Develops and validates a causality assessment tool for adverse events in medical devices, improving safety evaluations.
Background: Medical devices are crucial in health care; however, adverse events (AEs) require safety evaluation. Causality assessment determines the contribution of the device to AEs and guides decisions. India lacks a standardized scoring tool, leading to inconsistent interpretation. Aim: This study aimed to develop and validate a reliable causality assessment tool for AEs associated with medical devices. Materials and Methods: A nine-question structured scale was developed from a literature review to classify causality as certain, probable, possible, or unlikely. Validity was established through expert comparisons using the European Union Causality Assessment Scale. Sensitivity, specificity, and area under the curve (AUC) were calculated. Reliability testing occurred in two phases using 50 random Manufacturer and User Facility Device Experience database cases (2014–2024) assessed by six raters (physicians, biomedical engineers, and pharmacists). After 6 weeks, the same cases were reassessed. Reliability was determined using Cronbach’s alpha and intraclass correlation coefficient (ICC). Results: The ICC values for phases 1 and 2 were 0.324 and 0.399, respectively ( P < 0.001), indicating moderate agreement. Validity testing showed a sensitivity of 90.95%, specificity of 83.25%, and AUC of 0.8605, demonstrating strong accuracy in determining causality. The scale demonstrated high reliability (Cronbach’s alpha = 0.893). Conclusion: The validated causality assessment tool enhances consistency and reduces subjectivity among evaluators. It provides a reliable scoring system to support regulatory decisions, improve safety, and enable postmarket surveillance. This tool enables systematic assessment of device-related AEs across healthcare settings.
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George et al. (2026) studied this question.
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