Patient‐provider mismatch, late cancelations, frequent rescheduling, and no‐shows result in long delays in getting specialty care appointments, higher costs, and more importantly, poor health outcomes. We propose an intelligent patient access management system that uses existing clinical and transactional data to ensure that the right patient sees the right provider at the right time. To that end, we developed a software platform referred to as Priority‐Driven Patient Access Tool (PDPAT). PDPAT allows clinical departments to define their patient prioritization schema based on medical indication and other patient characteristics and makes various appointment itinerary suggestions to appointment coordinators for optimal scheduling. PDPAT dynamically reserves capacity for high‐priority patients while delaying lower‐priority patient through so‐called scheduling time windows. The time window for each priority group are optimized based on
1) patient mix targets set by the practice and
2) empirically estimated patient willingness‐to‐wait (WtW) behavior.
A pilot study at a surgical division resulted in reduced access time and increased throughput, due to better coordination of clinic and surgical calendars. The talk will also introduce a framework, which we refer to as Human‐AI dynamic dual mode, to develop a patient prioritization protocol through continuous collaboration between algorithms and human experts.
Mustafa Y. Sir, Ph.D., is a Senior Applied Scientist at Amazon’s Health Services organization. He is an experienced leader managing multi‐disciplinary applied science teams to develop and implement innovative healthcare solutions for improving operational efficiency, cost‐effectiveness, and health outcomes. He has expertise in optimization and decision sciences, including large‐scale and multi-objective optimization and reinforcement learning. He also has 10+ years of hands‐on experience in developing measurement methods, predictive and prescriptive analytic and machine learning solutions for data‐driven decision‐making. Prior to Amazon, he worked at Mayo Clinic focusing on developing clinical decision support systems using complex health data from sensors and electron‐ ic medical records. He holds a Ph.D. degree in Industrial and Operations Engineering from the University of Michigan in 2007.
The seminar series “Providing Better Healthcare through Systems Engineering” is presented by the U‐M Center for Healthcare Engineering and Patient Safety (CHEPS): Our mission is to improve the safety and quality of healthcare delivery through a multi‐disciplinary, systems‐engineering approach.
A zoom option will also be provided to those who RSVP.