Patients leaving without being seen from the emergency department: A prediction model using machine learning on a nationwide database
Author:
Affiliation:
1. Trinity West, Emergency Medicine Residency Steubenville Ohio USA
2. Department of Anesthesiology Mayo Clinic Rochester Minnesota USA
Publisher
Wiley
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/emp2.12266
Reference24 articles.
1. Emergency Department Operational Metrics, Measures and Definitions: Results of the Second Performance Measures and Benchmarking Summit
2. Factors Associated with Patients Who Leave without Being Seen
3. Hospital factors associated with emergency center patients leaving without being seen
4. Setting wait times to achieve targeted left-without-being-seen rates
5. Hospital Determinants of Emergency Department Left Without Being Seen Rates
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1. Investigation of emergency department abandonment rates using machine learning algorithms in a single centre study;Scientific Reports;2024-08-22
2. A study of “left against medical advice” emergency department patients: an optimized explainable artificial intelligence framework;Health Care Management Science;2024-08-13
3. Impatiently Waiting: Women Managers, Professionalism, Psychological Costs, and the Reduction of ER Wait Times;The American Review of Public Administration;2024-08-07
4. Those who opt to leave: Comparison by triage acuity of emergency patients who leave prior to seeing a medical practitioner;International Emergency Nursing;2023-09
5. Machine learning to identify attributes that predict patients who leave without being seen in a pediatric emergency department;Canadian Journal of Emergency Medicine;2023-07-28
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