Abstract Healthcare is a crucial and multifaceted sector dedicated to maintaining and restoring human health through a comprehensive range of services, including preventive care, specialised treatments, and public health interventions. The integration of advanced digital technologies has transformed this sector, enhancing accessibility, efficiency, and service quality through the digitisation and centralisation of patient records. However, this transformation also introduces significant cybersecurity challenges, including risks of data breaches, unauthorised access, and cyberattacks. To address these challenges, this paper proposes a robust decision-making framework based on Multi-Criteria Decision-Making (MCDM) methodologies, specifically, the CRiteria Importance Through Intercriteria Correlation (CRITIC) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. These are extended into an ordinal fuzzy environment to develop Ordinal-CRITIC (O-CRITIC) and Ordinal-TOPSIS (O-TOPSIS), enabling effective evaluation of healthcare system alternatives under linguistic and qualitative criteria. Seven evaluation criteria are considered: Required
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