Leveraging artificial intelligence to revolutionize medical device safety

Materiovigilance is a crucial component of health-care policy designed to ensure patient safety by monitoring and addressing safety issues associated with medical devices. However, traditional systems encounter challenges related to timely reporting, standardization, and the detection of adverse events. Artificial intelligence (AI) has the potential to transform materiovigilance by improving data processing, real-time monitoring, and predictive analytics. This review explores the potential of AI in strengthening medical device safety, highlighting its benefits in enhancing patient safety, personalizing medical devices, and streamlining regulatory reporting. AI-powered systems can detect adverse events, predict patient deterioration, and provide personalized treatment plans, ultimately improving patient outcomes. Furthermore, AI enables the analysis of large and complex datasets, facilitating proactive decision-making and the early identification of emerging risks associated with medical devices. By automating routine tasks and improving accuracy, AI can significantly reduce the administrative burden on health-care professionals. In addition, AI can enhance post-market surveillance by identifying trends and anomalies in real time, thereby accelerating corrective actions. However, ethical and regulatory considerations, such as algorithmic biases, data privacy, and accountability, must be addressed to ensure the responsible development and implementation of AI in materiovigilance. Establishing robust regulatory frameworks, fostering transparency, and promoting interdisciplinary collaboration are essential to overcoming these challenges and fully realizing AI’s potential in health care.

Authors

Publication Details

Journal
INNOSC Theranostics and Pharmacological Sciences
Published
2025-01-22
DOI
https://doi.org/10.36922/itps.6204
Citations
1
Primary Topic
Quality and Safety in Healthcare
Type
article
Field-Weighted Citation Impact
3.53
Controls
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article

Leveraging artificial intelligence to revolutionize medical device safety

Shubhima Grover, Hara Prasad Mishra, Nirav J. Shah, Smruti Mishra et al.
1 citations
INNOSC Theranostics and Pharmacological Sciences
Quality and Safety in Healthcare
3.53
article

Leveraging artificial intelligence to revolutionize medical device safety

Shubhima Grover, Hara Prasad Mishra, Nirav J. Shah, Smruti Mishra, Kevil Loriya
article en
1 citations

Abstract

Materiovigilance is a crucial component of health-care policy designed to ensure patient safety by monitoring and addressing safety issues associated with medical devices. However, traditional systems encounter challenges related to timely reporting, standardization, and the detection of adverse events. Artificial intelligence (AI) has the potential to transform materiovigilance by improving data processing, real-time monitoring, and predictive analytics. This review explores the potential of AI in strengthening medical device safety, highlighting its benefits in enhancing patient safety, personalizing medical devices, and streamlining regulatory reporting. AI-powered systems can detect adverse events, predict patient deterioration, and provide personalized treatment plans, ultimately improving patient outcomes. Furthermore, AI enables the analysis of large and complex datasets, facilitating proactive decision-making and the early identification of emerging risks associated with medical devices. By automating routine tasks and improving accuracy, AI can significantly reduce the administrative burden on health-care professionals. In addition, AI can enhance post-market surveillance by identifying trends and anomalies in real time, thereby accelerating corrective actions. However, ethical and regulatory considerations, such as algorithmic biases, data privacy, and accountability, must be addressed to ensure the responsible development and implementation of AI in materiovigilance. Establishing robust regulatory frameworks, fostering transparency, and promoting interdisciplinary collaboration are essential to overcoming these challenges and fully realizing AI’s potential in health care.

INNOSC Theranostics and Pharmacological SciencesVol. 8(3)
Openalex Percentile: Top 12%
Quality and Safety in Healthcare
3.53
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Leveraging artificial intelligence to revolutionize medical device safety — Shubhima Grover, Hara Prasad Mishra, et al. · INNOSC Theranostics and Pharmacological Sciences (2025) | TGRS Research Map | TGRS