Document Type : Review Article

Authors

1 Department of Health Information Technology, Health Human Resources Research Center, School of Management & Information Sciences, Shiraz University of Medical Sciences, Shiraz, Iran

2 Department of Health Information Technology, Lorestan University of Medical Sciences, Khorramabad, Iran

3 Health Policy Research Center, Shiraz University of Medical Sciences, Shiraz, Iran

Abstract

Background: Mobile health is one of the new technologies for the utilization of health information. For its successful implementation as well as any other system, we must primarily measure the adoption and use of its factors. The purpose of this study was to systematically investigate published articles about the factors affecting the adoption of mobile health and categorizing the factors affecting the adoption of this system.Methods: This study is a comprehensive review done by searching major databases such as Google Scholar, Emerald, Science Direct, Iran Medex, SID, Magiran, Pub med, etc. In addition, we use Mobile, mobile Health + adoption, mobile Health + TAM, Health + TAM keywords in the range of 2004 to 2015.Results: Among the studies that use information technology theories to survey the factors affecting the adoption of mobile health, TAM model was used more than other models. Factors such as perceived ease of use, perceived usefulness and facilitating condition form TUATU are the most effective in the adoption of mobile health.Conclusion:  Results showed that by considering factors such as perceived ease of use, perceived usefulness and facilitating condition can increase the adoption of mobile health system. Consequently, these factors are recommended to be considered in planning to run systems.

Keywords

  1. Ozdalga E, Ozdalga A, Ahuja N. The smartphone in medicine: a review of current and potential use among physicians and students. J Med Internet Res. 2012;14:e128. doi.org/10.2196/jmir.1994. PubMed PMID: 23017375. PubMed PMCID: 3510747.
  2. Alexandrou A, Chen LC. The Security Risk Perception Model for the Adoption of Mobile Devices in the Healthcare Industry.
  3. Bandyopadhyay T, Zadeh B. Acceptance of Mobile Health Technology in the Value Chain [Research-in-Progress]. 2014.
  4. Cocosila M. Role of user a priori attitude in the acceptance of mobile health: an empirical investigation. Electronic Markets. 2013;23:15-27. doi.org/10.1007/s12525-012-0111-5.
  5. Deng Z, Mo X, Liu S. Comparison of the middle-aged and older users’ adoption of mobile health services in China. Int J Med Inform. 2014;83:210-24. doi.org/10.1016/j.ijmedinf.2013.12.002. PubMed PMID: 24388129.
  6. Garavand A. The role of Mobile health in Facilitate providing Health services. Shiraz International Mobile Health Seminar (SIM Seminar). 17-18 May, Shiraz University of Medical Sciences; 2015.
  7. El-Wajeeh M, Galal-Edeen GH, Mokhtar H. Technology Acceptance Model for Mobile Health Systems.
  8. Leon SA, Fontelo P, Green L, Ackerman M, Liu F. Evidence-based medicine among internal medicine residents in a community hospital program using smart phones. BMC Med Inform Decis Mak. 2007;7:5. doi.org/10.1186/1472-6947-7-5. PubMed PMID: 17313680. PubMed PMCID: 1805745.
  9. Gilbert M, Namagembe F, editors. Understanding user adoption of mobile health technology in a resource constrained environment. Information Science, Computing and Telecommunications (PACT), 2013 Pan African International Conference on; 2013: IEEE. doi: 10.1109/scat.2013.7055089*.
  10. Johnson T, Vergara J, Doll C, Kramer M, Sundararaman G, Rajendran H, et al. A Mobile Food Recommendation System Based on The Traffic Light Diet. arXiv preprint arXiv:1409.0296. 2014.
  11. Garavand A. The role of Mobile Health in reducing hospital costs. Shiraz International Mobile Health Seminar (SIM Seminar). 17-18 May, Shiraz University of Medical Sciences; 2015.
  12. Lin S-P. Determinants of adoption of mobile healthcare service. International Journal of Mobile Communications. 2011;9:298-315. doi.org/10.1504/IJMC.2011.040608.
  13. Rho MJ, Kim HS, Chung K, Choi IY. Factors influencing the acceptance of telemedicine for diabetes management. Cluster Computing. 2015;18:321-31. doi.org/10.1007/s10586-014-0356-1.
  14. Khalifa M. Barriers to health information systems and electronic medical records implementation. A field study of Saudi Arabian hospitals. Procedia Computer Science. 2013;21:335-42. doi.org/10.1016/j.procs.2013.09.044.
  15. Rho MJ, Choi IY, Lee J. Predictive factors of telemedicine service acceptance and behavioral intention of physicians. Int J Med Inform. 2014;83:559-71. doi.org/10.1016/j.ijmedinf.2014.05.005. PubMed PMID: 24961820.
  16. Kijsanayotin B, Pannarunothai S, Speedie SM. Factors influencing health information technology adoption in Thailand’s community health centers: applying the UTAUT model. Int J Med Inform. 2009;78:404-16. doi.org/10.1016/j.ijmedinf.2008.12.005. PubMed PMID: 19196548.
  17. Sun Y, Wang N, Guo X, Peng Z. Understanding the acceptance of mobile health services: a comparison and integration of alternative models. Journal of Electronic Commerce Research. 2013;14:183.
  18. Vogel D, Viehland D, Wickramasinghe N, Mula JM. Mobile health. Electronic Markets. 2013;23:3. doi.org/10.1007/s12525-013-0121-y.
  19. Chang MK, Cheung W. Determinants of the intention to use Internet/WWW at work: a confirmatory study. Information & Management. 2001;39:1-14. doi.org/10.1016/S0378-7206(01)00075-1.
  20. Xi-tong G, Jin-qiao Y, Xiong-fei C, Xiao-dong C, editors. Understanding the acceptance of mobile health services: A service participants analysis. Management Science and Engineering (ICMSE), 2012 International Conference on; 2012: IEEE.
  21. Holden RJ, Karsh BT. The technology acceptance model: its past and its future in health care. J Biomed Inform. 2010;43:159-72. doi.org/10.1016/j.jbi.2009.07.002.
  22. Zhang X, Guo X, Lai KH, Guo F, Li C. Understanding gender differences in m-health adoption: a modified theory of reasoned action model. Telemed J E Health. 2014;20:39-46. doi.org/10.1089/tmj.2013.0092. PubMed PMID: 24161004.
  23. Phua J, Lim TK. How residents and interns utilise and perceive the personal digital assistant and UpToDate. BMC Med Educ. 2008;8:39. doi.org/10.1186/1472-6920-8-39. PubMed PMID: 18625038. PubMed PMCID: 2483706.
  24. Rogers EM. Diffusion of Innovations: modifications of a model for telecommunications. Die Diffusion von Innovationen in der Telekommunikation: Springer; 1995. p. 25-38.
  25. kahooei M, Babamohamadi H. Factors influencing the adoption of information technology in clinical nurses. Journal of Faculty of Tehran University of Medical Sciences (Pyavrd salamat). 2013;4:262-77. [In Persian]
  26. Chau PY, Hu PJH. Information technology acceptance by individual professionals: A model comparison approach. Decision sciences. 2001;32:699-719. doi.org/10.1111/j.1540-5915.2001.tb00978.x.
  27. Putzer GJ. Are physicians likely to adopt emerging mobile technologies? Attitudes and innovation factors affecting smartphone use in the Southeastern United States. Perspectives in Health Information Management. 2012;9:1. PubMed PMID: 22737094; PubMed Central PMCID: PMC3329206.
  28. Mekić E, Özlen MK. Acceptance of Smartphones by Users in BiH Through Extended Technology Acceptance Model. International multidisciplinary journal. 2014:136-49.
  29. Aggelidis VP, Chatzoglou PD. Using a modified technology acceptance model in hospitals. Int J Med Inform. 2009;78:115-26. doi.org/10.1016/j.ijmedinf.2008.06.006. PubMed PMID: 18675583.
  30. Mohd H, Syed Mohamad SM. Acceptance model of electronic medical record. Journal of Advancing Information and Management Studies. 2005;2:75-92.
  31. Bleich HL, Slack WV. Reflections on electronic medical records: when doctors will use them and when they will not. Int J Med Inform. 2010;79:1-4. doi.org/10.1016/j.ijmedinf.2009.10.002. PubMed PMID: 19939731.
  32. Wills MJ, El-Gayar O, Bennett D. Examining healthcare professionals’ acceptance of electronic medical records using UTAUT. Issues in Information Systems. 2008;9:396-401.
  33. Garavand A, Ghanbari S, Ebrahimi S, Kafashi M, Ahmadzadeh F. The effective factors in adopting picture archiving and communication system in Shiraz educational hospitals based on technology acceptance Model. Journal of Health and Biomedical Informatics. 2015;1:76-82.
  34. Tavakoli N, Jahanbakhsh M, Shahin A, Mokhtari H, Rafiei M. Electronic medical record in central polyclinic of isfahan oil industry: a case study based on technology acceptance model. Acta Inform Med. 2013;21:23-5. doi.org/10.5455/aim.2012.21.23-25. PubMed PMID: 23572857. PubMed PMCID: 3610586.
  35. Abdekhoda M, Ahmadi M, Gohari M, Noruzi A. The effects of organizational contextual factors on physicians’ attitude toward adoption of Electronic Medical Records. J Biomed Inform. 2015;53:174-9. doi.org/10.1016/j.jbi.2014.10.008. PubMed PMID: 25445481.
  36. Holtz B, Krein S. Understanding nurse perceptions of a newly implemented electronic medical record system. Journal of Technology in Human Services. 2011;29:247-62. doi.org/10.1080/15228835.2011.639931.
  37. Nematollahi M, Garavand A, Monem H. Factors Affecting the Intention to Use Electronic Medical Records from the Perspective of Top and Middle Managers of Shiraz Teaching Hospitals. Journal of Health and Biomedical Informatics. 2015;2:1-7.