Ratthaphon Bunmi/123RF

AI In Healthcare Use Case #35: LeanTaaS

  • 18 July 2019
  • Sam Mire

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 Mohan Giridharadas, founder and CEO of LeanTaaS, 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 your company? Why and how did you begin?

MG: LeanTaaS began with a simple concept — imagine being able to dramatically improve core operational processes using the principles of lean transformation while adding the sophistication of advanced mathematics and data science (e.g., predictive analytics, optimization, simulation, machine learning, artificial intelligence, etc.) and then delivering the solution through simple, easy-to-use web-based applications that did not require a deep level of integration into existing IT systems.

Over a period of five years (2010-2015), the company developed sophisticated algorithms, built an analytics platform, and perfected the delivery model for such solutions across a wide range of industries including retail, banking, technology, manufacturing and healthcare. One such solution happened to be related to the infusion centers at Stanford Health Care. They were facing the classic problems of a mid-day “rush hour” that resulted in patients being forced to wait and nurses having a larger-than-optimal workload, which was creating significant operational pressures given the high growth in the number of patients seeking infusion and other oncology-related treatments.

It took us six months to solve the problem for the first time and then an additional six months to stabilize the optimization algorithm to consistently deliver good results every single day. We then realized that we had solved one of the core operational problems in healthcare: how do you match the available supply of resources (staff, rooms, chairs, machines) to the incoming demand pattern of patients (number of patients, type of treatment, duration of treatment, resources needed for the treatment, etc.) in order to reduce the wait times for patients, improve the number of appointment opportunities available to them, and improve the utilization of the scarce (and often expensive) assets in the health system?

We pivoted the company to focus 100 percent on unlocking the capacity of assets in health systems through the iQueue suite of products.

2. Please describe your use case and how LeanTaaS uses artificial intelligence:

MG: At LeanTaaS, we are focused solely on the operational side of using data science and advanced algorithms to improve the utilization of scarce assets, improve access to care for patients, reduce the wait time experienced by patients, and support the staff that have to make hundreds of decisions each day which influence patient flow through the health systems.

As AI tech improves, the evolution of the core operational processes in health systems will:

· Match the demand pattern (i.e., the volume of patients arriving for treatment, the type of treatments for which they are arriving, the expected duration of their treatment) with the available supply of resources (staff with the right level of skill, equipment, rooms, etc.) needed to service the specific demand pattern.

· Adapt over time as the underlying factors on either the demand side or the supply side change.

· React in near real-time to the inevitable “shocks” that impact the operational performance of a healthcare system including cancellations, add-ons, no-shows, delays, equipment downtime, staff absences, complications or reactions experienced by patients, etc.

· Absorb ever-increasing amounts of data from IoT devices (wearables, badges, monitoring of key health parameters, etc.).

· Learn by gradually incorporating clinical attributes of specific patients and providers into the operational recommendations that are being made (e.g., in assigning appointment slots or building appointment templates).

3. Could you share a specific customer/user that benefits from what you offer? What has LeanTaaS done for them?

MG: UCHealth’s hospitals and clinics have been trusted healthcare destinations for generations of Coloradans. Today, based on four consecutive years of recognition of its superior nursing processes and quality patient care from the American Nurses Credentialing Center and its ranking as one of the top 15 hospitals in the country by U.S. News & World Report, UCHealth hospitals are uniquely positioned to meet the healthcare needs of families throughout the Rocky Mountain region and the entire United States.

Previous rapid improvement events focused on first-case-on-time starts and turnover times had not significantly improved utilization in a substantive, sustainable manner. Leadership knew their volume was likely to continue to increase before new ORs could be built. Feeling a sense of urgency and pressure to increase OR utilization with a scalable approach, UCHealth turned to LeanTaaS, a partner with whom they had worked to improve operations in its infusion centers.

UCHealth partnered with LeanTaaS to deploy the iQueue for Operating Rooms Exchange and Analyze modules throughout 25 inpatient and eight outpatient operating rooms at its metro Denver location at the University of Colorado Hospital. After seeing the impact those two modules had on improving their utilization, UCHealth extended its use of the solution to its other community hospitals and ambulatory surgery centers. iQueue for Operating Rooms’ modular approach allows healthcare providers the flexibility to deploy modules individually or in any combination.

With access to data-driven performance metrics and the ability to release and/or request block time without an endless series of phone calls, emails, and faxes, UCHealth surgeons have enthusiastically embraced iQueue for Operating Rooms.

As a result of UCHealth’s deployment of iQueue for Operating Rooms, UCHealth experienced a 47 percent monthly median increase in blocks released, blocks released 10 percent earlier than with previous manual releases, and a four percent increase in OR utilization. As a result, UCHealth estimates $400,000 in additional revenue per OR per year.

About Sam Mire

Sam is a Market Research Analyst at Disruptor Daily. He's a trained journalist with experience in the field of disruptive technology. He’s versed in the impact that blockchain technology is having on industries of today, from healthcare to cannabis. He’s written extensively on the individuals and companies shaping the future of tech, working directly with many of them to advance their vision. Sam is known for writing work that brings value to industry professionals and the generally curious – as well as an occasional smile to the face.