Determinants of Continuance Intention to Use a Hospital Information System in a Public Hospital in Sichuan, China
Keywords:
Perceived Usefulness, Information Quality, Facilitating Conditions, Self-Efficacy, Continuance IntentionAbstract
Purpose: This study aimed to identify the determinants of Factors affecting continuance intention to use the hospital information system in a public hospital in Sichuan, China: an integration of TAM, ISS, and UTAUT. With the rapid development of the economy, informatization has emerged as a pioneering endeavor, influencing all aspects of life, including the medical field. Hospitals, as the main carriers of healthcare, have undergone significant transformations through the deep integration of traditional medical care and information technology. Research Design, Data, and Methodology: Under the continuous promotion of hospital information systems, the disadvantages caused by their usage have also received more and more attention. Integrating the different perspectives of the users, the system, and the organizational management can help analyze the important factors that affect the users' continuance intention. 506 questionnaires were collected online, and the structural equation model (SEM) was used for data analysis. Results: The results suggest that information quality, facilitating conditions, and perceived usefulness can significantly influence continuance intention, while self-efficacy negatively affects continuance intention. Conclusions: This research provides solid evidence for the validity of the integrated ECM, ISS, and SCT model in the hospital in the model formation system field, which can be a theoretical basis for enhancing medical efficiency.
References
Alsyouf, A., & Ishak, A. K. (2018). Understanding EHRs continuance intention to use from the perspectives of UTAUT: Practice environment moderating effect and top management support as predictor variables. International Journal of Electronic Healthcare, 10(1/2), 24-59.
https://doi.org/10.1504/ijeh.2018.10013367
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191-215. https://doi.org/10.1037/0033-295X.84.2.191
Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351-370. https://doi.org/10.2307/3250921
Boakye, K. G. (2015). Factors influencing mobile data service (MDS) continuance intention: An empirical study. Computers in Human Behavior, 50, 125-131. https://doi.org/10.1016/j.chb.2015.04.008
Chen, S.-C., Jong, D., & Lai, M.-T. (2014). Assessing the relationship between technology readiness and continuance intention in an E-appointment system: Relationship quality as a mediator. Journal of Medical Systems, 38(9), 1-12. https://doi.org/10.1007/s10916-014-0076-3
Cho, J. (2016). The impact of post-adoption beliefs on the continued use of health apps. International Journal of Medical Informatics, 87, 75-83. https://doi.org/10.1016/j.ijmedinf.2015.12.016
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211. https://doi.org/10.2307/249688
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1), 60-95. https://doi.org/10.1287/isre.3.1.60
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.
Erwanti, N., Widodo, A. P., & Nurhayati, O. D. (2018). Determinants of continuance intention to use on-demand mobile service: GO-JEK case. International Journal of Computer Science Issues, 15(6), 9-15.
Gorla, N., Somers, T. M., & Wong, B. (2010). Organizational impact of system quality, information quality, and service quality. The Journal of Strategic Information Systems, 19(3), 207-228. https://doi.org/10.1016/j.jsis.2010.05.001
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th ed.). Pearson Prentice Hall.
Hassan, L. M., Shiu, E., & Parry, S. (2016). Addressing the cross-country applicability of the theory of planned behaviours (TPB): A structured review of multi-country TPB studies. Journal of Consumer Behavior, 15(1), 72-86. https://doi.org/10.1002/cb.1536
Hsiao, J.-L., & Chen, R.-F. (2019). Understanding determinants of health care professionals’ perspectives on mobile health continuance and performance. JMIR Medical Informatics, 7(1), e12350. https://doi.org/10.2196/12350
Hsieh, H.-L., Lai, J.-M., Chuang, B.-K., & Tsai, C.-H. (2022). Determinants of telehealth continuance intention: A multi-perspective framework. Healthcare, 10(10), 2038.
https://doi.org/10.3390/healthcare10102038
Iranmanesh, M., Zailani, S., & Nikbin, D. (2017). RFID continuance usage intention in health care industry. Quality Management in Healthcare, 26(2), 116-123.
https://doi.org/10.1097/qmh.0000000000000134
Islam, M. T., Talukder, M. S., Khayer, A., & Islam, A. N. (2023). Exploring continuance usage intention toward open government data technologies: An integrated approach. VINE Journal of Information Knowledge Management Systems, 53(4), 785-807. https://doi.org/10.1108/vjikms-10-2020-0195
Kusuma, T. A. H., Sandhyaduhita, P., & Shihab, M. R. (2017). Factors influencing continuance intention of travel agency information system use: A case study of Powersuite. 2017 Second International Conference on Informatics and Computing (ICIC), 1-6.
https://doi.org/10.1109/iac.2017.8280644
Larsen, T. J., Sørebø, A. M., & Sørebø, Ø. (2009). The role of task-technology fit as users’ motivation to continue information system use. Computers in Human Behavior, 25(3), 778-784. https://doi.org/10.1016/j.chb.2009.02.006
Lee, Y.-P., Tsai, H.-Y., & Ruangkanjanases, A. (2020). The determinants for food safety push notifications on continuance intention in an e-appointment system for public health medical services: The perspectives of UTAUT and information system quality. International Journal of Environmental Research Public Health, 17(21), 8287. https://doi.org/10.3390/ijerph17218287
Lutfi, A. (2022). Factors influencing the continuance intention to use accounting information system in Jordanian SMEs from the perspectives of UTAUT: Top management support and self-efficacy as predictor factors. Economies, 10(4), 75.https://doi.org/10.3390/economies10040075
Maduku, D. K. (2017). Understanding E-book continuance intention: Empirical evidence from E-book users in a developing country. Cyberpsychology, Behavior, Social Networking, 20(1), 30-36. https://doi.org/10.1089/cyber.2016.0287
Malanga, D. F., & Chigona, W. (2022). User Expectations and Continuance Intention of mHealth among Community Health Workers in Malawi. 2023 Conference on Information Communications Technology and Society (ICTAS), 1-6. https://doi.org/10.1109/ictas56421.2023.10082721
Meidani, Z., Mohammadian, H., Mobaraki, F., Swoboda, W., Moosavi, G. A., & Zare, S. (2021). Exploring the influence of users' characteristics in continuance intention to use electronic medical records (EMR): Extending the expectation confirmation model (ECM). ICIMTH.
Oppong, E., Hinson, R. E., Adeola, O., Muritala, O., & Kosiba, J. P. (2021). The effect of mobile health service quality on user satisfaction and continual usage. Total Quality Management Business Excellence, 32(1-2), 177-198. https://doi.org/10.1080/14783363.2018.1541734
Pedroso, B., Pilatti, L. A., Gutierrez, G. L., & Picinin, C. T. (2016). Quality of life assessment: The World Health Organization Quality of Life (WHOQOL-BREF) instrument. International Journal of Humanities and Applied Sciences, 5(2), 83-102.
Sampat, B., & Sabat, K. C. (2020). Antecedents to Continuance Intention to Use eGovernment Services in India. IFIP Advances in Information and Communication Technology, 2(1), 284-291. https://doi.org/10.1007/978-3-030-64849-7_25
Sica, C., & Ghisi, M. (2007). The Italian versions of the Beck Anxiety Inventory and the Beck Depression Inventory-II: Psychometric properties and discriminant power. In M. A. Lange (Ed.), Leading-edge psychological tests and testing research (pp. 27-50). Nova Science Publishers.
Suzianti, A., & Paramadini, S. A. (2021). Continuance intention of e-learning: The condition and its connection with open innovation. Journal of Open Innovation: Technology, Market, Complexity, 7(1), 97. https://doi.org/10.3390/joitmc7010097
Thong, J. Y., Hong, W., & Tam, K.-Y. (2002). Understanding user acceptance of digital libraries: What are the roles of interface characteristics, organizational context, and individual differences?. International Journal of Human-Computer Studies, 57(3), 215-242.
https://doi.org/10.1016/s1071-5819(02)91024-4
Tian, X.-F., & Wu, R.-Z. (2022). Determinants of the mobile health continuance intention of elders with chronic diseases: An integrated framework of ECM-ISC and UTAUT. International Journal of Environmental Research Public Health, 19(16), 9980. https://doi.org/10.3390/ijerph19169980
Tsai, F.-J., Hu, Y.-J., Chen, C.-Y., Tseng, C.-C., Yeh, G.-L., & Cheng, J.-F. (2021). Using the health belief model to explore nursing students’ relationships between COVID-19 knowledge, health beliefs, cues to action, self-efficacy, and behavioral intention: A cross-sectional survey study. Medicine, 100(11), e25210. https://doi.org/10.1097/md.0000000000025210
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
https://doi.org/10.1287/mnsc.46.2.186.11926
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
Walther, S., Sarker, S., Urbach, N., Sedera, D., Eymann, T., & Otto, B. (2015). Exploring organizational level continuance of cloud-based enterprise systems. Proceedings of the 23rd European Conference on Information Systems (ECIS).
Wang, T., Wang, W., Liang, J., Nuo, M., Wen, Q., Wei, W., & Lei, J. J. N. D. M. (2022). Identifying major impact factors affecting the continuance intention of mHealth: A systematic review and multi-subgroup meta-analysis. 5(1), 145. https://doi.org/10.1038/s41746-022-00692-9
Wang, Y., Chaw, L. Y., Leong, C.-M., Lim, Y. M., & Barut, A. (2023). Massive open online courses learners' continuance intention: Shaping a roadmap to micro-credentials. International Journal of Educational Management, 38(4), 978-1000. https://doi.org/10.1108/ijem-02-2023-0071
Wixom, B. H., & Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16(1), 85-102. https://doi.org/10.1287/isre.1050.0042
Xu, Q., Hou, X., Xiao, T., & Zhao, W. (2022). Factors affecting medical students’ continuance intention to use mobile health applications. Journal of Multidisciplinary Healthcare, 15, 471-484. https://doi.org/10.2147/jmdh.s327347
Yeh, R. K.-J., & Teng, J. T. (2012). Extended conceptualization of perceived usefulness: Empirical test in the context of information system use continuance. Behavior & Information Technology, 31(5), 525-540. https://doi.org/10.1080/0144929x.2010.517272
Yuan, K.-H., Zhang, Z., & Zhao, Y. (2017). Reliable and more powerful methods for power analysis in structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal, 24(3), 315-330. https://doi.org/10.1080/10705511.2016.1276836
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