Investigating the Adoption of Telemedicine Services: An Empirical Study of Factors Influencing Physicians’ Perspective in Pakistan

S. A Kamal, S. Hussain, M. Shafiq, M. Jahanzaib



Telemedicine services are increasingly becoming an integral part of health care system of many countries around the globe. However, despite its emergent proliferation its acceptance hasn’t been strikingly popular in clinical settings of developing countries, where shortage of practicing medical professionals is prevalent. The objective of this research study is to develop a theoretical model based on Technology Acceptance Model (TAM) and then empirically testing it for determining the key factors influencing doctors’ intention to adopt and use Telemedicine Services in clinical settings of a developing country. The partial least square model obtained from data of 220 doctors reflects that Perceived Usefulness (β = 0.30) and Perceived Ease of Use (β = 0.26), are the most significant drivers for doctors to use Telemedicine services in their practice, confirming the validity of original TAM constructs. In addition, new predictive constructs including Legal and Ethical Concerns ((β = -0.23) and Response Cost (β = -0.15) are found to have significant negative effects on usage intention of doctors. The survey findings reflect that telemedicine services are still in its infancy in Pakistan. Rigorous awareness and training programs are required to increase its acceptance among medical professionals. Effective financial and legal solutions also need to be devised leading physicians to uptake the adoption of telemedicine service.

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Adenuga, K.I., N.A. Iahad, and S. Miskon, Towards Reinforcing Telemedicine Adoption amongst Clinicians in Nigeria. International Journal of Medical Informatics, 2017.

Esmaeilzadeh, P., M. Sambasivan, and N. Kumar, The challenges and issues regarding e-health and health information technology trends in the healthcare sector, in E-business Technology and Strategy. 2010, Springer. p. 23-37.

Dasgupta, A. and S. Deb, Telemedicine: A new horizon in public health in India. Indian journal of community medicine: official publication of Indian Association of Preventive & Social Medicine, 2008. 33(1): p. 3.

Farhan Khan, M., F.S. Chaudhary, and M.N. Yousaf, Role of Telemedicine in Developed and Under-Developed Countries. Newsletter, 2016. 2016.

Ullah, N., et al., A Telemedicine Network Model for Health Applications in Pakistan-Current Status and Future Prospects. JDCTA, 2009. 3(3): p. 149-155.

Wootton, R., Recent advances-telemedicine. British Medical Journal, 2001. 323(7312): p. 557-560.

Hoque, R. and G. Sorwar, Understanding factors influencing the adoption of mHealth by the elderly: An extension of the UTAUT model. International Journal of Medical Informatics, 2017. 101: p. 75-84.

Gao, P. and A. Rafiq, The transformation of the mobile telecommunications industry in Pakistan: A developing country perspective. Telecommunications Policy, 2009. 33(5): p. 309-323.

Jameel, A., et al., Factors affecting Broadband proliferation in Pakistan and initiatives/measures taken by the Government of Pakistan. Procedia Technology, 2012. 1: p. 250-257.

Imtiaz, S.Y., M.A. Khan, and M. Shakir, Telecom sector of Pakistan: Potential, challenges and business opportunities. Telematics and Informatics, 2015. 32(2): p. 254-258.

Kurji, Z., Z.S. Premani, and Y. Mithani, ANALYSIS OF THE HEALTH CARE SYSTEM OF PAKISTAN: LESSONS LEARNT AND WAY FORWARD. Journal of Ayub Medical College Abbottabad, 2016. 28(3): p. 601-604.

Kim, H.-W. and A. Kankanhalli, Investigating user resistance to information systems implementation: A status quo bias perspective. MIS quarterly, 2009: p. 567-582.

Ahmed, J. and B.T. Shaikh, An all time low budget for healthcare in Pakistan. Journal of the College of Physicians and Surgeons Pakistan, 2008. 18(6): p. 388.

Hsieh, R.K., et al., Telemedicine in China. International Journal of Medical Informatics, 2001. 61(2): p. 139-146.

Lowery, C.L., et al., Distributing medical expertise: the evolution and impact of telemedicine in arkansas. Health Affairs, 2014. 33(2): p. 235-243.

Berg, M., Patient care information systems and health care work: a sociotechnical approach. International journal of medical informatics, 1999. 55(2): p. 87-101.

Broens, T.H., et al., Determinants of successful telemedicine implementations: a literature study. Journal of telemedicine and telecare, 2007. 13(6): p. 303-309.

Obstfelder, A., K.H. Engeseth, and R. Wynn, Characteristics of successfully implemented telemedical applications. Implementation Science, 2007. 2(1): p. 25.

Wootton, R., Telemedicine support for the developing world. Journal of telemedicine and telecare, 2008. 14(3): p. 109-114.

Rho, M.J., I. young Choi, and J. Lee, Predictive factors of telemedicine service acceptance and behavioral intention of physicians. International journal of medical informatics, 2014. 83(8): p. 559-571.

Chismar, W.G. and S. Wiley-Patton. Test of the technology acceptance model for the internet in pediatrics. in Proceedings of the AMIA Symposium. 2002. American Medical Informatics Association.

Schaper, L.K. and G.P. Pervan, ICT and OTs: A model of information and communication technology acceptance and utilisation by occupational therapists. International journal of medical informatics, 2007. 76: p. S212-S221.

Chau, P.Y. and P.J.-H. Hu, Investigating healthcare professionals decisions to accept telemedicine technology: an empirical test of competing theories. Information & management, 2002. 39(4): p. 297-311.

Yarbrough, A.K. and T.B. Smith, Technology acceptance among physicians: a new take on TAM. Medical Care Research and Review, 2007. 64(6): p. 650-672.

Yu, P., H. Li, and M.-P. Gagnon, Health IT acceptance factors in long-term care facilities: a cross-sectional survey. International journal of medical informatics, 2009. 78(4): p. 219-229.

Aggelidis, V.P. and P.D. Chatzoglou, Using a modified technology acceptance model in hospitals. International journal of medical informatics, 2009. 78(2): p. 115-126.

Venkatesh, V. and F.D. Davis, A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 2000. 46(2): p. 186-204.

Mun, Y.Y., et al., Understanding information technology acceptance by individual professionals: Toward an integrative view. Information & Management, 2006. 43(3): p. 350-363.

Davis, F.D., Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 1989: p. 319-340.

Melas, C.D., et al., Modeling the acceptance of clinical information systems among hospital medical staff: an extended TAM model. Journal of biomedical informatics, 2011. 44(4): p. 553-564.

King, W.R. and J. He, A meta-analysis of the technology acceptance model. Information & management, 2006. 43(6): p. 740-755.

Teo, T., Examining the influence of subjective norm and facilitating conditions on the intention to use technology among pre-service teachers: a structural equation modeling of an extended technology acceptance model. Asia Pacific Education Review, 2010. 11(2): p. 253-262.

Davis, F.D., R.P. Bagozzi, and P.R. Warshaw, User acceptance of computer technology: a comparison of two theoretical models. Management science, 1989. 35(8): p. 982-1003.

Legris, P., J. Ingham, and P. Collerette, Why do people use information technology? A critical review of the technology acceptance model. Information & management, 2003. 40(3): p. 191-204.

Whitten, P., G. Doolittle, and M. Mackert, Providers' acceptance of telehospice. Journal of palliative medicine, 2005. 8(4): p. 730-735.

Chen, R.-F. and J.-L. Hsiao, An investigation on physicians acceptance of hospital information systems: a case study. International journal of medical informatics, 2012. 81(12): p. 810-820.

Dnnebeil, S., et al., Determinants of physicians technology acceptance for e-health in ambulatory care. International journal of medical informatics, 2012. 81(11): p. 746-760.

Wu, J.-H., Y.-C. Chen, and L.-M. Lin, Empirical evaluation of the revised end user computing acceptance model. Computers in Human Behavior, 2007. 23(1): p. 162-174.

Lanseng, E.J. and T.W. Andreassen, Electronic healthcare: a study of people's readiness and attitude toward performing self-diagnosis. International Journal of Service Industry Management, 2007. 18(4): p. 394-417.

Shih, Y.-Y., The effect of computer self-efficacy on enterprise resource planning usage. Behaviour & Information Technology, 2006. 25(5): p. 407-411.

Venkatesh, V., et al., User acceptance of information technology: Toward a unified view. MIS quarterly, 2003: p. 425-478.

Sandberg, J., et al., A qualitative study of the experiences and satisfaction of direct telemedicine providers in diabetes case management. Telemedicine and e-Health, 2009. 15(8): p. 742-750.

Lederer, A.L., et al., The technology acceptance model and the World Wide Web. Decision support systems, 2000. 29(3): p. 269-282.

Hung, S.-Y., Y.-C. Ku, and J.-C. Chien, Understanding physicians acceptance of the Medline system for practicing evidence-based medicine: A decomposed TPB model. International journal of medical informatics, 2012. 81(2): p. 130-142.

Egea, J.M.O. and M.V.R. Gonzlez, Explaining physicians acceptance of EHCR systems: an extension of TAM with trust and risk factors. Computers in Human Behavior, 2011. 27(1): p. 319-332.

Mohd, H. and S.M. Syed Mohamad, Acceptance model of electronic medical record. Journal of Advancing Information and Management Studies, 2005. 2(1): p. 75-92.

Holden, R.J. and B.-T. Karsh, The technology acceptance model: its past and its future in health care. Journal of biomedical informatics, 2010. 43(1): p. 159-172.

Schepers, J. and M. Wetzels, A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information & management, 2007. 44(1): p. 90-103.

Milne, S., S. Orbell, and P. Sheeran, Combining motivational and volitional interventions to promote exercise participation: Protection motivation theory and implementation intentions. British journal of health psychology, 2002. 7(2): p. 163-184.

Oosterlaan, J. and J.A. Sergeant, Effects of reward and response cost on response inhibition in AD/HD, disruptive, anxious, and normal children. Journal of Abnormal Child Psychology, 1998. 26(3): p. 161-174.

Hillestad, R., et al., Can electronic medical record systems transform health care? Potential health benefits, savings, and costs. Health affairs, 2005. 24(5): p. 1103-1117.

Brown, I. and A.A. Adams, The ethical challenges of ubiquitous healthcare. International Review of Information Ethics, 2007. 8(12): p. 53-60.

Dickens, B. and R.J. Cook, Legal and ethical issues in telemedicine and robotics. International Journal of Gynecology & Obstetrics, 2006. 94(1): p. 73-78.

Whitman, M.E. and H.J. Mattord, Principles of information security. 2011: Cengage Learning.

Olver, I.N. and S. Selva-Nayagam, Evaluation of a telemedicine link between Darwin and Adelaide to facilitate cancer management. Telemedicine Journal, 2000. 6(2): p. 213-218.

Venkatesh, V., S.A. Brown, and H. Bala, Bridging the qualitative-quantitative divide: Guidelines for conducting mixed methods research in information systems. MIS quarterly, 2013. 37(1).

Shibl, R., M. Lawley, and J. Debuse, Factors influencing decision support system acceptance. Decision Support Systems, 2013. 54(2): p. 953-961.

Kohnke, A., M.L. Cole, and R. Bush, Incorporating UTAUT predictors for understanding home care patients' and clinician's acceptance of healthcare telemedicine equipment. Journal of technology management & innovation, 2014. 9(2): p. 29-41.

Hossain, M.M. and V.R. Prybutok, Consumer acceptance of RFID technology: An exploratory study. IEEE transactions on engineering management, 2008. 55(2): p. 316-328.

Foon, Y.S. and B.C.Y. Fah, Internet banking adoption in Kuala Lumpur: an application of UTAUT model. International Journal of Business and Management, 2011. 6(4): p. 161.

Cortina, J.M., What is coefficient alpha? An examination of theory and applications. Journal of applied psychology, 1993.


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