This interview is part of our new AI in Healthcare series, where we interview the world's top thought leaders on the front lines of the intersections between AI and healthcare.
In this interview, we speak with Neeraj Bhavani, CEO of TAGNOS to understand how his company is using AI to transform healthcare, and what the future of the industry holds.
1. What’s the story behind Tagnos? Why and how did you begin?
NB: In a world where everyone and everything is connected, imagine losing sight of a loved one for even a few minutes — let alone a few hours. That's what happened when I lost sight of my father when he was admitted to a hospital a few years back. He was actually on the same floor but had been moved to a different treatment room unbeknownst to me. It took nearly two hours to locate him. I had already conceived an idea for an Asset Tracking product stemming from my days at UCLA Anderson School of Management, but in recalling the anxiety I felt during those two long hours, I knew there had to be a better way to gain insight into patients — for both families and care teams.
In 2014, TAGNOS deployed into our first hospital, which provided us with the stepping stones to refine and optimize our solution and obtain funding to scale the business. We gained access to a coveted slot at EvoNexus' exclusive incubator program in Irvine, CA, and were able to focus on continued product
enhancements and expand beyond our initial hospital site. In 2018, we received our first round of Series A funding — moving from early stage company to Series A startup. Today, we take pride in helping hospital communities across the US orchestrate their workflows and drive excellence across all care delivery paths.
2. Please describe your use case and how Tagnos uses artificial intelligence:
NB: We’ve built our AI/machine learning application around the idea of being able to provide constant improvement. We are the only company on the market today that leverages real-time data capturing capabilities in combination with a hospital’s historical records to provide a system that continually updates and adjusts its operational intelligence for sustained improvement. It provides care delivery teams with a more accurate view into what, when and how things will happen throughout their day ahead with a focus on Emergency Departments and Operating Rooms.
Emergency Departments are always chaotic, and we like to think of TAGNOS as the crystal ball for in-the-moment course correction. Teams can predict patient census up to four times a day, so staffing levels can be adjusted to meet the demands for the upcoming shift. It helps limit over-time and flex staffing needs.
For Operating Rooms, we provide an additional layer of intelligence with case length predictions to better calculate surgery start and end times, allowing for improved surgical line efficiency and opportunity for increased surgical capacity. Additionally, we provide forecasting into asset inventory to ensure the appropriate resources are needed for upcoming surgeries and incoming patient census.
3. Could you share a specific customer/user that benefits from what you offer? What has your service done for them?
NB: TAGNOS customers have seen improved operational efficiency and an increase in capacity within their surgery lines after implementing the OR Patient Flow Solution — the flow solution includes all technology elements that improve patient flow (real-time data, mobile communication platform and AI/ML predictions). TAGNOS clients perform thousands of surgeries every year, and often are reliant on manually entered data and have limited visibility into patient, staff, and asset statuses.
Our powerful combination of IoT, AI-machine learning and mobile communication has reduced overall room turnover time by 9.7 percent and cycle times by up to 12.7 percent. Enabling clinical logistics automation workflows triggered by real-time location system (RTLS) alerts from TAGNOS and mobile communication creates a highly synergistic surgical suite that delivers actionable information and open lines of communication centered around optimal efficiency.
The scheduling team will utilize the AI/ML Case Length Prediction module — a system that uses historical physician and support staff performance to provide foresight into how long a surgery will take on that day and adjusts in real time to accommodate changes. The module has been tested with up to 93 percent accuracy, which provides an opportunity for fewer case cancellations, staff OT and unnecessarily long patient wait times.