العوامل المؤثرة على التوجه لاستخدام تقنية بلوكشين في السجلات الصحية بالمملكة العربية السعودية: دراسة حالة المنطقة الشرقية
Factors Affecting Intention to Use Blockchain Technology in Health Records in Saudi Arabia: A Case Study of the Eastern Province
DOI:
https://doi.org/10.7187/GJAT122023-10Keywords:
Blockchain Technology, Health Sector, Health Record, Technology AdoptionAbstract
The study aims to measure the impact of the combined independent factors (technical skill level of users, technical infrastructure, ease of use, security privacy, perceived benefit, and perceived risks) on the trend to use blockchain technology through the study of the attitude towards the use of blockchain technology. This study relies on the quantitative descriptive approach using a questionnaire. The sample population consisted of workers in the health sector in the eastern region of the Kingdom of Saudi Arabia, where the responsive sample amounted to n = 256. Results showed that there is a strong positive correlation at the significance level (α≤0.05) for the combined independent factors on the attitude towards the use of blockchain technology. The results of the model path quality efficiency test indicators also mostly showed ideal values. Thus, we conclude through these indicators that there is a positive impact of the combined independent factors (technical skill level of users, technical infrastructure, ease of use, security privacy, perceived benefit, perceived risks) on the orientation to use blockchain technology at the significance level (α≤0.05). The study recommends the need to continuously develop the technical infrastructure to keep pace with recent and rapid changes in information technology, such as health record systems, based on blockchain technology, which allows easy data sharing between healthcare service organizations and beneficiaries while maintaining the privacy and security of data in providing the best services.
References
Abou-Jaoude, J., & Saade, R. (2017). Blockchain Factors for Consumer Acceptance. The International Journal of Business Management and Technology.
Aldhmour, F., & Sarayrah, I. (2016). AN INVESTIGATION OF FACTORS INFLUENCING CONSUMERS'INTENTION TO USE ONLINE SHOPPING: AN EMPIRICAL STUDY IN SOUTH OF JORDAN. The Journal of Internet Banking and Commerce, 21(2), ---.
Almalki, M., FitzGerald, G., & Clark, M. (2011). Health care system in Saudi Arabia: an overview. EMHJ - Eastern Mediterranean Health Journal, 17(10), 784-793.
Almekhlafi, S., & Al-Shaibany, N. (2021). The Literature Review of Blockchain Adoption. Asian Journal of Research in Computer Science, 29-50.
Alzahrani, S. (2021). Assessment of the Blockchain Technology Adoption for the Management of the Electronic Health Record Systems. Portland State University,
Azaria, A., Ekblaw, A., Vieira, T., et al. (2016). Medrec: Using blockchain for medical data access and permission management. Paper presented at the 2016 2nd international conference on open and big data (OBD).
Bergquist, J. (2017). Blockchain Technology and Smart Contracts: Privacy-Preserving Tools. Uppsala University, DiVA.
Bhatti, A., Saad, S., & Gbadebo, S. (2018). Convenience risk, product risk, and perceived risk influence on online shopping: Moderating effect of attitude. International Journal of Business Management, 3(2), 1-11.
Cernian, A., Tiganoaia, B., Sacala, I., et al. (2020). PatientDataChain: a Blockchain-Based approach to integrate personal health records. Sensors, 20(22), 6538.
Cocco, L., Pinna, A., & Marchesi, M. (2017). Banking on blockchain: Costs savings thanks to the blockchain technology. Future internet, 9(3), 25.
Colby, C., & Parasuraman, A. (2001). Techno-ready marketing: how and why customers adopt technology: Simon and Schuster.
Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems. Cambridge, MA.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
Fatokun, T., Nag, A., & Sharma, S. (2021). Towards a blockchain assisted patient owned system for electronic health records. Electronics, 10(5), 580.
Fattal, A. (2020). Artificial Intelligence and Blockchain within Information Systems. California State University.
Godoe, P., & Johansen, T. (2012). Understanding adoption of new technologies: Technology readiness and technology acceptance as an integrated concept. Journal of European Psychology Students, 3(1).
Hargittai, E. (2005). Survey measures of web-oriented digital literacy. Social science computer review, 23(3), 371-379.
Hasselgren, A., Kralevska, K., Gligoroski, D., et al. (2020). Blockchain in healthcare and health sciences—A scoping review. International Journal of Medical Informatics, 134, 104-040.
Hau, Y., Lee, J., Park, J., et al. (2019). Attitudes toward blockchain technology in managing medical information: Survey study. Journal of medical Internet research, 21(12), e15870.
Hennig‐Thurau, T. (2004). Customer orientation of service employees: Its impact on customer satisfaction, commitment, and retention. International journal of service industry management.
https://www.ledgerinsights.com/blockchain-healthcare-pharma-uae/
https://www.mcit.gov.sa/ar/media-center/news/499305
https://www.mcit.gov.sa/ar/media-center/news/296001
https://www.mcit.gov.sa/ar/media-center/news/95325
https://publicadministration.un.org/en/Research/UN-e-Government-Surveys
https://publicadministration.un.org/egovkb/reports/un-e-government-survey-2018
https://www.stats.gov.sa/ar/1009
Ivan, D. (2016). Moving toward a blockchain-based method for the secure storage of patient records. Paper presented at the ONC/NIST Use of Blockchain for Healthcare and Research Workshop. Gaithersburg, Maryland, United States: ONC/NIST.
Ivanov, S., & Webster, C. (2019). Perceived appropriateness and intention to use service robots in tourism. In Information and communication technologies in tourism 2019 (pp. 237-248): Springer.
Kamble, S., Gunasekaran, A., & Arha, H. (2019). Understanding the Blockchain technology adoption in supply chains-Indian context. International Journal of Production Research, 57(7), 2009-2033.
Kumaraswamy, R., & Manhar, A. (2020). Blockchain Technology in Healthcare Industry. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 6(6), 236-240. Retrieved from https://doi.org/10.32628/CSEIT206645
Marstein, K.-E. (2019). Improve auditing and privacy of electronic health records by using blockchain technology. The University of Bergen,
Masa’deh, R. e. (2013). The impact of information technology infrastructure flexibility on firm performance: An empirical study of Jordanian public shareholding firms. Jordan Journal of Business Administration, 153(954), 1-42.
McConaghy, T., Marques, R., Müller, A., et al. (2016). Bigchaindb: a scalable blockchain database. white paper, BigChainDB. Retrieved from https://git.berlin/bigchaindb/site/raw/commit/b2d98401b65175f0fe0c169932ddca0b98a456a6/_src/whitepaper/bigchaindb-whitepaper.pdf
Miraz, M. H., Hasan, M. T., & Masum, M. H. (2020). FACTORS AFFECTING CONSUMERS INTENTION TO USE BLOCKCHAIN-BASED SERVICES (BBS) IN THE HOTEL INDUSTRY. International Journal of Mechanical and Production, 10, Issue 3, Jun 2020, 8891–8902.
Mokhsin, M., Misron, Z., Hamidi, S., et al. (2011). Measurement of user’s acceptance and perceptions towards campus management system (CMS) using technology acceptance model (TAM). International Journal of Information Processing and Management, 2(4), 34-46.
Mutahar, A., Daud, N., Ramayah, T., et al. (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), 180-204.
Nasir, A., Ali, D., Noordin, M., et al. (2011). Technical skills and non-technical skills: predefinition concept. Paper presented at the Proceedings of the IETEC’11 Conference, Kuala Lumpur, Malaysia.
Oh, J., & Yoon, S.-J. (2014). Validation of haptic enabling technology acceptance model (HE-TAM): Integration of IDT and TAM. Telematics and Informatics, 31(4), 585-596.
Rahman, R., & Alsharqi, O. (2019). What drove the health system reforms in the Kingdom of Saudi Arabia? An analysis. The International journal of health planning and management, 34(1), 100-110.
Rajput, A., Li, Q., & Ahvanooey, M. (2021). A Blockchain-Based Secret-Data Sharing Framework for Personal Health Records in Emergency Condition. Paper presented at the Healthcare.
Ramakrisnan, P., Jaafar, A., & Yatim, N. (2013). Student’s Behavioral Intention to Use Online Discussion Site (ODS) Scale: Investigating Unidimensionality of the Measurement Model. Paper presented at the International Visual Informatics Conference.
Rifi, N., Rachkidi, E., Agoulmine, N., et al. (2017). Towards using blockchain technology for eHealth data access management. Paper presented at the 2017 fourth international conference on advances in biomedical engineering (ICABME).
Rose, J., & Fogarty, G. (2006). Determinants of perceived usefulness and perceived ease of use in the technology acceptance model: senior consumers' adoption of self-service banking technologies. Paper presented at the Proceedings of the 2nd Biennial Conference of the Academy of World Business, Marketing and Management Development: Business Across Borders in the 21st Century.
Shahnaz, A., Qamar, U., & Khalid, A. (2019). Using blockchain for electronic health records. IEEE, 7, 147782-147795.
Siyal, A., Junejo, A., Zawish, M., et al. (2019). Applications of blockchain technology in medicine and healthcare: Challenges and future perspectives. MDPI, 3(1), 3.
Teo, T. (2011). Factors influencing teachers’ intention to use technology: Model development and test. Computers & Education, 57(4), 2432-2440.
Walczuch, R., Lemmink, J., & Streukens, S. (2007). The effect of service employees’ technology readiness on technology acceptance. Information & Management, 44(2), 206-215.
Wang, Y. S., Wang, Y. M., Lin, H. H., et al. (2003). Determinants of user acceptance of Internet banking: an empirical study. International journal of service industry management.
Wiley-Patton, S. (2002). A test of the Extended Technology Acceptance Model for understanding the Internet adoption behavior of physicians. University of Hawaii at Manoa,
Woodside, J., Augustine, F., & Giberson, W. (2017). Blockchain technology adoption status and strategies. Journal of International Technology and Information Management, 26(2), 65-93.
Xiaoren, Z., Xiangdong, C., & Ling, D. (2013). Comparative study of self-service technology adoption based on product function. Information Technology Journal, 12(12), 2350.
Yaeger, K., Martini, M., Rasouli, J., et al. (2019). Emerging blockchain