Abstract
This chapter presents a systematic mapping of studies that investigated the adoption of IoT-based healthcare services in developing countries. Specifically, this chapter investigates the current drivers and challenges of the adoption of IoT-based healthcare services in developing countries. It further investigates technology acceptance models/theories that have been used in IoT-based healthcare research in developing countries. The chapter suggests that there is a need to undertake more studies on IoT-based healthcare services in developing countries that are anchored on a theoretical foundation to enhance the understanding of the drivers and inhibitors of the adoption of such services. Such understanding will help devise strategies that could stimulate the adoption and use of IoT-based healthcare services in developing countries.
TopIntroduction And Background
Internet of Things (IoT) is one of the main enablers of the Fourth Industrial Revolution (4IR). IoT offers new opportunities that combine mental, physical and mechanical work (Bloem et al., 2014; Kante, 2020). Medical care and health care are some of the most attractive applications of IoTs (Islam, Kwak, Kabir, Hossain, & Kwak, 2015; Kante & Ndayizigamiye, 2020) as there are various applications of IoTs in the context of healthcare. For instance, mHealth, one of IoTs applications, has been hailed for its potential for supporting personalized healthcare such as remote monitoring of patients (Ndayizigamiye & Matlala, 2018; Ndayizigamiye & Maharaj, 2016), self-healthcare monitoring (Soni, Ndayizigamiye, Kanté, 2019); and public healthcare (Ndayizigamiye, Hangulu, & Akintola, 2017; Matiyabu, Ndayizigamiye, & Maharaj, 2017).
However, the design of ICT-based interventions for development purposes including IoTs must take into consideration the context in which they are deployed (Whitmore, Agarwal, & Da Xu, 2015; Ndayizigamiye, 2016; Ndayizigamiye & Maharaj, 2016; Ndayizigamiye, Soni & Jere, 2018; Matiyabu & Ndayizigamiye, 2019; Ndayizigamiye & Dube, 2019). Particularly, as developing countries are embracing the 4IR, there is a need to be aware of the current challenges and enablers of the adoption of IoT- based healthcare services in such settings. Such awareness will assist in devising IoT-based healthcare interventions tailored to the settings in which they are applied.
This chapter presents a systematic mapping of studies of the adoption of Internet of Things to provide healthcare services in developing countries. The chapter analyses the challenges, the enablers of the adoption of IoTs in healthcare as well as the theoretical frameworks that have been used in in IoT-based healthcare research in developing countries. The chapter starts with a description on the concepts of 4IR and IoT in the healthcare context. The chapter then describes the adopted methodology and the findings. The chapter then discusses the findings followed by the conclusion and suggestions for further research.
Key Terms in this Chapter
Adoption: It is the decision to start using something such as IoT based Healthcare services in this case.
Information and Communication Technology for Development (ICT4D): Information and communication technologies for development (health, agriculture, governance). It is the application of information and communication technologies for international development.
Internet of Things (IoT): The internet of things (IoT) is a concept reflecting a connected set of anyone, anything, anytime, anyplace, any service, and any network. The IoT is a megatrend in next-generation technologies that can impact the whole business spectrum and can be thought of as the interconnection of uniquely identifiable smart objects and devices within today’s internet infrastructure with extended benefits
Information Systems: The study of human interaction towards/with technology.
Partial Least Square Structural Equation Modelling: A statistical technique used to model variables.
Information and Communication Technology (ICT): Information and communication technologies.
Structural Equation Modelling: A statistical technique used to model variables.