The Impact of Using Decision Support Systems on Improving the Decision-Making Process: A Study on Primary Health Care Centers in Buraydah City
DOI:
https://doi.org/10.56830/WRBA10202605Keywords:
Decision Support Systems, Decision-Making, Software, Computers, Top Management Support, Human CompetenciesAbstract
This study aimed to investigate the impact of utilizing decision support systems (DSS), across their various dimensions (software, top management support, human competencies, and computers), on improving the decision-making process in primary healthcare centers in Buraidah. This objective was achieved by assessing the level of usage of these dimensions, identifying the challenges facing their implementation, and exploring the field reality of the decision-making process. To attain these goals, a descriptive survey methodology was employed, utilizing a questionnaire as the primary tool for data collection. The study population consisted of all medical and administrative staff in the targeted healthcare centers, from which a sample of 51 employees responded to the electronically distributed questionnaire. The findings revealed a high level of utilization of decision support systems; the "software" dimension ranked first with a mean score of 3.96, followed equally by "top management support" (3.84) and "human competencies" (3.84), while the "computers" dimension ranked last with a mean score of 3.70. Additionally, the challenges facing the implementation of these systems scored an overall mean of 3.25, representing a moderate level of agreement, spearheaded by a lack of specialized training on data analysis tools and frequent unexpected technical breakdowns. Conversely, the reality of the decision-making process achieved a high overall mean score of 4.08, highlighted most prominently by a reduction in the time required to reach final decisions and an enhanced capacity to effectively realize health transformation goals. The results also demonstrated a statistically significant impact at the significance level (α ≤ 0.05) of utilizing decision support systems on improving the decision-making process. Based on these insights, the study recommends conducting intensive and continuous specialized training programs for staff on data analysis tools, upgrading current software systems by integrating predictive models to forecast future requirements, and allocating dedicated budgets for infrastructure enhancement.
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