JMIR Publications

ABSTRACT

Background:

Adverse event (AE) reporting is a key feedback signal for detection of safety issues relating to healthcare products. The reporting of adverse events for medical devices is a longstanding area of concern, with suboptimal reporting due to a range of factors including a failure to recognise the association of AEs with medical devices, lack of knowledge of how to report AEs and a general culture of non-reporting. The introduction of Artificial Intelligence as a Medical Device (AIaMD) requires a robust safety monitoring environment that recognises both generic risks of a medical device, and some of the increasingly recognised risks of AI health technologies (such as algorithmic bias). There is an urgent need to understand the limitations of current AE reporting systems, and explore potential mechanisms for how AEs could be detected, attributed and reported with a view to improving early detection of safety signals.

Objective:

This systematic review aims to search for existing adverse event reports for AIaMD, extract event data, and analyse the reported events to yield insights into their frequency and severity, whilst characterising the events using existing regulatory guidance.

Methods:

Publicly accessible adverse event databases will be searched to identify adverse event reports for AIaMD. Scoping searches have identified three regulatory territories for which public access to AE reports is provided: USA, UK, and Australia. Data extraction will be conducted using a data extraction tool designed for this review and will be done independently by two reviewers. Descriptive analysis will be conducted to identify the types of AEs being reported, and their frequency, for different types of AIaMD. AEs will be analysed and characterised according to existing regulatory guidance.

Results:

Scoping searches are being conducted and data extraction and synthesis will commence in August 2023, with planned completion by the end of 2023. The review has been registered on the Open Science Framework (https://osf.io/n2wrt/).

Conclusions:

To our knowledge, this will be the first systematic review of three different regulatory sources reporting AEs associated with AIaMD. The review aims to outline the characteristics and frequency of adverse events reported for AIaMD, and help regulators and policy-makers to continue developing robust safety monitoring processes.