Abstract
User acceptance has been considered a crucial issue that should be present and understand before implementing any software product. Electronic personalized health records (e-PHR) has been developed and implemented in many countries around the worlds. However, it is essential to understand the existing factors that influence them to accept or reject this technology. While describing the user acceptance of any technology is always related to the current information system (IS), literature to measure the acceptance level simultaneously determine whether the technology will be accepted. This study presents the existing and current factors that influence user acceptance of e-PHR in various country. A comprehensive literature review has been performed to obtain the factors with the user acceptance theory (UAT) implemented from the existing studies. The systematic searching of all articles related to the literature review and evaluation of user acceptance towards ePHR has been done through several keywords utilizing in the main database ScienceDirect, IEEE Xplore, Web of Science, and other scholar articles several years. This study presents the existing and current factors that influence user acceptance of e-PHR in various country. Based on the searching result, around 144 articles related to this literature have been found. However, it is approximately 50 articles been filtered out with exclusion criteria to the related literature for this study. From this 50, it is 18 articles been selected after exclusion criteria that closest to the related literature for this study have been shown in Table 2. As a result, there are 55 factors that has been found which specifically related to e-PHR user acceptance. Several factors have been found from the existing studies that influence the user to accept or reject this technology from patients, physicians, and organization perspectives. These systematic user acceptance factors will contribute to emphasize the current research opportunities and extend the research fields.
Similar content being viewed by others
References
Doheir M, Hussin B, Samad A et al (2018) Identifying critical cloud computing technology issues for improving healthcare management. Jour of Adv Research in Dynamical & Control Systems 10(7):732–743
Vimala G, Omar SZ (2016) Implementation on ICT knowledge development in healthcare
Hameed MA, Counsell S, Swift S (2012) A conceptual model for the process of IT innovation adoption in organizations. Journal of Engineering and Technology Management 29:358–390. https://doi.org/10.1016/j.jengtecman.2012.03.007
Taherdoost H (2018) A review of technology acceptance and adoption models and theories. Procedia manufacturing 22:960–967. https://doi.org/10.1016/j.promfg.2018.03.137
Yaacob NM, Basari ASH, Salahuddin L, Ghani MK (2018a) A review on user acceptance of electronic personalized health records [e-PHR]. Jour of Adv Research in Dynamical & Control Systems 10:686–706
Greenberg AJ, Falisi AL, Finney Rutten LJ, Chou WYS, Patel V, Moser RP, Hesse BW (2017) Access to electronic personal health records among patients with multiple chronic conditions: a secondary data analysis. J Med Internet Res 19:e188. https://doi.org/10.2196/jmir.7417
Yang H, Lee H, Zo H (2017) User acceptance of smart home services: an extension of the theory of planned behavior. Ind Manag Data Syst 117:68–89. https://doi.org/10.1108/IMDS-01-2016-0017
Yaacob NM, Shibghatullah AS, Ghani MK, Salahuddin L (2018b) A review on electronic personalized health records. J Telecommun Electron Comput Eng 10:77–81
Liu CF, Tsai YC, Jang FL (2013) Patients’ acceptance towards a web-based personal health record system: an empirical study in Taiwan. Int J Environ Res Public Health 10:5191–5208. https://doi.org/10.3390/ijerph10105191
Yaacob NM, Ghani MKA, Basari ASH (2013) A Framework for accessing patient health records through multi channel of devices. In: e-Proceeding of Software Engineering Postgraduates Workshop (SEPoW). p 31
Yaacob NM, Basari ASH, Salahuddin L, Abd Ghani MK, Shibghatullah AS (2017) A review on electronic health records. Journal of Advanced Research in Dynamical and Control System 9(10):27–34
Yaacob NM, Samad A, Basari H et al (2017b) A review on pervasive health records. Jour of Adv Research in Dynamical & Control Systems 9:35–42
Jokonya O (2016) Validating technology acceptance model (TAM) during IT adoption in organizations. Proc - IEEE 7th Int Conf Cloud Comput Technol Sci Cloud Com 2015:509–516. https://doi.org/10.1109/CloudCom.2015.56
Kiwanuka A (2015) (PDF) Acceptance process: the missing link between UTAUT and diffusion of innovation theory. Am J Inf Syst. https://doi.org/10.12691/ajis-3-2-3
Al-Mamary YH, Al-nashmi M, Hassan YAG, Shamsuddin A (2016) A critical review of models and theories in field of individual acceptance of technology. Int J Hybrid Inf Technol 9:143–158. https://doi.org/10.14257/ijhit.2016.9.6.13
Ozok AA, Wu H, Garrido M et al (2014) Usability and perceived usefulness of personal health records for preventive health care : a case study focusing on patients ’ and primary care providers ’ perspectives. Appl Ergon 45:613–628. https://doi.org/10.1016/j.apergo.2013.09.005
Agrawal E (2010) Acceptance and use of personal health record: factors affecting physicians’ perspective. Indiana Univ December:113
Or CKLL, Karsh BT, Severtson DJ et al (2011) Factors affecting home care patients’ acceptance of a web-based interactive self-management technology. J Am Med Inform Assoc 18:51–59. https://doi.org/10.1136/jamia.2010.007336
Nambisan P (2017) Factors that impact Patient Web Portal Readiness (PWPR) among the underserved. Int J Med Inform 102:62–70. https://doi.org/10.1016/j.ijmedinf.2017.03.004
Zhang X, Yu P, Yan J, Ton SI (2015) Using diffusion of innovation theory to understand the factors impacting patient acceptance and use of consumer e-health innovations: a case study in a primary care clinic. BMC Health Serv Res 15:71. https://doi.org/10.1186/s12913-015-0726-2
Miller DM, Moore SM, Fox RJ, Atreja A, Fu AZ, Lee JC, Saupe W, Stadtler M, Chakraborty S, Harris CM, Rudick RA (2011) Web-based self-management for patients with multiple sclerosis: a practical, randomized trial. Telemed J E Health 17:5–13. https://doi.org/10.1089/tmj.2010.0133
Williamson RS, Cherven BO, Gilleland Marchak J et al (2017) Meaningful use of an electronic personal health record (ePHR) among pediatric cancer survivors. Appl Clin Inform 8:250–264. https://doi.org/10.4338/ACI-2016-11-RA-0189
Lamsaard J, Pongthananikorn S, Theeraroungchaisri A (2016) Development of a chronic kidney disease knowledge website with electronic personal health records for patients. Thai J Pharm Sci 40:159–162
Ro HJ, Jung SY, Lee K, Hwang H, Yoo S, Baek H, Lee K, Bae WK, Han JS, Kim S, Park H (2015) Establishing a personal health record system in an academic hospital: one year’s experience. Korean J Fam Med 36(3):121
Gartrell K, Trinkoff AM, Storr CL, Wilson ML, Gurses AP (2015) Testing the electronic personal health record acceptance model by nurses for managing their own health. Appl Clin Inform 6:224–247. https://doi.org/10.4338/ACI-2014-11-RA-0107
Richards RJ (2013) A study of the intent to fully utilize electronic personal health records in the context of privacy and trust. University of North Texas. 74:No-Specified
Morton AA (2011) Examining acceptance of an integrated personal health record (PHR). University of Maryland, Baltimore
Burkhard RJ, Schooley B, Dawson J, Horan TA (2010) Information systems and healthcare XXXVII: When your employer provides your personal health record-exploring employee perceptions of an employer-sponsored PHR system. Commun Assoc Inf Syst 27:323–338
Feistel G (2014) Technology acceptance model: factors influencing consumers’ intent to use Electronic Personal Health Records. Central Michigan University, p 166
Razmak J, Bélanger C (2018) Using the technology acceptance model to predict patient attitude toward personal health records in regional communities. Inf Technol People 31:306–326. https://doi.org/10.1108/ITP-07-2016-0160
Montero-Marín J, Prado-Abril J, Botella C, Mayoral-Cleries F, Baños R, Herrera-Mercadal P, Romero-Sanchiz P, Gili M, Castro A, Nogueira R, García-Campayo J (2015) Expectations among patients and health professionals regarding web-based interventions for depression in primary care: a qualitative study. J Med Internet Res 17:e67. https://doi.org/10.2196/jmir.3985
Dutta B, Peng MH, Sun SL (2018) Modeling the adoption of personal health record (PHR) among individual: the effect of health-care technology self-efficacy and gender concern. Libyan J Med 13:1500349. https://doi.org/10.1080/19932820.2018.1500349
Acknowledgements
The authors would like to thank Universiti Teknikal Malaysia Melaka (UTeM) for their support.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare no competing interests.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Yaacob, N.M., Basari, A.S.H., Ghani, M.K.A. et al. Factors and theoretical framework that influence user acceptance for electronic personalized health records. Pers Ubiquit Comput 28, 29–41 (2024). https://doi.org/10.1007/s00779-021-01563-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00779-021-01563-y