PUBLIC ADOPTION OF TELEHEALTH TECHNOLOGY IN THAILAND
Keywords:
TOE, Telehealth, Telemedicine, Technology adoptionAbstract
This study examines key determinants and challenges in the public adoption of telehealth technology in Thailand. It aims to provide managerial implication for Thai healthcare and telecommunication policy makers in designing and planning for the nation-wide adoption of the telehealth technology, in order to remedy long-standing healthcare problems including a medical staff shortage and an inefficient care delivery. In addition, it aims to contribute to the existing telehealth technology adoption literature in the context of rural areas where environmental factors could play a major role in a successful adoption. The TOE was employed as the framework to conduct a qualitative study using an in-depth interview a 12 out of 35 Thai public primary, secondary, tertiary and specialized care centers, participated in the pilot phase of the Telehealth project which was initiated by the National Broadcasting and Telecommunication Commission (NBTC) of Thailand and the Thai Ministry of Public Health (MOPH). Findings reveal that the compatibility with disparate legacy information technology systems, the disagreement over the balance between data privacy and data usage, and the ineffectiveness in the requirement gathering process from key stakeholders are main technological barriers for adoption. Furthermore, organizational factors including the continuous infrastructure and financial supports, the work process redesigning, the digital literacy training, and the motivation schemes for a sustainable adoption are cited to be crucial determinants. Lastly, concerned policy makers need to take into consideration environmental factors including the needs for systematic collaboration among care centers at all levels, the belief in a physical meeting between care providers and receivers, and the regulatory risks related to data privacy and intellectual property rights, for a successful adoption of the telehealth technology nationwide.References
Adelakun, O., & Garcia R. (2019). Technical factors in telemedicine adoption in extreme resource-poor countries. In M., Olivier and C. Croteau-Chonka (Eds.), Global health and volunteering beyond borders (pp. 83-101). Retrieved from https://doi.org/10.1007/978-3-319-98660-9_7
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
Bhatiasevi, V., & Naglis, M. (2018). Elucidating the determinants of business intelligence adoption and organizational performance. Information Development, 36(1), 78-96.
Campbell, J. I., Aturinda, I., Mwesigwa, E., Burns, B., Santorino, D., Haberer, J. E., Bangsberg, D. R., Holden, R. J., Ware, N. C., & Siedner, M. J. (2017). The technology acceptance model for resource-limited settings (TAM-RLS): A novel framework for mobile health interventions targeted to low-literacy end-users in resource-limited settings. AIDS and Behavior, 21(11), 3129-3140.
Carson, D., Gilmore, A., Perry, C., & Gronhaug, K. (2001). Qualitative marketing research. London: Sage
Chiu, C. Y., Chen, S., & Chen, C. L. (2017). An integrated perspective of TOE framework and innovation diffusion in broadband mobile applications adoption by enterprises. International Journal of Management, Economics and Social Sciences (IJMESS), 6(1), 14-39.
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.
Espadanal, M., & Oliveira, T. (2012). Cloud computing adoption by firms. In Mediterranean conference on information systems (MCIS) 2012 Proceedings (pp. 30). Retrieved from https://aisel.aisnet.org/mcis2012/30
Frankfort-Nachmias, C., & Nachmias, D. (1996). Research methods in the social sciences. London: St. Martin’s Press.
Gogia, S. (2020). Rationale, history, and basics of telehealth. In Fundamentals of Telemedicine and Telehealth (pp. 11-34). Retrieved from https://www.scienceopen.com/collection/17895cdc-a87c-42aa-a6d6-f8a385a92b64
Haluza, D., & Jungwirth, D. (2018). ICT and the future of healthcare: Aspects of pervasive health monitoring. Informatics for Health and Social care, 43(1), 1-11.
Hannabuss, S. (1996). Research interviews. New Library World, 97(5), 22-30.
Harst, L., Lantzsch, H., & Scheibe, M. (2019). Theories predicting end-user acceptance of telemedicine use: Systematic review. Journal of Medical Internet Research, 21(5), e13117.
Healy, M., & Perry, C. (2000). Comprehensive criteria to judge validity and reliability of qualitative research within the realism paradigm. Qualitative Market Research: An International Journal, 3(3), 118-126.
Hu, P. J. H., Chau, P. Y. K., & Sheng, O. R. L. (2000). Investigation of factors affecting healthcare organization’s adoption of telemedicine technology. In Proceedings of the 33rd annual Hawaii international conference on system sciences (p. 10). Maui, HI: IEEE.
Kamal, S. A., Shafiq, M., & Kakria, P. (2020). Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM). Technology in Society, 60, 101212
Lin, C. C. C., Dievler, A., Robbins, C., Sripipatana, A., Quinn, M., & Nair, S. (2018). Telehealth in health centers: Key adoption factors, barriers, and opportunities. Health Affairs, 37(12), 1967-1974.
Maarop, N., Win, K. T., Masrom, M., & Hazara Singh, S. S. (2011). Exploring factors that affect teleconsultation adoption. In The case of Malaysia. PACIS 2011: 15th Pacific Asia conference on information systems: Quality research in Pacific (pp. 1-12). Queensland: Queensland University of Technology.
Marques, A., Oliveira, T., Dias, S. S., & Martins, M. F. O. (2011). Medical records system adoption in European hospitals. Journal of Information Systems Evaluation, 14(1), 89.
Ngongo, B. P., Ochola, P., Ndegwa, J., & Katuse, P. (2019). The technological, organizational and environmental determinants of adoption of mobile health applications (m-health) by hospitals in Kenya. PLOS ONE, 14(12), 1-25.
Patton, M. Q. (1990). Qualitative evaluation and research methods (2nd ed.). Newbury Park, CA: Sage.
Peeters, J. M., de Veer, A. J. E., van der Hoek, L., & Francke, A. L. (2012). Factors influencing the adoption of home telecare by elderly or chronically ill people: A national survey. Journal of Clinical Nursing, 21(21-22), 3183-3193.
Ramayah, T., Mohamad, O., Omar, A., Marimuthu, M., & Leen, J. Y. A. (2013). Determinants of technology adoption among Malaysian SMES: An IDT perspective. Journal of Information and Communication Technology, 12(1), 103-119.
Rao, S., & Perry, C. (2003). Convergent interviewing to build a theory in under-researched areas: Principles and an example investigation of Internet usage in inter-firm relationships. Qualitative Market Research: An International Journal, 6(4), 236-247.
Redfern, J. (2017). Smart health and innovation: Facilitating health-related behaviour change. Proceedings of the Nutrition Society, 76(3), 328-332.
Rogers, E. M. (2003). Diffusion of innovations. New York: Free Press.
Sanders, C., Rogers, A., Bowen, R., Bower, P., Hirani, S., Cartwright, M., Fitzpatrick, R., Knapp, M., Barlow, J., Hendy, J., Chrysanthaki, T., Bardsley, M., & Newman, S. P. (2012). Exploring barriers to participation and adoption of telehealth and telecare within the whole system demonstrator trial: A qualitative study. BMC Health Services Research, 12(1), 1-12.
Sisk, B., Alexander, J., Bodnar, C., Curfman, A., Garber, K., McSwain, S. D., & Perrin, J. M. (2020). Pediatrician attitudes toward and experiences with telehealth use: Results from a national survey. Academic Pediatrics, 20(5), 628-635.
Sulaiman, H., & Magaireah, A. I. (2014). Factors affecting the adoption of integrated cloud based e-health record in healthcare organizations: A case study of Jordan. In Proceedings of the 6th international conference on information technology and multimedia (pp. 102-107). Retrieved from https://doi.org/10.1109/ICIMU.2014.7066612
Taylor, J., Coates, E., Wessels, B., Mountain, G., & Hawley, M. S. (2015). Implementing solutions to improve and expand telehealth adoption: Participatory action research in four community healthcare settings. BMC Health Services Research, 15(529). https://doi.org/10.1186/s12913-015-1195-3
Tornatzky, L. G., Fleischer, M., & Chakrabarti, A. K. (1990). Processes of technological innovation. KY: Lexington Books.
Tortorella, G. L., Fogliatto, F. S., Mac Cawley Vergara, A., Vassolo, R., & Sawhney, R. (2019). Healthcare 4.0: Trends, challenges and research directions. Production Planning & Control, 31(15), 1245-1260.
Tsai, J. M., Cheng, M. J., Tsai, H. H., Hung, S.W., & Chen, Y. L. (2019). Acceptance and resistance of telehealth: The perspective of dual-factor concepts in technology adoption. International Journal of Information Management, 49, 34-44.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
Vuononvirta, T., Timonen, M., KeinänenKiukaanniemi, S., Timonen, O., Ylitalo, K., Kanste, O., & Taanila, A. (2011). The compatibility of telehealth with health-care delivery. Journal of Telemedicine and Telecare, 17(4), 190-194.
Walsham, G. (1995). Interpretive case studies in IS research: Nature and method. European Journal of Information Systems, 4(2), 74-81.
Wong, L. W., Leong, L. Y., Hew, J. J., Tan, G.W. H., & Ooi, K. B. (2019). Time to seize the digital evolution: Adoption of block chain in operations and supply chain management among Malaysian SMEs. International Journal of Information Management, 52, 101997.
Yin, R. K. (1989). Case study research: Design and Methods. London: Sage.