Suggestion support system for healthcare facilities in Saudi Arabia: an assessment framework

Abstract

Saudi Arabia has developed an ambitious vision, Vision 2030, where the healthcare industry is one of the significant focus areas, making the healthcare industry more efficient and effective is crucial to attracting the private sector and making this vision a reality. Therefore, improving healthcare organisations' performance and competitiveness is necessary to achieve this sector's vision. In such a continuous improvement journey, suggestion systems can be considered an essential continuous improvement tool that identifies the industry's shortfalls and allows for potential future opportunities. It was found that the classical suggestion systems’ development process is subject to human behaviour that might discourage overall participation. Thus, interactive and straightforward systems will encourage productive participation. Furthermore, a study showed that employee creativity and positive engagement remain crucial in successful suggestion system implementation. Therefore, simplicity is considered the critical success factor in any suggestion system development and implementation process. The goal of this study is to develop an assessment framework for Saudi healthcare suggestion systems. A thorough review of the literature highlighted eighteen variables that act as drivers for the suggestion system's success. To account for a technology evaluation parameter, we adopted Nielson's definition of usability. He defines usability as a phenomenon that consists of five major factors: learnability, efficiency, memorability, error recovery, and satisfaction. A further understanding of the relationships between the suggestion system drivers and the adopted technical evaluation parameter's definition are investigated. A questionnaire on the eighteen variables was conducted, and 138 responses were collected. Based on a series of scientific analyses, the researcher identified three significant latent factors affecting the usability of a healthcare suggestion system: the Personal factor, System and Institutional factor, and Social Support factor. A maturity model with three levels of maturity was developed. The first level was defined as Low level, the second level was defined as a Medium level, and the third level was the High one. An Analytical Hierarchy Process (AHP) was performed to prioritise variables within each construct and among the three latent factors. AHP showed that the most critical factor is the Personal factor, followed by the System and Institutional factor, and then the Social Support factor. The first latent factor, the Personal one, includes the following suggestion system success variables: Reward, Ease of Use, Clear Scope, Autonomy, Trust, anonymity, Problem Solving, and Feedback. Under the second latent factor, System and Institutional, the success variables are Resources, Supervisor Support, Training, Publicity, Colleague Support, Compliance, and Equality. While the Social Support factor listed variables are Social Media and Social Networking. In order to test the developed model, two Saudi healthcare facilities were investigated. Furthermore, the developed model was found useful not only in assessing the current state of their suggestion systems but also in identifying the potential improvement opportunities. Having a prioritised list ensures that organisations can focus on improving factors that have a higher impact on the overall usability of the system.