An investigation on factors of the IoT-based healthcare adoption in Pakistan

Abstract

The innovation in Information and Communication Technology (ICT) has provided the future technology Internet of Things (IoT) with immense prospects and opportunities. IoT is a network founded on the use of sensors, actuators, beams, Radio Frequency Identification (RFID) devices, and software in things that can transform the future healthcare into pervasive healthcare delivery. IoT-based healthcare system can improve the delivery of healthcare services efficiently and innovatively by growing huge volume of patients’ data (big data) that can invoke proactive, predictive decisions and insights in future healthcare of Pakistan. However, no prior research is conducted so far in the context of IoT-based healthcare in Pakistan. To fill the research gap, the study contributed to develop and validate proposed research model and investigated significant factors influencing the IoT-based healthcare adoption by the community, medical professionals (doctors, support staff, health administrators), and end-users specifically in underserved areas of Pakistan. The research study confirmed proposed research framework in the precision of UTAUT and HBM theories on a sample of 281 diverse medical professionals’ responses from five hospitals located in different cities of Pakistan. The research employed exploratory, descriptive, and causal approaches to test and validate the research hypotheses using Exploratory Factor Analysis (EFA), measurement model, Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM) statistical techniques. The empirical findings statistically confirmed that performance expectancy (PE), effort expectancy (EE), facilitating condition (FC), doctor-patient relation (DPR) were significant predictors in technological context whereas, perceived severity(PS) of health risk behavior was also a significant factor of IoT-based healthcare adoption. The factors, which had no statistically significant impact, included perceived susceptibility (PSS) of health risk, social influence (SI), and trust (TR). These research findings are expected to improve prevailing healthcare in underserved areas and potentially benefit several stakeholders such as the healthcare service providers, health insurance companies, and remote healthcare providers, and designers of IoT-based health information systems in future.