Propensity to Hospitalize Patients From the ED in European Centers.

Not yet recruiting

• Conditions: Emergency Medicine
• Interventions: Other: no intervention

• Registration Number: NCT06354764
• Lead Sponsor: Mario Negri Institute for Pharmacological Research

Brief Summary

The peer-to-peer comparison means center-to-center comparison, which requires adjusting for possible differences among centers to be fair and convincing. The first step to reach this goal is to develop a predictive model that accurately estimates each patient's probability of being admitted, starting from clinical conditions and boundary variables. Such a model would make it possible to calculate, for each ED, the expected hospitalization rate; that is, the hospitalization rate that would have been observed if the ED had behaved like the average of the EDs that provided the data to build the model itself. Comparing the observed hospitalization rate in the single ED with the expected rate derived from the model provides a rigorous method of comparing the department with the average performance, taking into account the characteristics of the patients treated and the conditions under which the ED operated. In other words, the predictive model represents the benchmark against which each ED is evaluated.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2024-04-03
• Study First Submitted QC: 2024-04-03
• Study First Posted: 2024-04-09
• Status Verified: 2025-05
• Last Update Submitted: 2025-05-08
• Last Update Posted: 2025-05-09
• Study Start: 2026-01
• Primary Completion: 2026-06
• Study Completion: 2027-02

Recruitment & Eligibility

• Status: NOT_YET_RECRUITING
• Sex: All
• Target Recruitment: 162000

Inclusion Criteria

• Adult
• Arrived at emergency department between 1 January 2021 and 31 December 2023

Exclusion Criteria

• None

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
Adults who attended the emergency department	no intervention	-

Primary Outcome Measures

Name	Time	Method
Create two separate databases	September 2024 - September 2025	To create two separate databases (one for each of the two subgroups considered) on all patients who presenteding to the participating EDs over a defined period, containing the information considered important to study both the propensity to hospitalize these patients and their 30-day mortality
Multivariable models	September 2025 - September 2026	To develop two multivariable models that predict the probability that patients presenting to the ED with dyspnea (first model) or after a TLoC (second model) will be admitted to the hospital
Adjusted comparison	September 2025 - September 2026	To provide the participating EDs with an adjusted comparison of the hospitalization rates for the patients with selected symptoms, to improve the quality of care.