Current Projects
Characterizing the Workload of Emergency Medical Personnel
This research aims at quantifying the workload experienced by EMS personnel in real-time using the system generated data along with work measurements performed by a team of WSU students. The project uses techniques from Data Analytics, Simulation and Optimization.
Funding Provided by the National Science Foundation.
Contact: Laila Cure, Ph.D.
Spatiotemporally integrated radiotherapy plan optimization
This research aims at quantifying the extent of potential therapeutic gain that can be achieved from altering the radiation dose distribution over treatment sessions in fractionated radiotherapy. The design of optimal radiotherapy plans with spatiotemporally heterogeneous dose distributions gives rise to large-scale non-convex treatment-plan optimization problems. We employ global optimization techniques to solve the treatment-plan optimization problem and quantify the potential gain over traditional radiotherapy planning approaches using phantom cancer cases.
Funding Provided by the National Science Foundation.
Contact: Ehsan Salari, Ph.D.
Completed Projects
Developing Interruption-Handling Strategies for Inpatient Care processes
This research focuses on designig inpatient care tasks so that necessary interruptions can be integrated into the workday. We compare the risks associated with interrupting a primary task and with not addressing a secondary tasks immediately to determine the recommended action to address such itnerruption. More details about the methodology can be found here.
Contact: Laila Cure, Ph.D.
Collaborators: Stephanie Nicks (School of Nursing, WSU), Karen Schieman, Ph.D. (School
of Nursing, Western Michigan University).
Model-based Analysis of Work Execution Decisions in Nonrepetitive Work Systems.
This research focuses on the decisions made by a single worker over the short-term when decisions at higher levels have been made; staff has been scheduled and actual work needs to be accomplished. Examples of work execution decisions include the sequencing of tasks to be performed throughout a workday, the actions available to address randomly arising tasks or disruptions, and the revision of task sequences upon the realization of variability in work plans and disruptions. Theoretical constructs from state-of-the art research on interruption will be integrated with machine scheduling techniques using a computer-based, interactive and learning enabled simulation modeling approach. The identified work execution decisions will be studied in terms of their impacts on operational outcomes (i.e., quality, productivity, and workload).
Contact: Laila Cure, Ph.D.
Optimal Nurse Staffing and Skill-Mix Decisions in Inpatient-Care Settings
The objective of this research is to develop model-driven staffing strategies for nursing care delivery in inpatient care settings. Traditionally, nurse-to-patient ratios have been used to staff inpatient care units, which specify the number of patients that can be safely supervised by a nurse. However, patients often require different levels of care based on the severity of their medical conditions. Furthermore, not all care tasks need the support of highly trained registered nurses and thus hospitals often employ nursing staff with different skill levels for cost-saving purposes. The heterogeneity in patient-mix and nursing skill-mix can potentially render ratio-based staffing strategies ineffective. We incorporate this heterogeneity into staffing decisions using systems engineering approaches. In particular, queueing theory and discrete-event simulation techniques are used to determine optimal nursing skill-mix configurations that minimize staffing costs while ensuring timely delivery of care.
Contact: Ehsan Salari, Ph.D.
Multivariate Analysis of Quality in Trauma Care
The Institute of Medicine established that quality of care has six quality aim: effectiveness, efficiency, timeliness, safety, patient centeredness, and equitability. This research uses data from the Michigan Trauma Quality Improvement Program to define composite perfromance metrics per quality aim and perform multivariate analysis of trauma quality considering the six aims. The project is a collaboration between Wichita State University, Bronson Methodist Hospital Trauma Center, and Western Michigan University School of Nursing.
Contact: Laila Cure, Ph.D.
Collaborator: Karen Schieman, Ph.D. (Western Michigan University, School of Nursing)
Funding Provided by Bronson Methodist Hospital
Spatiotemporally integrated radiotherapy plan optimization
This research aims at quantifying the extent of potential therapeutic gain that can be achieved from altering the radiation dose distribution over treatment sessions in fractionated radiotherapy. The design of optimal radiotherapy plans with spatiotemporally heterogeneous dose distributions gives rise to large-scale non-convex treatment-plan optimization problems. We employ global optimization techniques to solve the treatment-plan optimization problem and quantify the potential gain over traditional radiotherapy planning approaches using phantom cancer cases.
Contact: Ehsan Salari, Ph.D.
Bidirectional Leaf Trajectory Optimization Approaches for Dynamic Delivery of Intensity-modulated Radiotherapy Plans
Unidirectional leaf-sequencing schemes have been traditionally used for dynamic delivery of intensity-modulated radiotherapy (IMRT) plans, where in order to modulate a desired fluence map, MLC leaves start from one end of the radiation field, sweep across, and stop at the opposite end. This research relaxes the unidirectional leaf-motion restriction and develops exact and heuristic leaf-sequencing approaches to obtain optimal bidirectional leaf trajectories. The trade-off between the fluence modulation quality and the required beam-on time is quantified for fluence maps with different complexity levels using the new and traditional leaf trajectory optimization methods.
Contact: Ehsan Salari, Ph.D.
Funding Provided by the National Science Foundation.