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Adoption of smart cards in the medical sector: : the Canadian experience

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  • Aubert, Benoit A.
  • Hamel, Geneviève

Abstract

This research evaluates the factors influencing the adoption of smart cards in the medical sector (a smart card has a micro-processor containing information about the patient: identification, emergency data (allergies, blood type, etc.), vaccination, drugs used, and the general medical record). This research was conducted after a pilot study designed to evaluate the use of such smart cards. Two hundred and ninety-nine professionals, along with 7248 clients, used the smart card for a year. The targeted population included mostly elderly people, infants, and pregnant women (the most intensive users of health care services). Following this pilot study, two surveys were conducted, together with numerous interviews, to assess the factors influencing adoption of the technology. A general picture emerged, indicating that although the new card is well-perceived by individuals, tangible benefits must be available to motivate professionals and clients to adopt the technology. Results show that the fundamental dimension that needs to be assessed before massive diffusion is the relative advantage to the professional. The system must provide a direct benefit to its user. The relative advantage of the system for the professional is directly linked to the obligation for the client to use the card. The system is beneficial for the professional only if the information on the card is complete. Technical adequacy is a necessary but not sufficient condition for adoption.

Suggested Citation

  • Aubert, Benoit A. & Hamel, Geneviève, 2001. "Adoption of smart cards in the medical sector: : the Canadian experience," Social Science & Medicine, Elsevier, vol. 53(7), pages 879-894, October.
    • Handle: RePEc:eee:socmed:v:53:y:2001:i:7:p:879-894
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    Cited by:

    1. Prarawan Senachai & Jakaphun Julsrigival & Raksmey Sann, 2022. "Social Marketing Strategy to Promote Traditional Thai Medicines during COVID-19: KAP and DoI Two-Step Theory Application Process," IJERPH, MDPI, vol. 19(14), pages 1-18, July.
    2. Kawaljeet Kaur Kapoor & Yogesh K. Dwivedi & Michael D. Williams, 2015. "Examining the role of three sets of innovation attributes for determining adoption of the interbank mobile payment service," Information Systems Frontiers, Springer, vol. 17(5), pages 1039-1056, October.
    3. Isabelle Piot-Lepetit & Mauro Florez & Karine Gauche, 2019. "Understanding the determinants of IT adoption in agriculture using an integrated TAM-TOE model: A bibliometric analysis," Post-Print hal-02789959, HAL.
    4. Arkesteijn, Karlijn & Oerlemans, Leon, 2005. "The early adoption of green power by Dutch households: An empirical exploration of factors influencing the early adoption of green electricity for domestic purposes," Energy Policy, Elsevier, vol. 33(2), pages 183-196, January.
    5. Simpson, Jesse R. & Mishra, Sabyasachee, 2021. "Developing a methodology to predict the adoption rate of Connected Autonomous Trucks in transportation organizations using peer effects," Research in Transportation Economics, Elsevier, vol. 90(C).

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