Acceptance of clinical decision support systems in Saudi healthcare organisations

Abstract

Applications of clinical decision support systems (CDSS) have become essential for physicians seeking to make appropriate decisions. The implementation of CDSS, however, is complicated if the factors affecting physician’s acceptance are not recognised. This study aims to explore the various factors that may influence the acceptance of CDSS in Saudi Arabia. A qualitative method was used to collect data from interviews with 54 GPs, with interviews conducted in three stages. The study then integrated the Unified Theory of Acceptance and Use of Technology (UTAUT) and Task-Technology Fit (TTF) models to communicate the findings. It is suggested that all factors of both UTAUT and TTF influence acceptance of CDSS by GPs, with the sole exception of the social influence factor. Some additional factors were also discovered by means of in-depth interviews, including accessibility, patient satisfaction, informativeness (increased knowledge), connectedness (informing patients), communication and shared knowledge, privacy and security, and perceived risk (functional performance risk and time risk). The study thus offers a new insight of the factors influencing GPs’ acceptance of CDSS.

The Antecedents of Acceptance of Clinical Decision Support Systems by Physicians and Pharmacists in Saudi Arabia

“…This nding is in line with results in prior research in general [31], [84], [85], [88]. In particular, this result validates the nding of the qualitative analysis in [86]. This result can be interpreted by the fact that (70.5%) of the respondents declared that the system helped them to meet patients' needs, and (74%) of them stated that the system allows them to accomplish more work than before.…”

“…The most common reasons for CDSS failures are Lack of integration into the business work ow, poor technical support, training issues, and the massive number of prompted alerts, "Alert fatigue" [22], [23], [24]. There is a reported lack of research publications investigating the acceptance of CDSS in Saudi health facilities [86]. Therefore, this research study is intended to examine the antecedents of user acceptance of the currently implemented CDSS as a part of Hospital Information System (HIS) BESTCare 2.0 in the Saudi Ministry of National Guard Health Affairs.…”

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“…This model has been employed to examine acceptance of technology in various fields, including computing technologies (Dwivedi et al 2019 ; Ayaz and Yanartas 2020 ), digital decision support system (Aljarboa and Miah 2021 ; Laka et al 2021 ), learning technologies (Almaiah et al 2019 ; Chao 2019 ; Altalhi 2021 ), social media (Al-Azawei 2018 ; Puriwat and Tripoposakul 2021b ), and healthcare system (Alam et al 2018 ; Nunes et al 2019 ). The studies that examine adoption of technology for banking services with UTAUT model are well established (Martins et al 2014 ; Bhatiasevi 2016 ; Sarfaraz 2017 ; Friadi et al 2018 ; Savic and Vasic 2019 ; Singh and Srivastava 2020 ; Yang et al 2021 ; Gupta and Dhingra 2022 ).…”

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“…The most commonly cited barriers to implementing a DSS were a lack of CDSS understanding among physicians, a large number of superfluous warnings in the system, the requirement for technical help, and the time spent using CDSS being deducted from time spent communicating with patient's electricity outages and a lack of technical understanding were also hurdles in deploying CDSS in rural health care in poor countries (Zakane et al, 2014). [12,13] The enormous number of alerts, the high expense of integrating the system with existing health-care practice settings, and the potential negative consequences on privacy, confidentiality, data accuracy, and alert creation are all barriers connected with CDSS (Gullapalli et al, 2015). [14] Furthermore, the previous study by Khalifa in 2016 allocated the barriers related to CDSS in Saudi Arabia into three categories; financial, organizational, and regulatory.…”

“…The second determinant is a systemic function, which refers to the fact that CDSS may be halted or unplugged from use due to system faults, causing delays or slowing the process of collecting required patient data; this, in turn, has a direct impact on CDSS acceptability. [12] Alert fatigue and clinical burnout are significant side effects of poorly integrated clinical decision assistance technologies that overwhelm users with irrelevant data or cause annoying workflow freezes that necessitate further clicks to resolve.…”