Usability

The Usability principle states that the end-users should be able to use a medical AI tool to achieve a clinical goal efficiently and safely in their real-world environment. On one hand, this means that end-users should be able to use the AI tool’s functionalities and interfaces easily and with minimal errors. On the other hand, the AI tool should be clinically useful and safe, e.g. improve the clinicians’ productivity and/or lead to better health outcomes for the patients and avoid harm.

To this end, four recommendations for Usability are defined in the FUTURE-AI framework. First, through a human-centred approach, target end-users (e.g. general practitioners, specialists, nurses, patients, hospital managers) should be engaged from an early stage to define the AI tool’s intended use, user requirements and human-AI interfaces (Usability 1). Second, training materials and training activities should be provided for all intended end-users, to ensure adequate usage of the AI tool, minimise errors and thus patient harm, and increase AI literacy (Usability 2). At the evaluation stage, the usability within the local clinical workflows, including human factors that may impact the usage of the AI tool (e.g. satisfaction, confidence, ergonomics, learnability), should be assessed with representative and diverse end-users (Usability 3). Furthermore, the clinical utility and safety of the AI tools should be evaluated and compared with the current standard of care, to estimate benefits as well as potential harms for the citizens, clinicians and/or health organisations (Usability 4).

Recommendation	Practical steps	Examples of approaches and methods	Stage
Usability 1. Define user requirements	Identify end-users Collect user needs and preferences Analyse current clinical workflow Define human factors to consider	Interviews with clinicians and patients Workflow analysis Ergonomics assessment Digital literacy evaluation	Design
Usability 2. Define human-AI interactions and oversight	Design user interfaces Implement quality check mechanisms Define override procedures Ensure regulatory compliance	Human-in-the-loop mechanisms Error flagging systems Manual override options Compliance with AI regulations	Development
Usability 3. Provide training	Develop training materials Design training activities Deliver training to end-users Assess training effectiveness	User manuals Online tutorials Hands-on training sessions Post-training evaluations	Deployment
Usability 4. Evaluate clinical usability	Design usability tests Recruit diverse end-users Conduct usability studies Analyse user feedback	User satisfaction surveys Performance metrics Human factors assessment Qualitative feedback analysis	Evaluation
Usability 5. Evaluate clinical utility	Design clinical evaluation studies Assess patient benefits Evaluate clinician benefits Analyse healthcare system benefits	Randomised clinical trials Patient outcome measures Clinician productivity metrics Cost-effectiveness analysis	Evaluation