Observational analysis reveals the effectiveness of regulatory mechanisms in healthcare, suggesting AI can enhance service quality.
This study aims to propose an intelligent preventive regulatory model to enhance the sustainability of healthcare service quality provided by medical offices affiliated with Hajj missions, within a highly complex operational environment that demands immediate response and precise performance monitoring. The proposed model integrates preventive oversight principles and artificial intelligence technologies with traditional field-based regulatory practices, leveraging real-time operational data expected to be collected through the “Al-Munazzim” platform, which is currently under development. The study includes an analysis of the existing regulatory landscape and reviews the Kingdom of Saudi Arabia’s experience—led by the Saudi Data and AI Authority (SDAIA)—in managing healthcare-related crowd control during the 2025 Hajj season. The model was developed based on field observation, active participation, and assessment of the current organizational and technical capabilities. It comprises five main components: a unified digital database, an intelligent analytics unit, a real-time monitoring dashboard, a proactive alert system, and a smart medical referral unit. This model supports the classification of medical offices by risk level, enabling accurate and flexible allocation of regulatory and clinical resources, and improving integration with emergency and specialized hospital services. The study recommends piloting the model in a limited scope as a first phase, alongside the technical development of the “Al-Munazzim” platform and capacity building for regulatory teams to make proactive, evidence-based decisions.
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Shameem Jabbar (2025) studied this question.
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