Collaborative Emergency Department Crowd Management Framework using Wearable Devices and Data Analytics

Emergency Department (ED) waiting time has a serious impact on patient mortality, morbidity, length of stay, and patient satisfaction. The ultimate objective of this project is to develop a dynamic data-driven collaborative ED framework on top of a sensor-based approach to efficiently reduce waiting times in EDs using continuous and real-time monitoring of the patient in the waiting room and supporting the real-time decision-making process of admission or transference to another ED. The team proposes to design a platform where multiple patients use wearable sensors that transmit real-time data of their vital signs to a central dashboard for monitoring. Signal processing and machine learning techniques will be applied to the data to extract relevant information (blood pressure, heart and respiration rates, oxygen levels, etc.) to

  1. generate real-time alerts when patient’s condition deteriorates,
  2. feed a mathematical decision model using decision theory and reinforcement learning to prioritize patients inside the ED,
  3. transmit and receive real-time and secure information to/from other EDs to improve the model in order to suggest transference of patients between EDs,
  4. provide secure communication of the data inside the network using advanced encryption and privacy techniques, and
  5. visualize the general state of the EDs in real-time.

This research group has extensive experience in data-driven algorithms for detecting vital signs and developing mathematical models with multi-attribute utility theory, fuzzy logic, and decision trees to generate priority list on EDs.

The team expects to provide an end-to-end system that includes all the aforementioned features and revolutionizes the current status of the waiting times in EDs. The project will also help to optimize EDs resources and provide support for an effective decision-making process.

Publications

  1. Preliminary Data Collection for Collaborative Emergency Department Crowd Management using Wearable Devices. Metuge, Victoire; Valero, Maria; Zhao, Liang; Nino, Valentina; Claudio, David. IEEE International Conference on Digital Health, 2022.
  2. Implementing Virtual Nursing in Health Care: An evaluation of effectiveness and sustainability. Tudorache, Oana; Kenemer, John Brandon; Pruiett, Janna; Valero, Maria; Hedenstrom, Margot Lisa; Shahriar, Hossain; Sneha, Sweta. IEEE International Conference on Digital Health, 2022.