A new tool to evaluate medical devices using artificial intelligence

When a company wishes to claim reimbursement for a medical device (as part of the list of products and services qualifying for reimbursement, LPPR), it must submit an application dossier to HAS. A properly completed dossier will benefit from an assessment without incurring any unnecessary delays. HAS is now updating its filing guides to support manufacturers in their submission for reimbursement of a medical device embedding a system with machine learning, and which falls within the field of artificial intelligence. Manufacturers may also submit a request for access to the innovation pass.

These filing guides now include a mapping of elements to complete that is dedicated to the particularities of this type of technology and serves to help manufacturers precisely describe the elements necessary for their assessment. The mapping grid was established after a public consultation phase open to all key players in the sector (manufacturers, developers, academics, learned societies, etc.) and held between November 2019 and January 2020.

The grid addresses various key points, grouped by categories, covering the entire process of technology development: what is the claimed use? What data was used for algorithm “learning”? Regarding the algorithm–the heart of the device–the manufacturer is asked to describe the features of its model: what type of learning? What frequency for relearning? What role does human intervention play in the process? What are the performance thresholds? ...

By following this grid companies can characterise their medical device, providing HAS with all the elements necessary for the evaluation of their product.

A common language to facilitate access to innovation

This is a major step for HAS in its continuous approach to support companies in their applications for coverage of medical devices. The basic criteria for regulatory assessment remain unchanged: HAS must have clinical data to issue an appraisal. Over time HAS will continue to build additional tools necessary for the evaluation of digital and connected medical devices.

This new tool will promote patient access to innovation as manufacturers learn early on the descriptive elements required for this type of technology assessment. Furthermore, encouraging access to precise information will facilitate dialogue between actors who come from different ecosystems (health or digital).

HAS’ next step will involve the publication of a functional classification grid of digital solutions according to purpose and use (screening function, diagnosis, prevention aid, help in understanding hygiene and dietary measures, etc.). This grid was submitted for public consultation between April and June 2020, and should be finalised by the end of the year.