Characteristics and Admission Preferences of Pediatric Emergency Patients and Their Waiting Time Prediction Using Electronic Medical Record Data: Retrospective Comparative Analysis.
Lin Lin GuoLin Ying GuoJiao LiYao Wen GuJia Yang WangYing CuiQing QianTing ChenRui JiangSi ZhengPublished in: Journal of medical Internet research (2023)
This study offers a contemporary exploration of pediatric emergency room visits, revealing significant variations in admission rates across different periods and uncovering certain admission patterns. The machine learning models, particularly ensemble methods, delivered more dependable waiting time predictions. Patient volume awaiting consultation or treatment and the triage status emerged as crucial factors contributing to prolonged waiting times. Therefore, strategies such as patient diversion to alleviate congestion in emergency departments and optimizing triage systems to reduce average waiting times remain effective approaches to enhance the quality of pediatric health care services in China.
Keyphrases
- emergency department
- healthcare
- machine learning
- end stage renal disease
- case report
- public health
- chronic kidney disease
- ejection fraction
- primary care
- newly diagnosed
- palliative care
- big data
- prognostic factors
- peritoneal dialysis
- electronic health record
- cross sectional
- patient reported outcomes
- convolutional neural network
- social media
- emergency medical
- robot assisted
- affordable care act
- patient reported