The Delphi method is a sophisticated information-collecting technique that allows individuals to resolve complicated issues without having to meet in person [13; 17]. The Delphi approach can handle vast amounts of data without group bias [13]. It is a group communication process designed to establish a consensus [7; 13]. However, this technique has two drawbacks: it can take a long time and produce a poor response rate [17]. The RPN is calculated by multiplication of severity (S), probability of occurrence (O) and detectability (D) scores [6], with higher risk failures prioritized for corrective actions. However, several studies have raised concerns about the validity of this traditional approach, noting that multiplying three ordinal scales may distort risk rankings [19]. Furthermore, severity, occurrence, and detectability may not contribute equally--severity is typically regarded as most critical [20], while detectability is important for mitigation but generally considered less influential [20]. RPN scoring is subjective [7] and varies based on experts' opinions [21], and this subjectivity introduces flaws such as equal weighting of S, O, and D, identical RPN values arising from different score combinations, and a failure to reflect the true relationships among factors and inherent uncertainty. In the healthcare context, FMEA struggles further with standardization and expert subjectivity. To resolve these limitations, Multi-Criteria Decision-Making (MCDM) methods, for example grey relational analysis (GRA), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Analytic Hierarchy Process (AHP), and fuzzy logic, have been proposed [22]. A promising avenue for future research in this domain also involves an exploration of MCDM techniques aimed at enhancing the reliability of the RPN calculation [23]. To obtain the highest scores (quantitative data) of possible failure causes based on risk scoresand severity score, MCDM was applied for calculating and prioritizing the risk scores to overcome traditional RPN calculation. In addition, Pareto theory and severity score were considered in selecting risk scores for corrective actions. Fetoscopes are used to treat, among other conditions, twin-to-twin transfusion syndrome (TTTS). An unbalanced placental vascularization in the amniotic sacs of monochorionic (shared placenta) twins is one of the leading causes of mortality in the womb of monochorionic twins, especially through TTTS [24; 25]. In severe cases of TTTS, fetoscopic laser ablation (FLA) has provided successful outcomes. This procedure, under ultrasound guidance, has become the gold-standard treatment over the last decade [24; 25; 26; 27]. However, there are several issues that have arisen due to poor visibility, a limited field of view, the varying position of the placenta, the identification of blood vessels, occasional bleeding, and poor image quality [28; 29; 30]. Consequently, a new design of a fetoscope becomes a challenge, and risk assessment is necessary. Currently, no standard method exists for assessing the risk of surgical instruments. The study aimed to propose a cascading Delphi framework designed to overcome FMEA limitations, specifically regarding data collection and RPN calculation using a case study of flexible fetoscope. The proposed framework systematically collects reliable expert insights.