UMHS Clinic Scheduling Optimization Tool
The University of Michigan Health system schedules over 2 thousand patient appointments per week. Matching the optimal appointment length/schedule to the appropriate patient clinical needs is a critical step in driving effective use of the UM Health system’s time and resources and hence profitability.
The Livonia Clinic is a group of specialty clinics from UMHS. Urology and Otolaryngology are two key clinics at the site. Clinic management believes that superior clinical care could be delivered in a more efficient manner through an improvement in the scheduling mechanisms currently available to the clinic. Staff nurses and others have identified a number of inconsistences between scheduled appointment time and the time actually utilized. There are examples of both over allocation and under allocation of time.
The student team will deliver a full analysis of the status quo, analysis of opportunities for efficiency gains based on simulation, and an implementation of a user-friendly, optimal scheduling front end that is fully integrated to the UMS scheduling system.
More Information: 2017-umhs
- Skill level All levels
- Students 5-7
- Likely Majors A&D, CS, IOE, MATH, SI
- Course Substitutions SI, Honors, IOE Capstone, A&D Elec
- IP & NDA Required? Yes
- Summer Opportunity Summer Funding Application
Scheduling / Optimization (2 or 3 Students)
Optimization, Modeling Time and Motion Study
- Likely Majors: IOE, MATH
Web Development (2 or 3 Students)
Tool development and back end integration with existing hospital system.
- Likely Majors: CSE/CS-LSA
User Interface Design (1 Student)
UI/UX Design, usability studies, graphic design experience/interest desireable
- Likely Majors: Information (SI), A&D
Faculty Mentor: Mary Duck
Operations Research and UM Health System
Mary lectures for the Senior Design course in the IOE Department, which partners with the Health System every semester. Together they manage 10-11 student projects on various process improvement topics. Mary is the Management Engineer Expert for the Health System. This allows her to function as sponsor and faculty.
Over the past 21 years, Mary has completed many process improvement projects within the U-M Health System (UMHS). She functions as a Six Sigma Master Black Belt. She is lean certified and has facilitated many Lean Value Stream Mapping workshops, internal education seminars, as well as other lean endeavors. She was the lead facilitator for the multidisciplinary OR/Pre-Op Lean committee, and initiated the process with UMHS administration to move forward lean principles that helped foster value-based decisions to improve and enhance patient and family-centered care initiatives.
Executive Sponsor Mentor: Dr. John T. Wei
Professor of Urology Associate Chair for Faculty Affairs and Communications in the Department of Urology
Prof. Wei graduated from the Medical, Education 6-year BS-MD Honors Program at Northwestern University, Evanston, IL and completed his urology training at the New York Hospital–Cornell Medical Center in New York City in 1997. Dr. Wei devotes 50% of his time to education/research with the remainder spent involved with clinical patient care. He has led the prostate cancer detection and Benign Prostatic Hyperplasia (BPH) research programs in the University of Michigan Urology Department (UM-Uro). His clinical focus includes the evaluation and treatment of male BPH, Prostate Cancer Biomarkers, and Quality of Life outcomes. Using the RAND prostate cancer quality indicators, the quality of care for localized prostate cancer was evaluated using a national cohort (the American College of Surgeons national cancer database). To date, the UM-Uro has developed novel measures for early stage prostate cancer (EPIC), urinary incontinence (M-ISI), and adaptation to pelvic floor disorders (ABI). His primary research focuses on the development and validation of health related quality of life measures, and the evaluation of quality of care for urologic conditions with an overarching goal to improve the delivery of urologic care. His other research interests also include biomarker validation where his research was funded by the Early Detection Research Network (EDRN).