Improving healthcare for millions of Americans living with chronic wounds
Kevin Keenahan is the co-founder and CEO of Tissue Analytics, a medical technology startup based in Baltimore. Using machine learning, Tissue Analytics transforms smartphones into powerful wound care imaging platforms. The app makes it easy for healthcare providers to take photos and gather information about skin, revolutionizing care for millions of Americans living with wounds, such as bedsores and diabetic ulcers, which sometimes accompany chronic conditions. With Tissue Analytics, providers can increase the accuracy and consistency of their measurements, and thereby assist their patients better and faster than ever before.
Kevin Keenahan spoke to citybizlist publisher Edwin Warfield from the Tissue Analytics offices at Spark for this interview.
EDWIN WARFIELD: Do you foresee the company staying here in Baltimore?
KEVIN KEENAHAN: We are extremely committed to the Baltimore ecosystem. Baltimore has been great to us. It’s been exciting to see the Baltimore ecosystem come together, and we think there’s a lot that this region can provide.
There’s great talent. There’s great health networks out here. It’s great from a sales perspective. You can get on a flight and go up to Chicago and back the same day. We have these sales hubs in Atlanta and Dallas. You can actually go to all those the same day, which can really cut down on the cost of customer acquisition.
We do expect to grow our sales force pretty considerably. There is this big potential to start to go after these larger hospital networks, these big multi-hospital networks. It’s great to work with academic medical centers and well-respected organizations across the country but, really, the way we will grow from a company the size we’re at right now to a much, much larger company is working with the chains out there—working with the hospitals that have 20, 30, 100, even 200 hospitals in the chain, and that takes a much different salesforce to go out and capture than we have now. One of the reasons we will be raising our Series A is to retune our salesforce and start to go after these larger enterprise contracts.
Q. How many employees do you have here?
A. We have about 10 people total, all located right here in Baltimore—mostly engineers, actually, which is I think what you’d expect for a company of our stage—but we do have a small and growing sales force that’s helping us maintain our rate of growth and our market penetration.
Q. Besides the machine learning, what are the other elements of the system?
A. It’s important for the way we go out and deploy to clinics that we have universal photo quality. You would never want to have even a different quality photo between two different systems. Our whole platform is around how to deliver the same quality photos and the same quality data to clinicians regardless of which setting they’re in.
To do that, we do a tremendous amount of processing on the images for things like color and lighting, and angle, and size, of course. We pre-process all these images based on these unified set of parameters before we start to do any other analytics. That’s the very, very first step we do.
Time saving is an extremely important aspect of the system. It’s really one of the ways that we can provide the most value in the short term. Of course, there is a huge potential to look at how our system and how our data improves wound healing times. That would be the ultimate goal for anyone to look at: Does this system actually heal patients? Does it allow clinicians to heal patients faster? But, in the short term, it’s really easy to look at how much time we can save clinicians. From a pilot we did at Lancaster General Hospital up in Pennsylvania, we found that we can cut documentation time by almost 60%. That’s time that the doctor can spend talking to the patient; tt’s time that the clinic could be seeing new patients; it’s time that the nurse could spend more time reviewing the patient’s wound healing progress with the patients themselves. We found that there’s huge potential to use that time to engage the patients in their own healing process.
Q. It seems like this data could help others besides clinicians and patients, like insurance companies.
A. The data that we generate, we found, can be valuable to a whole host of different organizations—not just the doctors themselves, not just the nurse, not just the patient, but, exactly as you said, this data can help the insurance companies. We can help the payers identify how long patients should be taking to heal, which products work. Through this tight collaboration with the care delivery folks and the payers, we can provide this next level of value. That’s something we see already starting to happen, as our database has grown so much. Because it’s such high quality data, we can start to ask these higher level questions. It is amazing—we’re extremely fortunate to have both Penn Medicine and Independence Blue Cross as investors because we can start to work with the data that we collect almost everyday.
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