Publication Date
2012
Document Type
Thesis
Committee Members
Subhashini Ganapathy (Committee Member), Thomas Hangartner (Other), Andrew Hsu (Committee Member), Yan Liu (Committee Member), Pratik Parikh (Advisor)
Degree Name
Master of Science in Engineering (MSEgr)
Abstract
One of the main issues faced within the U.S. healthcare continuum is ineffective care transition. Ineffective transitions from one area of care to the next can lead to a reduction in quality of care, an increased risk of readmission, and an increase in healthcare costs. According to the National Transitions of Care Coalition (NTOCC), as many as 42% of the hospitals surveyed reported that care transitions during coordinated care delivery do not go as planned. One of the primary reasons for ineffective care transition is poor discharge planning. The purpose of this research is to analyze the effect of various policies for determining the time to discharge a patient on a variety of performance measures at a generic acute care hospital using discrete-event simulation. Three discharge policies are compared: a static policy and two dynamic discharge policies. First, a baseline simulation was created to model the static policy in which a patient is discharged when his/her estimated risk of readmission is acceptable as determined by his/her current health status. To validate the simulation model multiple data sources were utilized, which include the U.S. national statistics on readmission rates and patient pathways, and patient arrival data and bed capacities from an 800+ bed acute care hospital in the U.S. Once the model was validated, we designed and modeled two dynamic discharge policies that account for both the patient's medical condition and the current resource utilization of the emergency department (ED) in determining patient discharges. The performance measures of interest include the following: average time a patient spends waiting and boarding in the ED, the annual hours spent on ambulance diversion, fraction of patients in the ED leaving without treatment, and the total number of readmissions per year. Results showed that the dynamic policies have substantial merit in reducing ED crowding and boarding. The results also suggested a tradeoff between reducing ED measures and the number of 30-day readmissions. The insights from this research could pave path for further research that considers other patient pathways, resource planning and flexibility, and integration with the discharge location decisions.
Page Count
65
Department or Program
Department of Biomedical, Industrial & Human Factors Engineering
Year Degree Awarded
2012
Copyright
Copyright 2012, all rights reserved. This open access ETD is published by Wright State University and OhioLINK.
