Predictive and Advanced Analytics in Emergency Medicine - Neurological Deficits

Recruiting

• Conditions: Artificial Intelligence; Resource Allocation; Neurologic Manifestations

• Registration Number: NCT06245694
• Lead Sponsor: Medical University of Vienna

Brief Summary

Future predictive modeling in emergency medicine will likely combine the use of a wide range of data points such as continuous documentation, monitoring using wearables, imaging, biomarkers, and real-time administrative data from all health care providers involved. Subsequent extensive data sets could feed advanced deep learning and neural network algorithms to accurately predict the risk of specific health conditions. Moreover, predictive analytics steers towards the development of clinical pathways that are adaptive and continuously updated, and in which healthcare decision-making is supported by sophisticated algorithms to provide the best course of action effectively and safely. The potential for predictive analytics to revolutionize many aspects of healthcare seems clear in the horizon. Information on the use in emergency medicine is scarce.

Aim of the study is to evaluate the performance of using routine-data to predict resource usage in emergency medicine using the commonly encountered symptom of acute neurologic deficit. As an outlook, this might serve as a prototype for other, similar projects using routine medical data for predictive analytics in emergency medicine.

Detailed Description

Not available

Study Timeline

• Study Start: 2022-01-01
• Study First Submitted: 2024-01-30
• Study First Submitted QC: 2024-01-30
• Study First Posted: 2024-02-07
• Status Verified: 2024-11
• Last Update Submitted: 2024-11-19
• Last Update Posted: 2024-11-22
• Primary Completion: 2025-01-01
• Study Completion: 2030-01-01

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 50000

Inclusion Criteria

• Female and Male subjects
• Age ≥ 18 years

Exclusion Criteria

• none

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Prediction model	1.1.2025	to be developed

Trial Locations

Locations (1)

Emergency Department, Medical University Vienna; 🇦🇹 Vienna, Austria