A Conceptual Study of User Adoption for Military Lifetime Health Record Systems

Hasimi Sallehudin, Ahmad Firdause Md Fadzil, Rogis Baker


The Ministry of Defence in Malaysia has realized a lot of information technology venturing into the world of healthcare for armed forces. From time to time, the majority of these successful healthcare systems are increasingly aware of the extent and success of its operations. Along with IT growth, there is a need for excellent technical capability as well as integrated, centralized, comprehensive and intensive health information systems for armed forces in Malaysia. However, given the success rate in the application of transverse health information system is very high, it is significant to identify the user adoption factor to increase the success rate. Thus, this paper attempt to identify user adoption factors among the medical and clinical personnel’s which Malaysian Armed Forces Hospital and Clinics should keep in mind, to ensure the success of health record systems’ implementation. In this article, we propose our proposition for the clinician and medical personnel’s adoption model to answer our research problem.


Technology Adoption Model; UTAUT; Electronic Health Record; Health Information System; Malaysia Armed Forces; healthcare personnel


R. Hoque and G. Sorwar, “Understanding factors influencing the adoption of mHealth by the elderly: An extension of the UTAUT model,” Int. J. Med. Inform., vol. 101, pp. 75–84, 2017.

R. E. Bawack and J. R. Kala Kamdjoug, “Adequacy of UTAUT in Clinician Adoption of Health Information Systems in Developing Countries: the Case of Cameroon,” Int. J. Med. Inform., vol. 109, pp. 15–22, 2018.

N. A. Mohamadali, A. N. F. Aziz, and N. A. M. Zahari, “A Novel Conceptual Framework of Health Information Systems (HIS) sustainability,” Res. Innov. Inf. Syst., pp. 1–6, 2017.

M. M. Yusof, J. Kuljis, A. Papazafeiropoulou, and L. K. Stergioulas, “An evaluation framework for Health Information Systems: human, organization and technology-fit factors (HOT-fit),” Int. J. Med. Inform., vol. 77, no. 6, pp. 386–398, 2008.

P. Palvia, K. Lowe, H. Nemati, and T. Jacks, “Information Technology Issues in Healthcare: Hospital CEO and CIO Perspectives,” Commun. Assoc. Inf. Syst., vol. 30, no. 19, pp. 293–312, 2012.

A. Granic and N. Marangunic, “Technology acceptance model : a literature review from 1986 to 2013,” Univers. Access Inf. Soc., vol. 14, no. 1, pp. 81–95, 2015.

F. D. Davis, “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” MIS Q., no. September, 1989.

V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, “User acceptance of information technology: toward a unified view,” MIS Q., vol. 27, no. 3, pp. 425–478, 2003.

I. Hebron, “Technology Acceptance Factors Affecting Adoption of Wireless Data Technology,” 2008.

Y. K. Dwivedi, M. A. Shareef, A. C. Simintiras, B. Lal, and V. Weerakkody, “A generalised adoption model for services: A cross-country comparison of mobile health (m-health),” Gov. Inf. Q., vol. 33, no. 1, pp. 174–187, 2016.

J. Jewer, “Patients’ intention to use online postings of ED wait times: A modified UTAUT model,” Int. J. Med. Informaticsl, vol. 112, pp. 34–39, 2018.

B. Kijsanayotin, S. Pannarunothai, and S. M. Speedie, “Factors influencing health information technology adoption in Thailand’s community health centers: Applying the UTAUT model,” Int. J. Med. Inform., vol. 78, no. 6, pp. 404–416, 2009.

H. Mohammadi, “Investigating users’ perspectives on e-learning: An integration of TAM and IS success model,” Comput. Human Behav., vol. 45, pp. 359–374, 2015.

M. Emmert and M. Wiener, “What factors determine the intention to use hospital report cards? The perspectives of users and non-users,” Patient Educ. Couns., vol. 100, no. 7, pp. 1394–1401, 2017.

V. Venkatesh and F. D. Davis, “A Theoritical Extension of the Technology Acceptance Model: Four Longitudinal Fields Studies,” Manage. Sci., vol. 46, no. 2, pp. 186–204, 2000.

H. Sallehudin, R. C. Razak, and M. Ismail, “Determinants and Impact of Cloud Computing Implementation in the Public Sector,” J. Adv. Inf. Technol., vol. 7, no. May, pp. 245–251, 2016.

D. Compeau and C. Higgins, “Application of social cognitive theory to training for computer skills,” Inf. Syst. Res., vol. 6, no. 2, pp. 118–143, 1995.

W. H. Hung, L. M. Chang, D. C. Yen, C. T. Ho, and M. C. Chiang, “ERP Success in the SMEs: The Perspectives of Service Quality and Social Cognitive Theory.,” Asia Pacific Manag. Rev., vol. 16, no. 4, pp. 503, 2011.

R. . B. Coeurderoy, N. . Guilmot, and A. . Vas, “Explaining factors affecting technological change adoption: A survival analysis of an information system implementation,” Manag. Decis., vol. 52, no. 6, pp. 1082–1100, 2014.

I. Ajzen, “The Theory of Planned Behavior,” Organ. Behav. Hum. Decis. Process, vol. 50, no. 2, pp. 179.211, 1991.

DOI: http://dx.doi.org/10.30630/joiv.3.1.211


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