'ne (TAM) entegre edilmiştir. Türkiye’deki kamu ve özel hastanelerden toplam 401 hemşire bu kesitsel çalışmaya katılmıştır. Veri analizi için İstatistiksel Paket Sosyal Bilimler (SPSS) 25 yazılımı kullanılmıştır. Çalışmada tanımlayıcı istatistikler, korelasyon ve yol analizi ile AMOS kullanılarak yapısal eşitlik modellemesi uygulanmıştır. Bu çalışmada incelenen modeldeki tüm dışsal faktörler arasında yalnızca sistem kalitesinin algılanan kullanım kolaylığı ve algılanan fayda üzerinde pozitif ve anlamlı bir etkisi belirlenmiştir. Hizmet kalitesinin yalnızca algılanan fayda üzerinde pozitif ve anlamlı bir etkisi varken, bilgi kalitesinin algılanan kullanım kolaylığı ve algılanan fayda üzerinde pozitif ve anlamlı bir etkisi belirlenememiştir. Algılanan kullanım kolaylığı ve algılanan fayda, kullanım niyeti üzerinde pozitif ve anlamlı bir etkiye sahiptir. Ayrıca, algılanan kullanım kolaylığının algılanan fayda üzerinde pozitif ve anlamlı bir etkisi olduğu tespit edilmiştir. Bu araştırma modeli, hemşireler arasında hastane bilgi yönetim sisteminin kabulünü etkileyen faktörleri ve bu faktörlerin kullanıcıların gelecekteki kullanım niyetlerini nasıl etkileyebileceğini belirlemeye yardımcı olmuştur. Sonuç olarak, HBYS'nin hasta bakımını iyileştirmek için sürekli geliştirilmesine yönelik alanlar bulunmaktadır.

Etik Beyan

Çalışmanın etiği Toros Üniversitesi Bilimsel Araştırma ve Yayın Etiği Kurulu tarafından 26.04.2023 tarih ve 54 sayılı kararla onaylandı.

Destekleyen Kurum

Yoktur.

Kaynakça

  • Adams, D. A., Nelson, R. R., & Todd, P. A. (1992). Perceived usefulness, ease of use, and usage of information technology: a replication. MIS Q 16:227–47.
  • Aggarwal, L.M. (2017). Advances in medical technology and its impact on health care in developing countries. Int J Radiol Radiat Ther., 2 (2):55‒56.
  • Ali, B., & Younes, B. (2013). The impact of information systems on user performance: exploratory study. Journal of Knowledge Management, Economics and Information Technology. ScientificPapers.org, vol. 3(2), pages 1-10, April. https://ideas.repec.org/a/spp/jkmeit/1369.html, Access Date July 19, 2024.
  • Alnawafleh, E.A.T., Tambi, A.M.A., Abdullah, A.A., Alsheikh, G.A.A., & Ghazali, P.L. (2018). The impact of service quality, subjective norms, and voluntariness on acceptance of provider’s mobile telecommunication service in Jordan. International Journal of Engineering & Technology 7 (4.34): 149-152.
  • Al-Otaibi, J., Tolma, E., Alali, W., Alhuwail, D., & Aljunid, S.M. (2022). The Factors contributing to physicians’ current use of and satisfaction with electronic health records in Kuwait’s public healthcare: Cross-sectional Questionnaire Study. JMIR Med. Inform. 10, e36313.
  • Alquraini, H., Alhashem, A.M., Shah, M.A., & Chowdhury, R.I. (2007). Factors influencing nurses’ attitudes towards the use of computerized health information systems in Kuwaiti hospitals. Journal of Advanced Nursing, 57(4), 375Y381.
  • Alsyouf, A., Masa’Deh, R., Albugami, M., Al-Bsheish, M., Lutfi, A., & Alsubahi, N. (2021). Risk of fear and anxiety in utilising health app surveillance due to COVID-19: Gender Differences Analysis. Risks, 9, 179.
  • Alsyouf, A., Lutfi, A., Al-Bsheish, M., Jarrar, M. T., Al-Mugheed, K., & Almaiah, M. A. et al. (2022). A. Exposure detection application.s acceptance: The case of COVID-19. Int.
  • Ballantine, J., Bonner, M., Levy, M., Martin, A., Munro, I., & Powell, P. (1996). The 3-D model of information systems success: The search for the dependent variable continues. Information Resource Management Journal, 9(4), 5–14
  • Barchielli, C., Marullo, Bonciani, M., & Vainieri, M. (2021). Nurses and the acceptance of innovations in technology-intensive contexts: the need for tailored management strategies J. BMC Health Services Research 21:639
  • Barzekar, H., Ebrahimzadeh, F., Luo, J., Karami, M., Zahra Robati, Z., & Goodarzi, P. (2019). Adoption of hospital information system among nurses: a technology acceptance model approach. Acta Inform (5): 305-310.
  • Bentler, P.M. (1990). Comparative fit indexes in structural model. Psychological Bulletin, 107, 2: 238-246.
  • Chang, S.S., Lou, S.J., Cheng, S.R., & Lin, C.L. (2015). Exploration of usage behavioral model construction for university library electronic resources’, The Electronic Library, (33) 2: 292–307.
  • Chayomchai, A., Phonsari, W., Jungit, A., Boongapim, R., & Suwannapusit, R. (2020). Factors affecting acceptance and use of online technology in Thai people during Covid-19 quarantine time, Management Science Letters 10: 3009-3016.
  • Chen, F., Curran, P.J., Bollen, K.A., Kirby, J., & Paxton, P. (2008). An empirical evaluation of the use of fixed cutoff points in RMSEA test statistic in structural equation models. Sociological Methods & Research, 36(4), 462-494.
  • Cheng, Y.M. (2012). Effects of quality antecedents on e-learning acceptance. Internet Research 22(3), 361–390.
  • Chimento-Díaz, S., Sánchez-García, P., Franco-Antonio, C., Santano-Mogena, E., Espino-Tato, I., & Cordovilla-Guardia, S. (2022). Factors associated with the acceptance of new technologies for ageing in place by people over 64 years of Age. Int. J. Environ. Res. Public Health,19, 2947.
  • Chuttur M. (2009). Working Papers on Information Systems. Overview of the technology acceptance model: Origins, developments, and future directions URL: https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1289&context=sprouts_all (Access Date January 05. 2024).
  • Collins, A.S. (2008). Preventing Health Care–Associated Infections. In: Hughes RG, editor. Patient Safety and Quality: an evidence‑based handbook for nurses. Rockville (MD): Agency for Healthcare Research and Quality (US). http://www.ncbi.nlm.nih.gov/books/ NBK268., Access Date July 20, 2024.
  • Davis, F.D. (1985). A Technology Acceptance Model for Empirically Testing New End-User Information Systems: Theory and Results. Massachusetts Institute of Technology. http://hdl.handle.net/1721.1/15192., Access Date January 20, 2024.
  • Davis, F.D., Bagozzi, R.P., & Warshaw, P.R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35, 982-1003.
  • Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q.13(3): 319–34.
  • DeLone, W.H., & McLean, E.R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1): 60-95.
  • Delone, W.H., & McLean, E.R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19 (4): 9-30.
  • Fishbein, M., & Ajzen, I. (1975) Belief, Attitude, Intentions and Behavior: An Introduction to theory and research, Addison- Wesley, Boston, MA.
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  • Infarinato, F., Jansen-Kosterink, S., Romano, P., Van Velsen, L., Akker, H.O.D., & Rizza, F. et al. (2020). Acceptance and potential impact of the eWALL platform for mhealth monitoring and promotion in persons with a chronic disease or age-related impairment. Int. J. Environ. Res. Public Health. 17, 7893.
  • Istianingsih, I., & Wijanto, S.H. (2008). Pengaruh Kualitas Sistem Informasi, Perceived Usefulness, dan Kualitas Informasi Terhadap Kepuasan Pengguna Akhir Software Akuntansi. Simposium Nasional Akuntansi 11 Pontianak.
  • Jeong, H. (2011). An investigation of user perceptions and behavioral intentions towards the e-library, Library Collections, Acquisitions, and Technical Services, 35, (2–3): 45–60.
  • Kan, A. (2009). Ölçme sonuçları üzerinde istatistiksel işlemler. H. Atılgan (Ed.), Eğitimde Ölçme ve Değerlendirme (397–456), Ankara: Anı Yayıncılık.
  • Kayserili, A., Tefiroğlu, E. (2023). Dijital Sağlık Hizmetlerinin Hastane İdarecileri Tarafından Değerlendirilmesi. Abant Sağlık Bilimleri ve Teknolojileri Dergisi, (3), 2: 26 – 38.
  • King, W.R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information & Management 43 (6): 740-755.
  • Kowitlawakul, Y. (2011). The technology acceptance model: predicting nurses’ intention to use telemedicine technology (eICU) Computers Informatics Nursing. 29:411–418.
  • Lee, Y., Kozar, K.A., & Larsen, K.R.T. (2003). The Technology acceptance model: past, present, and future, communications of the association for Information Systems 12 (50): 752-780.
  • Lei, J., Liu, J. & L.W. (2021). Hospital information systems in developing countries: a state- of-the-art systematic review. Kybernetes, 50, 12: 3286-3304
  • Ling, K.C., Daud, D., Piew, T.H., Keoy, K. H., & Hassan, P. (2011). Perceived risk, perceived technology, online trust for the online purchase intention in Malaysia. International Journal of Business Management (6) 2: 167-182.
  • Lovelock, C., & Wirtz, J. (2011). Services Marketing: People, Technology, Strategy. New Jersey: Pearson Education, Inc.
  • Mardiana, S., Tjakraatmadja, J.H., & Apprianingsih, A. (2015). DeLone-McLean information system success model revisited: the separation of intention to use- use and the integration of technology acceptance models. International Journal of Economics and Financial Issues 5 (1): 172-182.
  • Marin, H.F. (2007). Nursing informatics: Advances and trends to improve health care quality. International Journal of Medical Informatics, 76, S267YS269.
  • Mao, E., & Palvia, P. (2006). Testing an extended model of IT acceptance in the Chinese Cultural Context. Data Base for advances in information systems 37, (2-3): 20-30.
  • Maskeliūnas, R., Damaševičius, R., & Segal, S. (2019). A review of internet of things technologies for ambient assisted living environments. Futur. Internet, 11, 259.
  • McLean, E., Petter, S., & Delone, W. (2014). Information Systems Success: The quest for the independent variables. Journal of Management Information 4:7-62.
  • Mendez, J.R., Parasuraman, A., & Papadopoulos, N. (2017). Demographics, attitudes, and technology readiness: A cross-cultural analysis and model validation. Marketing Intelligence & Planning 35(1):18-39.
  • Moody, L.E., Slocumb, E., Berg, B., & Jackson, D. (2004). Electronic health records documentation in nursing: nurses’ perceptions, attitudes, and preferences. Computers Informatics Nursing. 22:337–344.
  • Özbek, F., Yardımsever, M., Saka, O. (2007). Akdeniz Üniv. Hastanesi Laboratuvar ve Radyoloji Bilgi Sistemi Mimarisi. In: Akademik Bilişim’07-Ix. Akademik Bilişim Konferansı. Dumlupınar Üniversitesi, Kütahya; 20152007:311-316.
  • Pai, D., & Vanijja, V. (2020). Perceived usability evaluation of Microsoft Teams as an online learning platform during COVID-19 using system usability scale and technology acceptance model in India. Child Youth Serv. Rev. 119: 105535.
  • Pai, F.Y., & Huang, K.I. (2011). Applying the technology acceptance model to the introduction of health information systems. Technol Forecast Soc. Chang. 78(4): 650-660.
  • Parasuraman, A., Zeithaml, V.A., & Berry, L. L. (1988). Servqual- A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1),12-40.
  • Prakash, B. (2010). Patient satisfaction. Journal of Cutaneous and Aesthetic Surgery, 3:151-155.
  • Prasetyo, Y.T., Ong, A.K.S., Concepcion, G.K.F., Navata, F.M.B., Robles, R.A.V., & Tomagos, I.J.T., et al. (2021). Determining factors affecting acceptance of e-learning platforms during the COVID-19 pandemic: integrating extended technology acceptance model and DeLone and Mclean is success model, Sustainability, 13(15):1-16.
  • Premchaiswadi, W.P., Porouhan, N., & Premchaiswadi. (2012). An empirical study of the key success factors to adopt e-learning in Thailand. Paper presented at the 2012 International Conference on Information Society (i-Society), London, 25-28 June.
  • Rafique, H., Almagrabi, A.O., Shamim, A., Anwar, F. & Bashir, A.K. (2020). Investigating the acceptance of mobile library applications with an extended technology acceptance model (TAM). Computers and Education, 145:103-732.
  • Reichertz, P.L. (2006). Hospital information system Past, present, future. International Journal of Medical Informatics, 75(3), 282Y299
  • Republic of Türkiye Ministry of Health. (2015). https://dijitalhastane.saglik. gov.tr/TR4881/ hbys-hastane-bilgi-yonetim-sistemi.html., Access Date May 24, 2024.
  • Rezvani, S., Heidari, S., Roustapisheti, N., Dokhanian, S. (2022). The Effectiveness of System Quality, Habit, and Effort Expectation on Library Application Use Intention: The Mediating Role of Perceived Usefulness, Perceived Ease of Use, and User Satisfaction. International Journal of Business Information, 1 (1):1-18.
  • Schaper, L.K., & Pervan, G.P. (2007). A model of information and communication technology acceptance and utilization by occupational therapists. International Journal of Medical Informatics 76:212-221
  • Seçer, İ. (2018). Psikolojik test geliştirme ve uyarlama süreci: SPSS ve LISREL uygulamaları. Anı yayıncılık. Seddon, P. B. (1997). A respecification and extension of the Delone and Mclean model of Is success. Information Systems Research, 8(3), 240–253
  • Seddon, P., & Kiew, M.Y. (1996). A Partial Test and Development of Delone and Mclean’s Model of IS Success. Australasian Journal of Information Systems, 4(1).
  • Simsir, I., İlhan, S. (2022). Hastanelerde sağlik teknolojileri yönetimi, sağlik hizmetlerinde dijitalleşme ve geleceği. Ankara: İksad Publications.
  • Susilo, W., Ariyanti, M., Sumrahadi, S., Susilo, W., Ariyanti, M., & Sumrahadi, S. (2017). Pengaruh Daya Tarik Promosi, Persepsi Kemudahan, Persepsi Kemanfaatan Dan Harga Terhadap Minat Beli E-toll Card Bank Mandiri. eProceedings of Management, 4 (1).
  • Tarcan, G.Y., Çelik, Y. (2016). Individual factors affecting hospital managers’attitudes towards health information technologies, Hacettepe Sağlık İdaresi Dergisi, 19 (1):35-36.
  • Tavşancıl, E. (2005). Tutumların Ölçülmesi ve SPSS ile Veri Analizi. Ankara, Nobel Basımevi.
  • Taylor, S. & Todd, P. (1995). Decomposition and Crossover Effects in the Theory of Planned Behavior: A Study of Consumer Adoption Intentions. International Journal of Research in Marketing, 12, 137-155.
  • Timmons, S. (2003). Nurses resisting information technology. Nursing Inquiry, 10 (4): 269. Understanding intention to use electronic information resources: a theoretical extension of the technology acceptance model (TAM). AMIA Annual Symposium Proceedings; 2008.
  • Ural, A., & Kılıç, İ. (2006). Bilimsel Araştırma Süreci ve SPSS ile Veri Analizi. (Genişletilmiş İkinci Baskı), Ankara: Detay Yayıncılık.
  • Uslu, D., Toygar, Ş. A., Mansur, F. (2016). Hastane bilgi yönetim sisteminin kullanılabilirliğini belirlemeye yönelik bir araştırma. Uluslararası Sağlık Yönetimi ve Stratejileri Araştırma Dergisi, 2(3):45-57.
  • Ünal, E., Uzun, A.M. (2021). Understanding university students’ behavioral intention to use Edmodo through the lens of an extended technology acceptance model. British Journal of Technology, 52 (2): 619-637.
  • Venkatesh V., & Davis F.D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag. Sci. 46 (2):186-204.
  • Venkatesh, V. (2000). Determinants of perceived ease of use: integrating control, intrinsic motivation, and emotion into the technology acceptance mode–l. Info Syst Res. 11(4):342-365.
  • Walker, P.G.T., Whittaker, C., Watson, O.J., Baguelin, M., Winskill, P., & Hamlet, A. (2020). The impact of COVID-19 and strategies for mitigation and suppression in low- and middle-income countries. Science, 369(6502), 413-422.
  • Wilkins, M.A. (2009). Factors influencing acceptance of electronic health records in hospitals. Perspectives in health information management/AHIMA, American Health Information Management Association. pp 6.
  • Wong, A., Carlbäck, J. (2018). A Study on factors influencing acceptance of using mobile electronic identification applications in Sweden. Project, Business Administration.
  • 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 : journal of the International Society for Quality in Health Care, 20(2), 123–129. https://doi.org/10.1093/intqhc/mzm074
  • Zhang, H.Y., Cocosila, M., & Archer, N. (2010). Factors of adoption of mobile information technology by homecare nurses: A technology acceptance model 2 approach. Computers, Informatics, Nursing, 28(1), 49Y56.
Toplam 82 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Sağlık Bilişimi ve Bilişim Sistemleri, Sağlık Kurumları Yönetimi
Bölüm Makaleler
Yazarlar

Aydan Kayserili

Behire Sançar 0000-0003-1053-6688

Yayımlanma Tarihi 6 Ocak 2025
Gönderilme Tarihi 22 Temmuz 2024
Kabul Tarihi 1 Aralık 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 8 Sayı: 2

Kaynak Göster

APA Kayserili, A., & Sançar, B. (2025). Evaluation of Acceptance of Hospital Information Management System Among Nurses Through Technology Acceptance Model. Eurasian Journal of Health Technology Assessment, 8(2), 99-118. https://doi.org/10.52148/ehta.1520164

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