Thematic Issues in Analysis and Visualization of Hospital Emergency Department Patient Flow
Poster presentation for the International Symposium on Human Factors and Ergonomics in Health Care, Boston, MA (March 2018)
Bottlenecks in patient care within the emergency department (ED) are a growing concern for hospitals around the country. Most trauma centers operate at or above capacity, and patients regularly experience long wait times, long lengths of stay, and a lack of inpatient bed availability. These factors not only significantly impact patient and provider satisfaction, but can substantially increase operating costs for hospitals. Understanding patient flow, and identifying bottlenecks to flow from the ED to eventual placement or discharge, has the potential to reduce wait times, improve care for individual patients, and increase the volume of patients treated at the hospital over time. These outcomes would additionally decrease health care disparities experienced by underserved communities. We reviewed the relevant literature on sources of emergency department bottlenecks and systems for analyzing and visualizing patient flow data, performed searches in Google Scholar and inspected the search results for papers most relevant to analysis or visualization of emergency department patient flow. From these articles, we identified variables used to measure flow and congestion, variables used to predict flow and congestion, models of patient flow, techniques for visualizing patient flow, and causes for concern with current practices for analyzing or predicting patient flow. We supplemented our understanding of these documents with input from subject matter experts, including emergency department physicians and nurses. What we identifed is a relative absence of using predictive means to manage flow of patients through the emergency department, as well as drawbacks in hospital practice and data visualization tools that further affect bottlenecks. Tools to analyze and visualize patient flow have the potential to greatly benefit both clinicians and patients.
1 Charles River Analytics
2 National Center for Human Factors in Healthcare, MedStar Health
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