How did DearHealth get started?
I and a team of medical researchers at UCLA Ronald Reagan Medical Center were working with patient data, trying to improve treatment for diseases. We saw something that electronic medical records were not able to provide. They were not addressing treatment of chronic diseases, especially cancer.
How did you address this?
We used artificial intelligence to analyze certain markers in lab results that appear in the medical record, as well as imaging and other bits of information. Our metadata model gets very granular — a virtual Excel spreadsheet, if you will. Then we applied artificial intelligence algorithms to that data to come up with sets of treatment recommendations. We applied this first to inflammatory bowel diseases. The goal is to develop treatment recommendations for a whole range of diseases.
Don’t doctors and specialists already look at the electronic medical record and decide on treatments?
Yes, but it can take an oncologist days to look at the data and weigh the various treatment options. Our program can do that in a matter of minutes. And we offer a clear synthesis of the recommendations — essentially explaining why the program comes up with the treatment recommendations offered.
How had Covid impacted the demand for the DearHealth software?
There was a positive and a negative impact. On the positive side, Covid greatly accelerated both the adoption of and reimbursement for digital technology like ours. On the negative side, at least initially, hospitals in particular were scrambling to obtain personal protective gear, ventilators and other Covid-related items. Anything non-Covid, like our software, was put off to the side until the immediate crisis passed.
What’s next for DearHealth?
We just hired a new full-time chief executive who will now focus on scaling up our products and expanding our customer base. It’s an acknowledgment that we’ve come out of the product development phase and are now ready to hit the marketplace.