Procurement of algorithms for mammography

Breast cancer is the most common cancer among women in Denmark, and the demand for imaging diagnostics is increasing. This is due to the increasing number of exams per year, higher quality demands in the images and the lack of a corresponding rise in the number of specialists. AI technologies have the potential to address this challenge by automating certain tasks and freeing up resources.

Evaluations from the preceding MAGIC project have shown that commercial AI solutions are already ready for implementation, but there is a need for a well-structured procurement process that accounts for data security, ongoing maintenance, and system adjustments.

Aim

The goal of this project is to develop two comprehensive guidelines for the procurement and rapid validation of AI in clinical settings. The first guideline will focus on a quick validation process for AI models in clinical practice, while the second will cover the entire AI procurement process. These guidelines will be tested with AI solutions for mammography screening to ensure relevance and practical application. Through collaboration with key stakeholders, the project aims to create a scalable model that can support AI procurement across other clinical areas.

Partners

To ensure that the project develops guidelines that are practically applicable for conducting innovative procurement, interdisciplinary competencies from all relevant stakeholders are involved in both the development and evaluation phases. The primary project group consists of:

• Department of Radiology, OUH
• CAI-X
• Regional IT
• AI Competence Unit, Region of Southern Denmark
• Procurement and Legal Department, Region of Southern Denmark

Funding

The project is funded by the Danish Business Authority under the 2023 grant scheme for Innovative Procurement in Healthcare.