Use of the Technology Acceptance Model for Electronic Medical Records in Nursing Documentation: Scooping Review
Abstract
Digital transformation in the health sector, especially in health services, where previously health facilities used manual medical records, switched to electronic medical records. The Technology Acceptance Model is a framework used to understand how users accept and adopt technology, in this case electronic medical records. This study aims to identifyuse of the Technology Acceptance Model on nurses' acceptance of the implementation of electronic medical records. This study used the scooping review method. Literature searches were obtained through 3 databases, namely PubMed and CINAHL, as well as Google Scholar with the keywords: Technology Acceptance Model, Nursing Documentation, Electronic Medical Record's. Articles were extracted manually through tabulation and analyzed using a descriptive analysis approach. The publication period in the article search is the last 10 years (2014-2024). Collecting data used manual table. There were 8 articles included in this study, where the results of the scoping showed a significant relationship between perceived usefulness and perceived ease of use on nurses' acceptance of attitudes and attitudes had a strong influence on intentions to use electronic medical records. The importance of management support in preparing electronic medical records from their usefulness and ease of use in supporting nursing service activities in health facilities.
References
Abdullah, F., & Ward, R. (2016). Developing a general extended technology acceptance model for e-learning (GETAMEL) by analysing commonly used external factors. Comput. Hum. Behav., 56. https://doi.org/10.1016/j.chb.2015.11.036
Akman, I., & Turhan, C. (2017). User acceptance of social learning systems in higher education: An application of the extended technology acceptance model. Innovations in Education and Teaching International, 54. https://doi.org/10.1080/14703297.2015.1093426
Alfadda, H., & Mahdi, H. (2021). Measuring students’ use of Zoom application in language course based on the technology acceptance model (TAM). Journal of Psycholinguistic Research. https://doi.org/10.1007/s10936-020-09752-1
Alfuqaha, O., & Alsharah, H. (2018). Burnout among nurses and teachers in Jordan: a comparative study. Arch Psychiatry Psychother, 20. https://doi.org/10.12740/APP/80168
Alhur, A. (2023). An Investigation of Nurses’ Perceptions of the Usefulness and Easiness of Using Electronic Medical Records in Saudi Arabia: A Technology Acceptance Model: Technology Acceptance Model . Indonesian Journal of Information Systems, 5(2 SE-Articles), 30–42. https://doi.org/10.24002/ijis.v5i2.6833
Alipour, J., Lafti, S., Majdabadi, H., Yazdiyani, A., & Valinejadi, A. (2016). Factors affecting hospital information system acceptance by caregivers of educational hospitals based on technology acceptance model (TAM): A study in Iran. A JOURNAL OF MULTIDISCIPLINARY SCIENCE AND TECHNOLOGY, 7, 119–123.
Arksey, H., & O’Malley, L. (2005). Scoping studies: towards a methodological framework. Int J Soc Res Methodol, 8. https://doi.org/10.1080/1364557032000119616
Asiri, H., AlDosari, B., & Saddik, B. (2014). Nurses’ attitude, acceptance and use of Electronic Medical Records (EMR) in King AbdulAziz Medical City (KAMC) in Riyadh, Saudi Arabia. Merit Res Journals, 2.
Ayala Solares, J. R., Diletta Raimondi, F. E., Zhu, Y., Rahimian, F., Canoy, D., Tran, J., Pinho Gomes, A. C., Payberah, A. H., Zottoli, M., Nazarzadeh, M., Conrad, N., Rahimi, K., & Salimi-Khorshidi, G. (2020). Deep learning for electronic health records: A comparative review of multiple deep neural architectures. Journal of Biomedical Informatics, 101, 103337. https://doi.org/https://doi.org/10.1016/j.jbi.2019.103337
Barzekar, H., Ebrahimzadeh, F., Luo, J., Karami, M., Robati, Z., & Goodarzi, P. (2019). Adoption of Hospital Information System Among Nurses: a Technology Acceptance Model Approach. Acta Informatica Medica : AIM : Journal of the Society for Medical Informatics of Bosnia & Herzegovina : Casopis Drustva Za Medicinsku Informatiku BiH, 27(5), 305–310. https://doi.org/10.5455/aim.2019.27.305-310
Chelladurai, U., & Pandian, S. (2022). A novel blockchain based electronic health record automation system for healthcare. Journal of Ambient Intelligence and Humanized Computing, 13(1), 693–703. https://doi.org/10.1007/s12652-021-03163-3
Dunn Lopez, K., Chin, C. L., Leitão Azevedo, R. F., Kaushik, V., Roy, B., Schuh, W., Banks, K., Sousa, V., & Morrow, D. (2021). Electronic health record usability and workload changes over time for provider and nursing staff following transition to new EHR. Appl Ergon, 93. https://doi.org/10.1016/j.apergo.2021.103359
Groot, K., Veer, A. J. E., Paans, W., & Francke, A. L. (2020). Use of electronic health records in relation to standardized terminologies: a nationwide survey of nursing staff experiences. Int J Nurs Stud, 104. https://doi.org/10.1016/j.ijnurstu.2020.103523
Intansari, I., Rahmaniati, M., & Hapsari, D. F. (2023). Evaluasi Penerapan Rekam Medis Elektronik Dengan Pendekatan Technology Acceptance Model di Rumah Sakit X di Kota Surabaya. J-REMI : Jurnal Rekam Medik Dan Informasi Kesehatan, 4(3 SE-), 108–117. https://doi.org/10.25047/j-remi.v4i3.3914
Kaipio, J., Kuusisto, A., Hyppönen, H., Heponiemi, T., & Lääveri, T. (2020). Physicians’ and nurses’ experiences on EHR usability: Comparison between the professional groups by employment sector and system brand. International Journal of Medical Informatics, 134, 104018. https://doi.org/10.1016/j.ijmedinf.2019.104018
Khairat, S., Xi, L., Liu, S., Shrestha, S., & Hill, C. (2020). Understanding the Association Between Electronic Health Record Satisfaction and the Well-Being of Nurses : Survey Study Corresponding Author : 3, 1–9. https://doi.org/10.2196/13996
Moy, A. J., Schwartz, J. M., Chen, R. J., Sadri, S., Lucas, E., Cato, K. D., & Rossetti, S. C. (2021). Measurement of clinical documentation burden among physicians and nurses using electronic health records: a scoping review. J Am Med Inform Assoc, 28. https://doi.org/10.1093/jamia/ocaa325
Nagasubramanian, G., Sakthivel, R. K., Patan, R., Gandomi, A. H., Sankayya, M., & Balusamy, B. (2020). Securing e-health records using keyless signature infrastructure blockchain technology in the cloud. Neural Computing and Applications, 32(3), 639–647. https://doi.org/10.1007/s00521-018-3915-1
Rajkomar, A., Oren, E., & Chen, K. (2018). Scalable and accurate deep learning with electronic health records. NPJ Digit Med, 1. https://doi.org/10.1038/s41746-018-0029-1
Rastogi, S., Tevaarwerk, A. J., Sesto, M., Van Remortel, B., Date, P., Gangnon, R., Thraen-Borowski, K., & Cadmus-Bertram, L. (2020). Effect of a technology-supported physical activity intervention on health-related quality of life, sleep, and processes of behavior change in cancer survivors: A randomized controlled trial. Psycho-Oncology, 29(11), 1917–1926. https://doi.org/10.1002/pon.5524
Rauniar, R., Rawski, G., Yang, J., & Johnson, B. (2014). Technology acceptance model (TAM) and social media usage: An empirical study on Facebook. Journal of Enterprise Information Management, 27. https://doi.org/10.1108/JEIM-04-2012-0011
Schopf, T. R., Nedrebø, B., Hufthammer, K. O., Daphu, I. K., & Lærum, H. (2019). How well is the electronic health record supporting the clinical tasks of hospital physicians? A survey of physicians at three Norwegian hospitals. BMC Health Services Research, 19(1), 934. https://doi.org/10.1186/s12913-019-4763-0
Snyder, C., Choi, Y., Blackford, A. L., DeSanto, J., Mayonado, N., Rall, S., White, S., Bowie, J., Cowall, D. E., Johnston, F., Joyner, R. L., Mischtschuk, J., Peairs, K. S., Thorner, E., Tran, P. T., Wolff, A. C., & Smith, K. C. (2022). Simplifying Survivorship Care Planning: A Randomized Controlled Trial Comparing 3 Care Plan Delivery Approaches. Journal of the National Cancer Institute, 114(1), 139–148. https://doi.org/10.1093/jnci/djab148
Tavakoli, N., Jahanbakhsh, M., Shahin, A., Mokhtari, H., & Rafiei, M. (2013). Electronic medical record in central polyclinic of isfahan oil industry: a case study based on technology acceptance model. In Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH (Vol. 21, Issue 1, pp. 23–25). https://doi.org/10.5455/AIM.2012.21.23-25
Tavares, J., Goulão, A., & Oliveira, T. (2018). Electronic Health Record Portals adoption: Empirical model based on UTAUT2. Informatics Heal Soc Care, 43.
Walker, R. M., Burmeister, E., Jeffrey, C., Birgan, S., Garrahy, E., Andrews, J., Hada, A., & Aitken, L. M. (2020). The impact of an integrated electronic health record on nurse time at the bedside: A pre-post continuous time and motion study. Collegian, 27(1), 63–74. https://doi.org/https://doi.org/10.1016/j.colegn.2019.06.006
Walle, A. D., Ferede, T. A., Baykemagn, N. D., Shimie, A. W., Kebede, S. D., Tegegne, M. D., Wubante, S. M., Yehula, C. M., Demsash, A. W., Melaku, M. S., & Mengistie, M. B. (2023). Predicting healthcare professionals’ acceptance towards electronic personal health record systems in a resource-limited setting: using modified technology acceptance model. BMJ Health & Care Informatics, 30(1). https://doi.org/10.1136/bmjhci-2022-100707
Weerasinghe, S., & Hindagolla, M. C. B. (2018). Technology acceptance model and social network sites (SNS): A selected review of literature. Global Knowledge, Memory and Communication, 67. https://doi.org/10.1108/GKMC-09-2017-0079
Zhang, Q., Fu, Y., Lu, Y., Zhang, Y., Huang, Q., Yang, Y., Zhang, K., & Li, M. (2021). Impact of Virtual Reality-Based Therapies on Cognition and Mental Health of Stroke Patients: Systematic Review and Meta-analysis. Journal of Medical Internet Research, 23(11), e31007. https://doi.org/10.2196/31007
Zullig, L. L., Shahsahebi, M., Neely, B., Hyslop, T., Avecilla, R. A. V, Griffin, B. M., Clayton-Stiglbauer, K., Coles, T., Owen, L., Reeve, B. B., Shah, K., Shelby, R. A., Sutton, L., Dinan, M. A., Zafar, S. Y., Shah, N. P., Dent, S., & Oeffinger, K. C. (2021). Low-touch, team-based care for co-morbidity management in cancer patients: the ONE TEAM randomized controlled trial. BMC Family Practice, 22(1), 234. https://doi.org/10.1186/s12875-021-01569-8
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