Seeing the need, making it happen – a founders journey

Necessity is the mother of invention. And in the case of Mednition, I will add, fatherly love.

The genesis for Mednition came nine years ago from a personal experience in an emergency department (ED), one that was unfortunate and could have ended quite differently for my daughter, who is fine today. The experience gave me critical insight into the practice of medicine. And more critically, it gave me a front row seat to the challenges facing patients and clinicians alike, particularly ones working in the EDs of today’s busiest hospitals.

Long a management and technology consultant, my skills are honed to identify problems. I key in on threads and follow them in search of overlooked answers and solutions. We did that in the ED. And, it became clear that ED nurses — every hour of every day — face an uphill battle. 

Every year, more than 145 million people are treated in EDs. And over the past 20 years, that number has increased by about 35% while the number of EDs has shrunk by 11%, according to the Centers for Disease Control and Prevention. That’s untenable.

It was apparent that ED nurses facing 21st century challenges needed 21st century solutions. Challenges needed to be addressed in real-time, in a practical, efficient and safe way. And it had to be done in a way that was cost effective and, first and foremost, made sense to the nurses. Lives, literally, depended upon it.

With that insight, I teamed up with my brother, a technologist with substantial experience in operational systems and machine learning, to form Mednition. Our mission from the get-go has been to develop new machine learning powered solutions that improve healthcare and save lives where it matters most, at the point of care. Initially, that means in the hands of emergency nurses. For the past seven years, we’ve been unlocking and leveraging critical data in EHR systems in ways never before imagined, and in ways making it readily accessible and actionable within the emergency nurse’s existing processes.

Today, our goal has been met. Meet KATE!

This new machine learning solution provides real-time decision support to help emergency nurses increase the accuracy of triage decisions. The platform can read and extract the entirety of EHR data, and detect and manage anomalies of care. KATE integrates easily into popular EHR systems and existing triage processes.

It wasn’t easy. It has taken a passionate team of clinicians and data scientists years to bring KATE to life. It has also taken invaluable partnerships, like the one forged with Adventist Health White Memorial (AHWM). We’re proud of how our team is collaborating with AHWM on many fronts, starting with an in-depth first-of-its kind study reviewing the efficacy of KATE.  Based upon the findings of that study, KATE is now in full commercial use in the AHWM Emergency Department. The study is currently under peer review and can be accessed on the research pre-print site arXiv.org.

Later this week at the Emergency Nurses Association EN19 conference in Austin, we’ll demonstrate KATE for the first time publicly. Like any new company bringing its first product to market, we are incredibly proud of what we have done and the solution we have made. 

But our team is even prouder of what KATE is already doing — it has been in the hands of real nurses at Adventist Health White Memorial for nine months, supporting them and their patients in real time (over 45,000 to date), to deliver the best possible care for AHWM patients. 

And that’s what fires us up every day!