With the rise of chronic diseases and the recent outbreak of the COVID-19 pandemic, new challenges have been generated in the healthcare industry. Electronic health (e-health) is considered to be one of the stratagems, identified to overcome the challenges and to raise the standard of the medical system (Gagnon et al., 2016). Researchers like Severinsen et al. (2019), stated that implementing an e-health system, could improve many aspects of medical practices, and make the healthcare system safer, and more efficient.
However, several studies have raised concerns regarding the adoption of e-health systems, especially among healthcare providers. Abdekhoda et al. (2016) stated that healthcare providers’ adoption and use of an e-health system are still low and according to Alam et al. (2018), several e-health implementation projects were subject to resistance from users when they were deployed. According to Reiners et al. (2019), there is a disconnect between the anticipated improvements of the e-health system and the clinical reality. Despite the potential of e-health, many e-health implementations are either unsuccessful or are gradually losing steam.
Researchers like Kujala et al. (2020) stated that “The success of an e-health implementation depends on healthcare practitioners’ acceptance of the technology; for this reason, it’s necessary to research the elements that will influence the adoption of an e-health system before it is put in place”. Our research aims to explore the key factors that influence the behavioural intention of healthcare professionals, to adopt an e-health system in their daily routine. To identify the facilitators and barriers that affect e-health adoption among healthcare providers.
To analyse the determining factors affecting e-health adoption, The “Unified Theory of Acceptance and Use of Technology” (UTAUT) model of Venkatesh et al., 2003, offers a thorough picture of the aspects impacting users’ embracing and use of a technological system. Our research model is built based on the UTAUT model and the study of Venkatesh et al. (2003), which consisted of one dependent variable “Behavioural Intention” and seven independent variables “Performance Expectancy”, “Effort Expectancy”, “Social Influence”, “Facilitating Conditions”, “Self-Efficacy”, “Anxiety” and “Attitude Towards Using Technology”.
The quantitative research method and a cross-sectional explanatory research design were used to determine the elements impacting e-health system adoption. A total of 800 healthcare providers from a private group of hospitals in Mauritius, namely the Fortis Wellkin Hospital and the Fortis Darné Hospital were randomly selected and invited to participate in our survey using a validated questionnaire, which has been adopted from the study of the UTAUT model of Venkatesh et al. (2003). The final sample of respondents to our survey is made up of 512 individuals.
The data was evaluated in two stages: the first was to assess the discriminant and convergent validity of the measuring tool, and the second was to inspect the correlations amongst the variables of the study model. Exploratory Factor Analysis and Linear Regression Analysis were different kinds of statistical techniques used to analyse and validate the data.
Our results show that factors like “Performance Expectancy”, “Effort Expectancy”, “Social Influence”, “Facilitating Condition” and “Attitude Towards Using Technology”, are direct determinants and significant factors affecting the “Behavioural Intention” for the adoption of the computerised health system. However, factors such as “Anxiety” and “Self-Efficacy” have no significant effect on healthcare professionals’ adoption of the computerised health system.
The study has brought a much better thoughtful of the important aspects in the establishment of the e-health system by healthcare professionals of a private group of hospitals in Mauritius, which helps with developmental strategies to reduce the failure rate of e-health system implementations. Our research has helped to influence the body of knowledge on ICT adoption and e-health, it has also supplemented earlier studies on technology adoption by investigating the pertinence of the UTAUT model.