Clinical Research Directory

AI4Triage - Development of an Artificial Intelligence Based Methods for the Analysis of Triage Data.

Artificial intelligence, and in particular Graph Neural Networks (GNNs), have shown enormous potential in the analysis of complex clinical data. Thanks to their ability to model relationships between variables, GNNs represent a significant evolution compared to traditional models, enabling better interpretation of medical information and supporting data-driven decision-making in complex contexts such as emergency medicine. The application of GNNs to clinical triage and to the prediction of length of stay can improve clinical efficiency by optimizing resource allocation and patient management. This observational study aims to evaluate the accuracy of predictions with respect to real clinical data, contributing to the development of advanced predictive tools to support healthcare decision-making processes.

Response Times in Danish Emergency Medical Services

The overall aim of this retrospective observational study is to investigate the association of emergency medical services response time with patient survival and treatment outcomes. The main question it aims to answer is: What is the association between response time and patient survival? The investigators will collect data for all patients who were treated by ambulance and/or helicopter services in Denmark and follow the patient's path from illness or injury to discharge from hospital with a focus on the significance of ambulance and helicopter response time.

Impact of Point-of-care Lactate Testing as Triage Supplement on Patient Management Using Manchester Triage System

Although the Manchester Triage System (MTS) is widely used and validated internationally, it has some limitations. Its accuracy is moderate, especially for children and the elderly. Rising patient numbers and overcrowded emergency departments increase wait times, sometimes beyond safe limits. In Slovenia, MTS has been in use for 14 years without major updates, despite a significant rise in emergency visits. The yellow triage category (60-minute wait time) includes a very diverse group of patients, some of whom might require faster care. Older patients, in particular, often show atypical symptoms and may be under-triaged. Including rapid bedside lab tests, like blood lactate levels, could improve risk assessment and triage accuracy. Elevated lactate is linked with higher mortality and can help identify critically ill patients more effectively. The proposed study is a prospective, randomized trial involving two groups of patients in the yellow triage category, all of whom will have their capillary blood lactate levels measured. Patients with normal lactate levels will be excluded. Only patients with elevated lactate will be compared. The test group will be re-triaged to the orange category and treated more urgently. The control group, despite also having high lactate levels, will remain in the yellow category, and their elevated lactate values will not be shared with the treating physician. Randomization will be based on the patient's birth date (even days = test group, odd days = control group). Only the nurse will know the result, maintaining physician blinding to avoid the Hawthorne effect-changes in behavior due to awareness of being studied. Standard lab tests will be performed later during treatment as deemed necessary by the attending doctor.

FOllow-up of LOW-acuity Patients After REdirection From a Swiss Emergency Department Using an Electronic TRIage Application

Emergency department (ED) overcrowding is a growing issue, affecting patient safety, healthcare quality, and hospital efficiency. One strategy to manage low-acuity patients is triage-based redirection, where patients with non-urgent conditions are offered the option to receive care at external medical facilities instead of the ED. This monocentric, prospective observational study will be conducted at Fribourg Cantonal Hospital, Switzerland, and evaluates the impact of a new electronic triage and redirection system (Logibec Réorientation). The study compares two triage processes: Current practice - Redirection based on the Swiss Emergency Triage Scale (SETS), limited to low-acuity patients (SETS 4). New practice - Redirection using the Logibec software, allowing redirection of both low-acuity (SETS 4) and semi-urgent (SETS 3) patients based on predefined criteria. The primary objective is to assess whether the new triage-based redirection reduces the number of ED consultations per patient within 48 hours of their initial visit. Secondary outcomes include: Number of consultations in the ED or other medical facilities within 7 days Rate of hospital admissions within 7 days Patient satisfaction with redirection Evolution of health literacy over 6 months Number of ED visits over 6 months Participants are adult patients (≥18 years old) classified as SETS 3-4 and identified as eligible for redirection by the Logibec software. Data will be collected through phone interviews and questionnaires over a 6-month follow-up period. This study aims to improve triage efficiency, patient flow management, and healthcare accessibility, while ensuring patient safety in the redirection process.

Establishment of Emergency Surgery Triage and Checklist Management System

The goal of this observational study is to develop and test a system for managing emergency surgery patients at Beijing Union Medical College Hospital. The main questions it aims to answer are: What information is necessary for effective patient triage and handovers between the emergency department, anesthesia, and ICU for surgical patients? How effective and feasible is a standardized handover process in improving patient outcomes and safety? Participants will: Be observed and have their handovers documented to identify key information required. Participate in implementing a new handover checklist and triage system. Researchers will compare the periods before and after implementing the new system to see if it: Reduces missed critical information during handovers. Decreases pre-surgery waiting times for critically ill patients. Improves overall patient safety and outcomes, including reducing postoperative complications, mortality rates, length of hospital stay, and medical costs.