ArticleCureus2026
Challenges to Reporting Medical Device-Associated Adverse Events: Perspectives of Various Stakeholders.
Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
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Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background The effective operation of a medical device surveillance system relies heavily on healthcare professionals and other stakeholders voluntarily reporting adverse events related to medical devices. Despite measures to increase awareness among stakeholders and ensure user-friendly reporting procedures, the materiovigilance (MV) program is yet to pick up pace. Studies on knowledge and reporting of medical device-associated adverse events have been carried out in other countries, while in India, there has been limited investigation into this. This study aimed to understand the readiness of healthcare professionals in reporting adverse events related to medical devices. Objectives The objectives of this study were to identify hurdles to reporting medical device-related adverse events among healthcare workers, determine the awareness of MV among healthcare professionals, and resolve the challenges faced. Methodology This qualitative study used purposive sampling to conduct focus group discussions with selected healthcare workforce, including clinicians, nursing staff, pharmacists, and administrators from a tertiary care teaching hospital. Following Institutional Ethics Committee or IEC approval, we obtained informed consent from all participants before commencing the study. Each group consisted of six to eight participants to ensure diverse input across different levels of seniority and policy-making. A semi-structured framework was used to evaluate awareness, reporting experiences, and strategies to overcome barriers in MV. The discussions were recorded and transcribed. The transcribed data were thematically analyzed using inductive qualitative coding to develop subthemes and themes. Results The four themes elicited from the codes and subthemes were knowledge and awareness, hurdles in reporting, socioeconomic and logistical factors, importance of reporting, and resolutions in MV. The study identified a significant disparity in knowledge. Participation was further restrained by psychological and logistical hurdles, including a fear of professional blame and the burden of documentation. The important phrases that came to the fore, quoted verbatim, were as follows: (1) "if we report, they might get into trouble" and (2) "is there a Google form; the writing process is too much." Challenges such as a lack of institutional support, vendor-related problems, and device quality issues were found to directly impact patient safety. To mitigate these risks, participants emphasized the need for structured resolutions, including feedback and appreciation, inter-departmental collaboration, and enhanced vendor accountability. Conclusion Effective MV is crucial for patient safety and device quality, yet it requires robust training and a culture of feedback to encourage consistent reporting. Implementing accessible reporting tools such as digital forms or dedicated registers allows monitoring centers to streamline data collection and receive better support from healthcare staff. A no-blame environment is essential to encourage honest reporting.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.