Pinned straw:
Investor presentation webinar gives some possible revenue and answers some of the questions regarding progress.
Anticipated reimbursement for Aortic Stenosis is US$68 of which EIQ gets 25% at ~90+% margin. US $8.5M ARR @10% market share (conservative 5M number of Echocardiograms only Medicare, total could be closer to 35M). In contrast the same market share for Heart Failure is $264 @25% or $42M as the penalties for hospitals are much higher if the patient returns to hospital following missed diagnosis or insufficient treatment.
Reimbursement allows EIQ to clip the ticket rather than charging the medical centre.
$4M cash burn in last 12 months. Stated that HF approval not needed to be a successful company. AS treatment in UK only @10% so large market expansion potential for device/ drug treatment.
HF FDA approval expected in the next 12 months. Reimbursement should follow shortly after.
Licensing discussions ongoing with device manufacturers, pharmaceutical firms and hardware producers. Expected to peak post approval and reimbursement.
Accepted that initial push on missed diagnoses had not been well received and so now focusing more on improved workflow and practitioner assist. Although the algorithm is black box they are trying to show how the numerical data generated leads to the decision to provide greater transparency.
Claiming competitors AI solutions were about improving the image rather than aiding the decision but pretty vague.
Suggesting that once a partner top US hospital is using the product, liability concern issues will drive wider adoption.
Really interesting post, thanks for sharing. I tend to agree that the benefits will be in workflow / cost-savings rather than avoiding missed diagnoses. I would like to see more of the scientific data supporting use of the algorithm though - a search for the SCREEN-HF and NIL-CHF studies hasn't found any papers for me. If anyone has an abstract, conference outline or the papers themselves please share :)
While searching for echosolv papers, I have come across competitor solutions. I'm not prepared to set these aside as meaningless just yet, esp. as these firms seems to be building their scientific basis more than EIQ. We really need to see some data showing how the algorithm will change decision making, or show a time / cost / resource saving, in order to justify the potential commercial benefits.