The Unified Theory of Acceptance and Use of Technology (UTAUT) Method in Evaluating Hospital Management Information Systems
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Published:
Sep 30, 2024
Keywords:
Collaboration, Convenience, Hospital Management Information System, Second keyword, UTAUT
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Abstract
Hospital management information systems play an important role in managing patient care together. Technology acceptance models such as the Unified Theory of Acceptance and Use of Technology (UTAUT) have proven important for predicting information technology acceptance. This literature review aims to evaluate the extended UTAUT model to predict hospital management information systems represented by behavioral intention, convenience, and ease of collaboration. The methods used in this paper are literature review, collection and analysis of scientific articles, and other scientific sources. The results of the literature review show that UTAUT can be a theoretical approach that supports hospital management information systems
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La’a, M. ., Tangdililing, M. L., & Paramarta, V. . (2024). The Unified Theory of Acceptance and Use of Technology (UTAUT) Method in Evaluating Hospital Management Information Systems. Journal of Midwifery and Nursing, 6(3), 710-716. https://doi.org/10.35335/jmn.v6i3.5174
References
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Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982
Dwivedi, Y. K., Rana, N. P., Tamilmani, K., & Raman, R. (2020). A meta-analysis based modified unified theory of acceptance and use of technology (meta-UTAUT): a review of emerging literature. Current Opinion in Psychology, 36, 13–18. https://doi.org/10.1016/j.copsyc.2020.03.008
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Hasan, Z., Ahmed, M. W., Mehdi, G. G., Khan, J. A. M., & Islam, Z. (2022). Factors affecting the healthcare utilization from Shasthyo Suroksha Karmasuchi scheme among the below ? poverty ? line population in one subdistrict in Bangladesh?: a cross sectional study. BMC Health Services Research, 22(885), 1–14. https://doi.org/10.1186/s12913-022-08254-1
Jiang, Y., & Lau, A. K. W. (2023). Understanding Post-Adoption Behavioral Intentions of Mobile Health Service Users: An Empirical Study during COVID-19. International Journal of Environmental Research and Public Health, 20(5). https://doi.org/10.3390/ijerph20053907
Kamalzadeh. (2015). Factors Determining Nurse Acceptance of Hospital Information Systems in the Medication Process. Journal of Soft Computing and Decision Support Systems, 2(6), 14–19.
Kijsanayotin, B., Pannarunothai, S., & Speedie, S. M. (2009). Factors influencing health information technology adoption in Thailand’s community health centers: Applying the UTAUT model. International Journal of Medical Informatics, 78(6), 404–416. https://doi.org/10.1016/j.ijmedinf.2008.12.005
Li, J., Talaei-Khoei, A., Seale, H., Ray, P., & MacIntyre, C. R. (2013). Health Care Provider Adoption of eHealth: Systematic Literature Review. Interactive Journal of Medical Research, 2(1), e7. https://doi.org/10.2196/ijmr.2468
Li, W., Gui, J., Luo, X., Yang, J., Zhang, T., & Tang, Q. (2023). Determinants of intention with remote health management service among urban older adults: A Unified Theory of Acceptance and Use of Technology perspective. Frontiers in Public Health, 11, 1117518.
Mannheim, I., Varlamova, M., van Zaalen, Y., & Wouters, E. J. M. (2023). The Role of Ageism in the Acceptance and Use of Digital Technology. Journal of Applied Gerontology, 42(6), 1283–1294. https://doi.org/10.1177/07334648231163426
Mohammadi, A., Khatami, F., Azimbeik, Z., Khajavi, A., Aloosh, M., & Aghamir, S. M. K. (2022). Hospital-acquired infections in a tertiary hospital in Iran before and during the COVID-19 pandemic. Wiener Medizinische Wochenschrift, 172(9–10), 220–226. https://doi.org/10.1007/s10354-022-00918-1
Nunes, N., Adamo, G., Ribeiro, M., Gouveia, B. R., Rubio Gouveia, E., Teixeira, P., & Nisi, V. (2022). Modeling Adoption, Security, and Privacy of COVID-19 Apps: Findings and Recommendations From an Empirical Study Using the Unified Theory of Acceptance and Use of Technology. JMIR Human Factors, 9(3), 1–21. https://doi.org/10.2196/35434
Sadoughi, F., Khodaveisi, T., & Ahmadi, H. (2019). The used theories for the adoption of electronic health record: a systematic literature review. Health and Technology, 9(4), 383–400. https://doi.org/10.1007/s12553-018-0277-8
Salinero, S. P. (2016). Understanding the Technology Usage and Acceptance Behaviors of Healthcare Information Technology Users?: a Comparative Cross-Case Analysis. September.
Schretzlmaier, P., Hecker, A., & Ammenwerth, E. (2022). Suitability of the Unified Theory of Acceptance and Use of Technology 2 Model for Predicting mHealth Acceptance Using Diabetes as an Example: Qualitative Methods Triangulation Study. JMIR Human Factors, 9(1). https://doi.org/10.2196/34918
Sharifian, R., Askarian, F., Nematolahi, M., & Farhadi, P. (2014). Factors influencing nurses’ acceptance of hospital information systems in Iran: application of the Unified Theory of Acceptance and Use of Technology. Health Information Management Journal, 43(3), 23–28. https://doi.org/10.12826/18333575.2014.0001.Sharifian
Simpson, E., Brown, R., Sillence, E., Coventry, L., Lloyd, K., Gibbs, J., Tariq, S., & Durrant, A. C. (2021). Understanding the Barriers and Facilitators to Sharing Patient-Generated Health Data Using Digital Technology for People Living With Long-Term Health Conditions: A Narrative Review. Frontiers in Public Health, 9(November). https://doi.org/10.3389/fpubh.2021.641424
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly: Management Information Systems, 27(3), 425–478. https://doi.org/10.2307/30036540
Venkatesh, V., Sykes, T. A., & Zhang, X. (2011). “Just what the doctor ordered”: A revised UTAUT for EMR system adoption and use by doctors. Proceedings of the Annual Hawaii International Conference on System Sciences, 1–10. https://doi.org/10.1109/HICSS.2011.1
Wilson, J., Heinsch, M., Betts, D., Booth, D., & Kay-Lambkin, F. (2021). Barriers and facilitators to the use of e-health by older adults: a scoping review. BMC Public Health, 21(1), 1–12. https://doi.org/10.1186/s12889-021-11623-w
Yasumura, S., & Abe, M. (2017). Fukushima Health Management Survey and Related Issues. Asia-Pacific Journal of Public Health, 29(2_suppl), 29S-35S. https://doi.org/10.1177/1010539516687022
Yehualashet, D. E., Seboka, B. T., Tesfa, G. A., Demeke, A. D., & Amede, E. S. (2021). Barriers to the adoption of electronic medical record system in ethiopia: A systematic review. Journal of Multidisciplinary Healthcare, 14, 2597–2603. https://doi.org/10.2147/JMDH.S327539
Yin, Z., Yan, J., Fang, S., Wang, D., & Han, D. (2022). User acceptance of wearable intelligent medical devices through a modified unified theory of acceptance and use of technology. Annals of Translational Medicine, 10(11), 629–629. https://doi.org/10.21037/atm-21-5510
Zhou, L. L., Owusu-Marfo, J., Asante Antwi, H., Antwi, M. O., Kachie, A. D. T., & Ampon-Wireko, S. (2019). “assessment of the social influence and facilitating conditions that support nurses’’ adoption of hospital electronic information management systems (HEIMS) in Ghana using the unified theory of acceptance and use of technology (UTAUT) model".” BMC Medical Informatics and Decision Making, 19(1), 1–9. https://doi.org/10.1186/s12911-019-0956-z
Cobelli, N., Cassia, F., & Donvito, R. (2023). Pharmacists’ attitudes and intention to adopt telemedicine: Integrating the market-orientation paradigm and the UTAUT. Technological Forecasting and Social Change, 196(September), 122871. https://doi.org/10.1016/j.techfore.2023.122871
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982
Dwivedi, Y. K., Rana, N. P., Tamilmani, K., & Raman, R. (2020). A meta-analysis based modified unified theory of acceptance and use of technology (meta-UTAUT): a review of emerging literature. Current Opinion in Psychology, 36, 13–18. https://doi.org/10.1016/j.copsyc.2020.03.008
Fres. (2022). No Title??? ??? ????? ?? ?? ????? ???? ??????. ????, 8.5.2017, 2003–2005. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders
Hasan, Z., Ahmed, M. W., Mehdi, G. G., Khan, J. A. M., & Islam, Z. (2022). Factors affecting the healthcare utilization from Shasthyo Suroksha Karmasuchi scheme among the below ? poverty ? line population in one subdistrict in Bangladesh?: a cross sectional study. BMC Health Services Research, 22(885), 1–14. https://doi.org/10.1186/s12913-022-08254-1
Jiang, Y., & Lau, A. K. W. (2023). Understanding Post-Adoption Behavioral Intentions of Mobile Health Service Users: An Empirical Study during COVID-19. International Journal of Environmental Research and Public Health, 20(5). https://doi.org/10.3390/ijerph20053907
Kamalzadeh. (2015). Factors Determining Nurse Acceptance of Hospital Information Systems in the Medication Process. Journal of Soft Computing and Decision Support Systems, 2(6), 14–19.
Kijsanayotin, B., Pannarunothai, S., & Speedie, S. M. (2009). Factors influencing health information technology adoption in Thailand’s community health centers: Applying the UTAUT model. International Journal of Medical Informatics, 78(6), 404–416. https://doi.org/10.1016/j.ijmedinf.2008.12.005
Li, J., Talaei-Khoei, A., Seale, H., Ray, P., & MacIntyre, C. R. (2013). Health Care Provider Adoption of eHealth: Systematic Literature Review. Interactive Journal of Medical Research, 2(1), e7. https://doi.org/10.2196/ijmr.2468
Li, W., Gui, J., Luo, X., Yang, J., Zhang, T., & Tang, Q. (2023). Determinants of intention with remote health management service among urban older adults: A Unified Theory of Acceptance and Use of Technology perspective. Frontiers in Public Health, 11, 1117518.
Mannheim, I., Varlamova, M., van Zaalen, Y., & Wouters, E. J. M. (2023). The Role of Ageism in the Acceptance and Use of Digital Technology. Journal of Applied Gerontology, 42(6), 1283–1294. https://doi.org/10.1177/07334648231163426
Mohammadi, A., Khatami, F., Azimbeik, Z., Khajavi, A., Aloosh, M., & Aghamir, S. M. K. (2022). Hospital-acquired infections in a tertiary hospital in Iran before and during the COVID-19 pandemic. Wiener Medizinische Wochenschrift, 172(9–10), 220–226. https://doi.org/10.1007/s10354-022-00918-1
Nunes, N., Adamo, G., Ribeiro, M., Gouveia, B. R., Rubio Gouveia, E., Teixeira, P., & Nisi, V. (2022). Modeling Adoption, Security, and Privacy of COVID-19 Apps: Findings and Recommendations From an Empirical Study Using the Unified Theory of Acceptance and Use of Technology. JMIR Human Factors, 9(3), 1–21. https://doi.org/10.2196/35434
Sadoughi, F., Khodaveisi, T., & Ahmadi, H. (2019). The used theories for the adoption of electronic health record: a systematic literature review. Health and Technology, 9(4), 383–400. https://doi.org/10.1007/s12553-018-0277-8
Salinero, S. P. (2016). Understanding the Technology Usage and Acceptance Behaviors of Healthcare Information Technology Users?: a Comparative Cross-Case Analysis. September.
Schretzlmaier, P., Hecker, A., & Ammenwerth, E. (2022). Suitability of the Unified Theory of Acceptance and Use of Technology 2 Model for Predicting mHealth Acceptance Using Diabetes as an Example: Qualitative Methods Triangulation Study. JMIR Human Factors, 9(1). https://doi.org/10.2196/34918
Sharifian, R., Askarian, F., Nematolahi, M., & Farhadi, P. (2014). Factors influencing nurses’ acceptance of hospital information systems in Iran: application of the Unified Theory of Acceptance and Use of Technology. Health Information Management Journal, 43(3), 23–28. https://doi.org/10.12826/18333575.2014.0001.Sharifian
Simpson, E., Brown, R., Sillence, E., Coventry, L., Lloyd, K., Gibbs, J., Tariq, S., & Durrant, A. C. (2021). Understanding the Barriers and Facilitators to Sharing Patient-Generated Health Data Using Digital Technology for People Living With Long-Term Health Conditions: A Narrative Review. Frontiers in Public Health, 9(November). https://doi.org/10.3389/fpubh.2021.641424
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly: Management Information Systems, 27(3), 425–478. https://doi.org/10.2307/30036540
Venkatesh, V., Sykes, T. A., & Zhang, X. (2011). “Just what the doctor ordered”: A revised UTAUT for EMR system adoption and use by doctors. Proceedings of the Annual Hawaii International Conference on System Sciences, 1–10. https://doi.org/10.1109/HICSS.2011.1
Wilson, J., Heinsch, M., Betts, D., Booth, D., & Kay-Lambkin, F. (2021). Barriers and facilitators to the use of e-health by older adults: a scoping review. BMC Public Health, 21(1), 1–12. https://doi.org/10.1186/s12889-021-11623-w
Yasumura, S., & Abe, M. (2017). Fukushima Health Management Survey and Related Issues. Asia-Pacific Journal of Public Health, 29(2_suppl), 29S-35S. https://doi.org/10.1177/1010539516687022
Yehualashet, D. E., Seboka, B. T., Tesfa, G. A., Demeke, A. D., & Amede, E. S. (2021). Barriers to the adoption of electronic medical record system in ethiopia: A systematic review. Journal of Multidisciplinary Healthcare, 14, 2597–2603. https://doi.org/10.2147/JMDH.S327539
Yin, Z., Yan, J., Fang, S., Wang, D., & Han, D. (2022). User acceptance of wearable intelligent medical devices through a modified unified theory of acceptance and use of technology. Annals of Translational Medicine, 10(11), 629–629. https://doi.org/10.21037/atm-21-5510
Zhou, L. L., Owusu-Marfo, J., Asante Antwi, H., Antwi, M. O., Kachie, A. D. T., & Ampon-Wireko, S. (2019). “assessment of the social influence and facilitating conditions that support nurses’’ adoption of hospital electronic information management systems (HEIMS) in Ghana using the unified theory of acceptance and use of technology (UTAUT) model".” BMC Medical Informatics and Decision Making, 19(1), 1–9. https://doi.org/10.1186/s12911-019-0956-z
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