Artificial intelligence is driving optimized capacity and revenue in asset-driven service industries that resemble healthcare in their operational challenges and goals. In healthcare, we have the opportunity to replicate those successes as we deploy AI to achieve better return on investment.
AI in Industries Outside Healthcare
We already encounter the use of AI frequently in solutions we use to navigate our daily lives. In all the following instances, AI derives key conclusions from pools of data far too large or complex for manual calculations and drives the ROI that keeps these industries running.
- Airlines: Whenever we fly, most often on a full plane, airlines have done a lot of work to predict passenger demand by route. Airlines use historical data to forecast on which day one of 300 million Americans might fly from which of 20,000 possible airports to which of 19,999 others. They also predict how many ticketed passengers will not fly to accurately “overbook.”
- Package Delivery: UPS and other delivery services predict the volume, origins and destinations of millions of packages shipped each day, while also optimally loading packages of varied shapes and sizes into static-sized trucks and determining the most efficient routes to deliver them.
- Navigation Systems: Apps like Waze predict the precise patterns of traffic based on both historic data along routes and update them based on traffic events in real time.
- Consumer Services: Amazon uses buyers’ habits to recommend further products to them, and Google, whose revenue comes purely from ads, displays those most likely to ensure user clicks.
What Healthcare Can Learn From Other Industries
Directing patients and appointment schedules accurately relies on the same level of prediction, based on historic patterns and real time updates, utilized by other service industries. Leaving room for unexpected occurrences is also critical to ensuring smooth day-to-day operations.
Operating rooms are like airplanes, only creating revenue when they are “in flight” and fully booked. Outpatient appointments such as infusion treatments amount to different sizes and shapes being “packed” into a static space—a clinic’s schedule, rooms and chairs—not unlike packages being loaded onto a UPS truck. Directing the flow of inpatients through various bed units and levels, ensuring “traffic” runs without bottlenecks, requires the same precision and accuracy used by Waze to predict the fastest possible route at a given moment.
All these functions support the fullest possible use of existing healthcare assets to drive better ROI. The historical data we need to produce these predictions and prescribed actions has already been captured in most EHRs. In healthcare, there is a massive opportunity to further leverage technologies that already exist to capture our capacity and drive revenue.
Why Healthcare Lags in Leveraging AI
There are several reasons healthcare leaders are wary of adopting AI tools. One is the perception that our existing EHRs are robust enough. However, EHRs and data dashboards are designed for gathering information from each patient encounter into a single database. While they can display capacity problems, AI-level analytics will make informed recommendations beyond what EHRs can do and beyond what most in-house teams, regardless of size, have the resources to build.
Another concern is that healthcare’s special obligation to safety and accuracy prevents us from risking new solutions. In fact, healthcare is not unique in these concerns. Note the airline industry. Every morning 3 million Americans board a 200,000-pound steel tube and are shot across the sky. If even as few as .001% of these passengers did not land safely, the industry would risk 30 deaths each day. But this is not the case, and very rarely are the passengers’ bags even lost. AI can help provide healthcare the same ability to master the science of increasing access and lowering cost.
Finally, healthcare leaders are rightfully dedicated to making sound fiscal decisions that make the best use of limited resources. The financial rewards of investing in AI are also clear, and the cost is much lower than attempting to build AI-powered solutions in-house. At LeanTaaS, we strive to act as true partners in this regard. We are so confident in our AI-driven iQueue solutions’ ability to deliver value that we offer an unconditional money-back guarantee to customers who don’t achieve their desired results within three months. This guarantee is unprecedented in the healthcare space, and none of our customers have accepted the offer yet.
The ROI of AI: What Health Systems are Already Achieving
We have calculated that the 57 health system customers who were live with iQueue for Operating Rooms for over one year made an average $500,000 worth of OR time available annually for more surgeries. Penn Medicine used the AI tools offered by iQueue for Infusion Centers to more efficiently “pack” daily schedules and increased patient volumes by 25%. UCHealth, an iQueue for Inpatient Bed customer, improved its predictability yielded an 8% decrease in opportunity days, equal to $8 million in value.
In each of these cases, by deploying AI to optimize asset utilization as other industries already do, healthcare providers unlocked new revenue. All healthcare organizations have the opportunity to do the same.
To explore a health system’s successful use of AI in unlocking OR time and generating surgical revenue, view Baptist Health Jacksonville’s recent webinar, “Optimizing OR Utilization Using Predictive and Prescriptive Analytics: A Case Study.”
Sanjeev Agrawal is COO and co-founder, LeanTaaS.