A Review of the Technology Acceptance Model in Electronic Health Records

Al-Momani Ala'a; Thurasamy Ramayah

Al-Momani Ala'a Postgraduate
Thurasamy Ramayah

Abstract

Over the years, many theories and models have been proposed to explain and interpret behaviours related to the acceptance and usage of technology. The technology acceptance model (TAM), which has been tested in different technological applications, is the most well-known of these models. This article reviews previously published research on the application of TAM to electronic health records. According to the findings of this review, the original TAM was updated and extended to fit the dynamic healthcare service environment by absorbing and integrating variables from various theoretical frameworks as well as by adding variables in specific contextual settings. This demonstrates how the TAM model has been adapted and expanded to meet the specific demands of the healthcare industry, emphasising its usefulness in various settings.

Author Biographies

Al-Momani Ala'a, Postgraduate

Ala’a Al-Momani is currently a Ph.D. candidate at the School of Management, Universiti Sains Malaysia (USM), Malaysia. She was a lecturer for 9 years at the Faculty of Business Administration, Management Department, Taibah University, Al Madinah Al Monawarah, Saudi Arabia. She holds Bachelor’s degree in Management Information Systems from Yarmouk University, Jordan, in 2008. She also received her Master’s degree in Management Information Systems from Yarmouk University, Jordan, in 2013. Her areas of interest include technology management and research methodology. She is well-trained in quantitative analysis using SPSS, AMOS, and SmartPLS. She also holds a Professional Certificate in Business Analytics from the School of Management, Universiti Sains Malaysia (USM), Malaysia, in 2020.

Thurasamy Ramayah

T. Ramayah, is currently a Professor of Technology Management, School of Management, Universiti Sains Malaysia, Visiting Professor Daffodil International University (DIU) Bangladesh, Fakulti Ekonomi dan Pengurusan, Universiti Kebangsaan Malaysia (UKM), Faculty of Business, Economics and Social Development, Universiti Malaysia Terengganu (UMT), Faculty of Economics and Business, Universiti Malaysia Sarawak (UNIMAS), Fakulti Pengurusan dan Perniagaan, Universiti Teknologi Mara (UiTM) and Adjunct Professor at Faculty of Economics and Business Universitas Indonesia (UI), University Center for Research & Development (UCRD), Chandigarh University (CU), India, Sunway University, Universiti Tunku Abdul Rahman (UTAR) and Universiti Tenaga Nasional (UNITEN), Malaysia. He has an h-index of 103 and citation of 42,126 in Google Scholar and i-10 index of 497, his h-index in SCOPUS is 59, with 12,651 citations while his h-index in ISI/Clarivate is 46 with 8,414 citations. His full profile can be accessed from http://www.ramayah.com

References

Ajzen, I., & Fishbein, M. (1980). Theory of Reasoned Action in understanding attitudes and predicting social behaviour.
Al-Adwan, A. S., & Berger, H. (2015). Exploring physicians' behavioural intention toward the adoption of electronic health records: An empirical study from Jordan. International Journal of Healthcare Technology and Management, 15(2), 89. https://doi.org/10.1504/ijhtm.2015.074538.
Alipour, J., Lafti, S. S., Majdabadi, H. A., 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. IIOAB Journal, 119–123.
Al-Qaysi, N., Mohamad-Nordin, N., & Al-Emran, M. (2020). Employing the technology acceptance model in Social Media: A systematic review. Education and Information Technologies, 25(6), 4961–5002. https://doi.org/10.1007/s10639-020-10197-1.
Alsharo, M., Alnsour, Y., & Alabdallah, M. (2020). How habit affects continuous use: Evidence from Jordan’s National Health Information System. Informatics for Health and Social Care, 45(1), 43–56. https://doi.org/10.1080/17538157.2018.1540423.
Beglaryan, M., Petrosyan, V., & Bunker, E. (2017). Development of a tripolar model of technology acceptance: Hospital-based physicians’ perspective on Ehr. International Journal of Medical Informatics, 102, 50–61. https://doi.org/10.1016/j.ijmedinf.2017.02.013.
Chintalapati, N., & Daruri, V. S. (2017). Examining the use of YouTube as a learning resource in higher education: Scale Development and validation of TAM Model. Telematics and Informatics, 34(6), 853–860. https://doi.org/10.1016/j.tele.2016.08.008.
Cho, Y., Kim, M., & Choi, M. (2021). Factors associated with nurses' user resistance to change of Electronic Health Record (preprint). https://doi.org/10.2196/preprints.25582.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of Information Technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008.
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.
Dhagarra, D., Goswami, M., & Kumar, G. (2020). Impact of trust and privacy concerns on technology acceptance in Healthcare: An Indian perspective. International Journal of Medical Informatics, 141, 104164. https://doi.org/10.1016/j.ijmedinf.2020.104164.
Ebnehoseini, Z., Tara, M., Tabesh, H., Dindar, F. H., & Hasibian, S. (2020). Understanding key factors affecting on hospital electronic health record (EHR) adoption. Journal of family medicine and primary care, 9(8), 4348.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Contemporary Sociology, 6(2), 244–245.
Gagnon, M.-P., Ghandour, E. K., Talla, P. K., Simonyan, D., Godin, G., Labrecque, M., Ouimet, M., & Rousseau, M. (2014). Electronic health record acceptance by physicians: Testing an integrated theoretical model. Journal of Biomedical Informatics, 48, 17–27. https://doi.org/10.1016/j.jbi.2013.10.010.
Gajanayake, R., Sahama, T., & Iannella, R. (2013). The role of perceived usefulness and attitude on electronic health record acceptance. 2013 IEEE 15th International Conference on E-Health Networking, Applications and Services (Healthcom 2013), 388–393.
Hoque, M. R., Bao, Y., & Sorwar, G. (2017). Investigating factors influencing the adoption of e-health in developing countries: A patient’s perspective. Informatics for Health and Social Care, 42(1), 1–17. https://doi.org/10.3109/17538157.2015.1075541.
Isaac, O., Abdullah, Z., Aldholay, A. H., & Abdulbaqi Ameen, A. (2019). Antecedents and outcomes of internet usage within organisations in Yemen: An extension of the unified theory of acceptance and use of technology (utaut) model. Asia Pacific Management Review, 24(4), 335–354. https://doi.org/10.1016/j.apmrv.2018.12.003.
Isaac, O., Abdullah, Z., Ramayah, T., & Mutahar, A. M. (2017). Internet usage, user satisfaction, task-technology fit, and performance impact among public sector employees in Yemen. The International Journal of Information and Learning Technology, 34(3), 210–241. https://doi.org/10.1108/ijilt-11-2016-0051.
Kalayou, M. H., Endehabtu, B. F., & Tilahun, B. (2020).

the applicability of the modified technology acceptance model (TAM) on the sustainable adoption of eHealth Systems in resource-limited settings

. Journal of Multidisciplinary Healthcare, Volume 13, 1827–1837. https://doi.org/10.2147/jmdh.s284973.
King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information & Management, 43(6), 740–755. https://doi.org/10.1016/j.im.2006.05.003.
Kowitlawakul, Y., Chan, S. W., Pulcini, J., & Wang, W. (2015). Factors influencing nursing students' acceptance of electronic health records for Nursing Education (EHRNE) software program. Nurse Education Today, 35(1), 189–194. https://doi.org/10.1016/j.nedt.2014.05.010.
Mutahar, A. M., Daud, N. M., Ramayah, T., Isaac, O., & Aldholay, A. H. (2018). The effect of awareness and perceived risk on the technology acceptance model (TAM): Mobile Banking in Yemen. International Journal of Services and Standards, 12(2), 180. https://doi.org/10.1504/ijss.2018.091840.
Ortega Egea, J. M., & Román González, M. V. (2011). Explaining physicians’ acceptance of EHCR systems: An extension of TAM with trust and risk factors. Computers in Human Behavior, 27(1), 319–332. https://doi.org/10.1016/j.chb.2010.08.010.
Pavlovic, A., Rajovic, N., Pavlovic Stojanovic, J., Akinyombo, D., Ugljesic, M., Pavlica, M., Pavlovic, V., Randjelovic, S., Spaic, D., Masic, S., Stanisavljevic, D., & Milic, N. (2021). Electronic health record acceptance by physicians: A single hospital experience in daily practice. Bio Med Informatics, 1(1), 6–17. https://doi.org/10.3390/biomedinformatics1010002.
Saare, M. A., Mahdi, A. A., Lashari, S. A., Sari, S. A., & Hamid, N. A. (2021). Measuring prevailing practices of healthcare professional on electronic health record through the lens of Iraq. Bulletin of Electrical Engineering and Informatics, 10(2), 970–977. https://doi.org/10.11591/eei.v10i2.2408.
Shachak, A., Kuziemsky, C., & Petersen, C. (2019). Beyond Tam and utaut: Future directions for hit implementation research. Journal of Biomedical Informatics, 100, 103315. https://doi.org/10.1016/j.jbi.2019.103315.
Sintonen, S., Mäkelä, K., & Miettinen, R. (2015). User acceptance of electronic health records: A post-implementation study. International Journal of Healthcare Technology and Management, 15(2), 162. https://doi.org/10.1504/ijhtm.2015.074556.
Steininger, K., & Stiglbauer, B. (2015). EHR acceptance among Austrian resident doctors. Health Policy and Technology, 4(2), 121–130. https://doi.org/10.1016/j.hlpt.2015.02.003.
Steininger, K., Stiglbauer, B., Baumgartner, B., & Engleder, B. (2014). Factors explaining physicians’ acceptance of electronic health records. 2014 47th Hawaii International Conference on System Sciences, 2768–2777.
Straub, D., Keil, M., & Brenner, W. (1997). Testing the technology acceptance model across cultures: A three country study. Information & Management, 33(1), 1–11. https://doi.org/10.1016/s0378-7206(97)00026-8.
Sun, H., & Zhang, P. (2006). The role of moderating factors in user technology acceptance. International Journal of Human-Computer Studies, 64(2), 53–78. https://doi.org/10.1016/j.ijhcs.2005.04.013.
Tanwar, S., Tyagi, S., & Kumar, N. (Eds.). (2019). Security and Privacy of Electronic Healthcare Records: Concepts, Paradigms and Solutions. Institution of Engineering and Technology.
Terrizzi, S., Sherer, S., Meyerhoefer, C., Sheinberg, M., & Levick, D. (2012). Extending the technology acceptance model in healthcare: Identifying the role of trust and shared information. 18th Americas Conference on Information Systems 2012, AMCIS 2012, 6, 4518–4527.
Tubaishat, A. (2017). Perceived usefulness and perceived ease of use of electronic health records among nurses: Application of Technology Acceptance Model. Informatics for Health and Social Care, 43(4), 379–389. https://doi.org/10.1080/17538157.2017.1363761.
Venkatesh, Morris, Davis, & Davis. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425. https://doi.org/10.2307/30036540.
Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating perceived behavioral control, computer anxiety and enjoyment into the technology acceptance model. Information Systems Research, 11, 342–365.
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315. https://doi.org/10.1111/j.1540-5915.2008.00192.x.
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.
Vitari, C., & Ologeanu-Taddei, R. (2018). The intention to use an electronic health record and its antecedents among three different categories of clinical staff. BMC Health Services Research, 18(1). https://doi.org/10.1186/s12913-018-3022-0.
Yoo, S., Lim, K., Jung, S. Y., Lee, K., Lee, D., Kim, S., Lee, H.-Y., & Hwang, H. (2022). Examining the adoption and implementation of behavioral electronic health records by healthcare professionals based on the clinical adoption framework. BMC Medical Informatics and Decision Making, 22(1). https://doi.org/10.1186/s12911-022-01959-7.
Zayyad, M. A., & Toycan, M. (2018). Factors affecting sustainable adoption of e-health technology in developing countries: An exploratory survey of Nigerian hospitals from the perspective of healthcare professionals. PeerJ, 6. https://doi.org/10.7717/peerj.4436.