What are AI Early Adopter sites?
Early Adopter sites are forward-thinking GP practices that try new Patchs features before anyone else. These are generally new AI modules but they can be other features too.
Why do we have Early Adopter sites?
Early Adopter sites help us gather evidence for clinical evaluations and safety assessments before the features are released to all practices. For the AIs this is required for PATCHS' registration with the MHRA and UKCA marking.
What are the benefits of being an Early Adopter site?
- You get to use the features before anyone else and therefore experience their benefits sooner.
- You can shape how the features are designed to suit your needs.
- Urgency AI can improve patient safety by helping you identify urgent requests and prioritise your workload quicker.
- Assign AI can improve patient safety by helping you identify requests that need clinician input quicker.
- Both Urgency AI and Assign AI support those making initial triage decisions (usually receptionists), thereby reducing their workload and improving triage accuracy.
- Mental Health AI speeds up consultations and reduces workload by automatically asking patients to complete PHQ-9 and GAD-7 where appropriate, thereby improving care quality by ensuring all patients get assessed in a standardised way.
- F2F AI can reduce workload duplication by highlighting which patients may need a face-to-face consultation, enabling you to book them directly in rather than dealing with them remotely first via Patchs or telephone, thus decreasing the number of patient contacts for the same problem.
What is required if you join the Early Adopter programme?
- Attend 1 training session on how to use the AIs (20-30 mins) and sign an Early Adopter agreement
- Attend 1-2 follow up meetings to give your feedback (20-30 mins each, 2 people expected to attend - ideally a clinician e.g. GP and non-clinician e.g. receptionist)
- Volunteer 3 members of staff to be interviewed by researchers from The University of Manchester about their experiences using the AIs (20-30 mins)