Hybrid Modeling Approach using Discrete Event Simulation and Layout Optimization for Healthcare Layout Planning Problems
Open Access
- Author:
- Lather, Jennifer Irene
- Graduate Program:
- Architectural Engineering
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- May 20, 2019
- Committee Members:
- John Isaac Messner, Dissertation Advisor/Co-Advisor
John Isaac Messner, Committee Chair/Co-Chair
Rob Leicht, Committee Member
Catherine Mary Harmonosky, Committee Member
S Shyam Sundar, Outside Member
Eleanor Dunham, Special Member - Keywords:
- Facility Layout Planning
Discrete Event Simulation
Data-Driven Healthcare Planning and Design
Hybrid Modeling - Abstract:
- The US is experiencing a growing population of older adults, increasing the demand on the healthcare system, and the Emergency Department (ED) serves as the main gateway for inpatient admissions. With this growing demand, EDs and hospitals are expanding and building new facilities at a growing rate. ED expansion and redesign is a complex design task which takes into account many operational processes (current and proposed) as well a projected changes in the system, e.g., patient volume. The effective layout of these critical departments in addition to the workflow processes that are hospitals influence the efficiency and effectiveness of delivering healthcare services. Yet, currently workflow processes and layout are not studied together. Workflow processes are studied via discrete event simulation in a static layout. Layout optimization finds an optimal layout given a static set of flow or adjacency data. The data from both methods need to be accessible and timely in delivery for effective use in the rapid pace of facility design. Given the lack of integration of computational facility planning techniques in the design and layout of healthcare facilities, new methods are needed to leverage data in the analysis planning and design decisions in timely ways. Computational models can be used to evaluate minimal distances or cost functions. Discrete event simulations can be used to model the stochastic nature of operations to check the impact on specific performance measures. Visualization can be used to immerse decision makers in the future environment to aid model validity, communication, and understanding. In this dissertation, the three techniques are investigated: discrete event simulation, mathematical layout optimization, and virtual visualization. First, layout implications in a discrete event simulation of an ED are studied so as to understand how the healthcare processes are impacted by layout decisions. Second, a layout optimization methodology leveraging the graph theoretical approach and a placement strategy is developed and connected to common parametric building information modeling (BIM) authoring tools for generating layouts with distance weighted adjacency step-wise optimality. Next, the use of generative layouts is studied with healthcare planning and design professionals. Finally, a framework for using these techniques in an integrated hybrid simulation modeling approach in the healthcare planning process is presented. The results for the study of layout in discrete event simulation show that not all layout consideration are additive. Two of five layout conditions contributed to the most amount of improvement over the baseline condition: results waiting (15.1% improvement on all patient length of stay - LOS) and admits zone (15.7%). A combined improvement was estimated to be 1.19 hours (23.9%) for overall LOS. The addition of fast track bays reduced the improvement by an estimated 10 minutes. The best scenario included care initiation, results waiting, and admits zone, and reduced overall LOS by 1.21 hours (24.3%). Study of space allocation and space utilization found additional fast track bays were not helpful and the results waiting was underutilized (max utilization = 7.40 people, a fifth of the seats available). Modeling the stochastic system of an ED in the context of the layout changes can help identify what changes contribute the most benefit, which changes are additive or compete, and help determine the space requirements and allocations through the analysis of projected operations in that facility, but needs operational process inputs and estimated new workflows. A new method for generating layouts was developed based on the graph theoretical approach for optimizing adjacency. The method uses an adjacency weighted distance score and a generative approach to create multiple layouts for review by designers and planners by translating space content into common parametric BIM tools. The results from the study of layout optimization and healthcare planners and designers is that the scoring metric aligns relatively well with expert opinions, but that more advances are needed to make generative layout methods more accepted by professionals. On average, respondents selected the ‘best’ layout marginally higher than random chance (proportion = 29.0%, expected = 16.7%). Respondents tended to choose the higher and lower scoring layouts, respectively: 65% of respondents selected either of the higher two options; 48% selected either of the lower two options, out of 6 options. Respondents found generative layouts promising for helping overcome design bias, however the current state of the technology would need additional development. Across all respondents experience, gender, and view on generative layouts, respondents wanted to understand the generative layout decision details. These layouts are based on adjacency ratings, which in an automated methodology could be updated through simulation. A hybrid modeling framework is presented which integrates simulation, optimization, and visualization modeling methods for healthcare facility layout planning activities for optimizing both process and layout. Objectives are presented to create a systems approach to the management, planning, design, construction, and operations of healthcare facilities. The main implications of this body of work are that layout and processes are paired, are in need of greater investigation, and an integrated approach is presented as a framework for healthcare professionals and researchers to guide the development of an automated decision support system for healthcare facility operations, planning, and design. These techniques, while described in a healthcare context, have implications for other domains where uncertain and latent processes are components of the layout decision making process.