Poster
Client Context
The client is the Winship Cancer Institute at Emory University Hospital Midtown (Winship). Winship is a comprehensive cancer facility that provides treatment across 17 stories and more than 450,000 square feet. The facility opened for treatment in May of 2023 with an outpatient model that adopts the patient-centered universal room concept, where all the necessary doctors, staff, and services are brought to the patient staying in one room. This model maximizes patient comfort as patients do not need to switch locations during their visit.
Project Objective
The motivation of this project stems from Winship’s projection of an annual volume increase of 4-6% in patient demand over the next ten years. The focus of this project will be to manage treatment capacity in the long term to accommodate this growing patient demand, and to find the tradeoffs between resources and patient wait time. The team is working with Winship Outpatient Operations Team and stakeholders such as clinical and technical staff to provide statistical insight.
Design Strategy
This project has two components. The first involves designing a new set of time slot recommendation through the use of the newsvendor model and extensive data analysis. The second opportunity involves a capacity forecast using Simio to simulate future hospital growth.
Deliverables
We developed two different deliverables. The first deliverable is an Excel spreadsheet outlining recommended time slots for doctors, infusion sessions, and patient room occupancy, as well as a detailed report explaining the rationale behind each recommendation. The report will also include the methodology employed to derive these recommendations, enabling the client to replicate the process for other floors or future services in the building.
The second deliverable aims to provide Winship with a flexible set of recommendations for both short and long-term operational changes. This includes:
- A simple Excel dashboard indicating the recommended duration for specific appointment types based on patient and appointment type variables.
- Another dashboard displaying daily patient capacity upper bounds. The client can input nurse and doctor policies currently in place, and the dashboard will calculate the maximum number of patients the floor can accommodate in a day.
Value and Impact
The project, focused on a non-profit hospital, prioritized non-monetary metrics for value assessment. Time slot reassessment yielded significant improvements: doctor service time slots for current and new doctors were 26.2% and 25.3% more accurate respectively for exam appointments, while infusion appointment recommendations were 6.37% more accurate. Using a Simio model, future projections revealed a 4-6% yearly increase in patient demand and a 24.4% rise in cancer survivors by 2032. The model identified potential bottlenecks and equilibrium points between resource capacity and patient arrival rates, highlighting doctor and room utilization as key congestion points. It also established patient arrival rate minima and maxima of 45 and 65 respectively, under specific resource constraints.
Project Information
Student Team
Jacob Schroeder
Suhyun Yun
Amelia Ayers
Shayna Coffsky
Julian Arbelaez
Calvin Dong
Aisha Sobti
Faculty Advisor
Faculty Evaluator
