Issue link: https://beckershealthcare.uberflip.com/i/1187260
20 Executive Briefing: Standards simply do not work. Patient arrivals do not conform neatly to the established standards and specialists follow their established practice and tend to ignore standards set by the administrative leadership. Here is the interesting nugget — although specialists are dramatically different from each other in the way that they practice medicine, they are remarkably consistent with themselves. A specialist will be very consistent in managing the flow of activities for each type of patient appointment that they encounter over the course of the day. We call this their "fingerprint" since it represents the extreme in personalization. Just as each of us has a unique fingerprint, each specialist has a unique fingerprint that captures the essence of the way in which they practice medicine. Just as metronomes maintain a steady, consistent beat in music, an intelligent "fingerprint" provides a stabilizing, guiding force for the dance that occurs in clinics. The fingerprint model is a mathematical construct that is built by analyzing thousands of arrival rates, appointment types, add-ons, cancellations, visit lengths and the appointment choreography of the support staff for each specialist. The fingerprint model can be readily validated by simulation methods — simply enter the actual appointment sequence from a prior day and the fingerprint model will predict the room occupancy, patient backlog and wait times minute-by-minute throughout the day, which can be matched against the actual experience to confirm that the fingerprint is indeed an accurate abstraction of the unique manner in which each specialist practices medicine. Armed with an intelligent fingerprint and an accurate simulation model, the appointment template for each specialist can be optimized. Over time, the AI/ML algorithms embedded in these applications would continue to make the templates for each specialist even more smart so that the shocks and delays that will inevitably occur each day are less disruptive to the patient flow through the clinic. This means that specialists and nurses no longer spend their days underwater or dealing with unnecessary downtime, and staff wouldn't have to face frustrated patients, handling complaints instead of administering care. And, because AI-based systems learn and improve with each interaction, they can spot what worked well, which days didn't go as planned, and why. This data then gets applied to positively impact future scheduling. Tailored flexibility replaces standardization for more positive outcomes. While reducing the chaos of the typical clinic setting and enhancing the patient experience are enough to warrant bringing AI into clinics, there are some additional bonuses. As we've seen in other segments of healthcare in which AI is already helping to optimize resources, clinics could discover they have more rooms available than they thought, in which case they can accept more patients and help more people. They might also identify areas where they need to hire an additional provider or nurse. Through the simple act of intelligently reshuffling the appointments within the day, clinics can create a better flow that benefits specialists, patients and support staff. They can create a culture of continuous improvement. Those that seize it can expect greater patient loyalty as well as improved specialist and staff satisfaction, all while operational costs drop and the quality of care is enhanced. Mohan Giridharadas is an accomplished expert in lean methodologies. As founder and CEO of LeanTaaS, Mohan works closely with dozens of leading healthcare institutions including Stanford Health Care, UCHealth, NewYork-Presbyterian, Memorial Sloan Kettering, MD Anderson and more. Mohan holds a B.Tech from IIT Bombay, MS in Computer Science from Georgia Institute of Technology and an MBA from Stanford GSB. For more information on LeanTaaS, please visit https://leantaas.com/. LeanTaaS provides software solutions that combine lean principles, predictive analytics, and machine learning to transform hospital and infusion center operations. More than 70 providers across the nation rely on the company's iQueue cloud-based platform to increase patient access, decrease wait times, reduce healthcare delivery costs, and improve revenues. LeanTaaS is based in Santa Clara, California, and Charlotte, North Carolina. For more information about LeanTaaS, please visit https://leantaas.com/, and connect on Twitter/LeanTaaS, Facebook/LeanTaaS and LinkedIn/LeanTaaS.