Emergency Medicine
Conditions
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.
Interventions
OTHERno intervention
no intervention
Sponsors
Mario Negri Institute for Pharmacological Research
Astir s.r.l.
Centre Hospitalier Universitaire Vaudois
Orobix Life S.r.l.
Fondazione Bruno Kessler
Study design
Observational model
COHORT
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Inclusion criteria
* Adult * Arrived at emergency department between 1 January 2021 and 31 December 2023
Exclusion criteria
* None
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| 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. |
Countries
Italy
Contacts
CONTACTChiara Pandolfini
CONTACTGiulia Ghilardi
PRINCIPAL_INVESTIGATORGuido Bertolini, MD
Istituto Di Ricerche Farmacologiche Mario Negri
Outcome results
None listed