Choice TeleMed provides Medical Imaging with the expertise and guidance for coordination and adoption of Imaging AI swiftly and effectively across Imaging providers and Clinical Trials. Including clinical validation, trialling, integration and triage, IG and cybersecurity, regulation and compliance, as well as best practice.
Globally, Imaging is under severe capacity strain with an 11% (UK) annual increase in scan volumes (with added specialism and complexity) and reduced time to diagnosis targets -with no significant increase in the number of reporters. Hence the potential of Imaging AI to revolutionise and become the saviour of diagnostics as we know it. However, there is a lot of ‘talk’ surrounding AI, particularly in Imaging and Radiology. And this talk ain’t cheap!
Given the fact that Imaging AI is a relatively new and evolving innovation, some 50-100 ‘Imaging AI companies’ have raised 100s of millions (if not billions by now) in VC, despite there being only 7 FDA and CE approved algorithms at the beginning of 2019. That figure has at least doubled during 2019, which demonstrates the speed of current advancement.
It is actually quite difficult to come across actual experts in Imaging AI however at Choice we have been fortunate to spend the last 2 years studying AI in detail and most importantly how it integrates and impacts into healthcare. Key considerations when considering AI include:
If you are considering AI as an innovative adjunct to your current Imaging provisions, talk to Choice's Imaging AI Consulting team today. We have the independent and impartial knowledge, experience and connections with all the leading AI providers to meet your bespoke requirements professionally.
Cost Reduction. Clinical trial scans are routinely reviewed by 2 readers with often a 3rd for adjudication. Collectively these resources can be costly particularly with any significant volumes and timepoints. One way to save on cost potentially is to introduce AI to perform one of the reads. Hence the first reader is AI at a cost reduction, the second reader is still a radiologist.
Improve Accuracy. Single read clinical radiology accuracy rates are generally thought to be @85%. The introduction of a second reader and
adjudicator can raise that up to @95% common in clinical trials. The potential of AI is also to introduce a further layer on top as a 3rd (or 4th)
reed, hence pushing the accuracy rate up further above 97/98%.
Collect more data. If the objective of the trial is to collect as much qualitative and quantitative data as possible, the introduction of AI can produce more structured outcomes and assist with incident findings.