Patient overflow in Emergency Departments (ED) has become a significant challenge for healthcare institutions in the United States. It has led to overcrowding, long wait times, and decreased quality of care. The consequences of patient overcrowding include increased morbidity and mortality rates, decreased patient and staff satisfaction, and higher healthcare costs.
A trusted healthcare institute in the US operating across multiple states in the country, sought a solution to predict the patient volumes in each department for better staff planning and to reduce the length of stay for patients. The team at Factspan helped the healthcare institution to develop a customized and scalable predictive data modeling solution that uses patient volume history and resource availability to manage patient flow across the departments. By focusing on anticipating patient demand and optimizing resource allocation, the model enabled the hospital to reduce wait times and improve patient experience.
- Assist hospitals to forecast high patient volume with accuracy of over 89%
- Provide staffing suggestions to reduce hospital staff burnout by 30%
- Minimize wait times and congestion by up to 50%
- Around 30% reduction in the duration of patient stays through data-driven insights
- Streamline hospital medication supply by 15% for better patient outcomes