- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06345352
Evaluation of the Quality of Care in the Emergency Department by Studying the Appropriateness of Admissions of Patients Accessing the Emergency Department (Fondazione IRCCS Ca' Granda Ospedale Maggione Policlinico)
May 18, 2026 updated by: Mario Negri Institute for Pharmacological Research
Evaluation of the Quality of Care in the Emergency Department by Studying the Appropriateness of the Admissions of Patients Accessing the PS: Construction and Validation of an Algorithm Based on Computerised Databases
The aim of this study is to develop, study and validate a rigorous and sustainable method for assessing the clinical appropriateness of the decision taken in the Emergency Department to admit or not to admit patients.
Study Overview
Status
Active, not recruiting
Detailed Description
The information normally recorded in the Emergency Department medical record will be used, as well as the available clinical and administrative databases.
For reasons of feasibility, the investigators will also restrict the analysis to patients coming to the Emergency Department with non-specific manifestations in the pulmonary, cardiovascular and abdominal districts, represented by one or more of the following symptoms: dyspnoea, chest pain, transient loss of consciousness, abdominal pain.
Study Type
Observational
Enrollment (Estimated)
1200
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Locations
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MI
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Milan, MI, Italy, 20122
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano
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Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
No
Sampling Method
Non-Probability Sample
Study Population
All patients entering Emergency Department represented by one or more of the following symptoms: chest pain, abdominal pain, dyspnoea, transient loss of consciousness.
Description
Inclusion Criteria:
- Adult patients
- Presentation in the Emergency Department with non-specific cardiopulmonary or abdominal manifestations, represented by one or more of the following symptoms: chest pain, abdominal pain, dyspnoea, transient loss of consciousness.
Exclusion Criteria:
- Voluntary removal of the patient;
- Sending home with instructions to return for further services
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
|---|
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Elegible population
All adult patients presenting to the emergency department with non-specific cardiopulmonary or abdominal manifestations, represented by one or more of the following symptoms: chest pain, abdominal pain, dyspnoea, transient loss of consciousness.
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Algorithm validation
Time Frame: February 2024 - December 2024
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To validate the classification algorithm on a sample of hospital medical records.
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February 2024 - December 2024
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Algorithm application
Time Frame: January 2025 - December 2027
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To apply the validated algorithm on patients referred to the PS of the Policlinico hospital over 36 months, to estimate the proportion of appropriate admissions.
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January 2025 - December 2027
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Appropriateness estimation
Time Frame: January 2025 - December 2027
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Provide, for the types of patients considered, an estimate of appropriate discharges for patients discharged and subsequently admitted to the Polyclinic, by drawing on the data available at the polyclinic itself.
For all other patients, data on living status and admissions to other facilities in the metropolitan area (PS administrative flow and hospital discharge cards - SDOs), will be analysed using data provided by the ATS Milano Città Metropolitana.
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January 2025 - December 2027
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Algorithm creation
Time Frame: September 2020 - January 2024
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To develop, for the types of patients taken into consideration, a classification algorithm of the appropriateness of admissions based on the files available at the Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico (for simplicity: Policlinico hospital)
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September 2020 - January 2024
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Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Actual)
September 15, 2020
Primary Completion (Estimated)
December 1, 2026
Study Completion (Estimated)
December 1, 2027
Study Registration Dates
First Submitted
March 28, 2024
First Submitted That Met QC Criteria
March 28, 2024
First Posted (Actual)
April 3, 2024
Study Record Updates
Last Update Posted (Actual)
May 20, 2026
Last Update Submitted That Met QC Criteria
May 18, 2026
Last Verified
May 1, 2026
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- IRFMN_7520_PoliMI
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
UNDECIDED
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
product manufactured in and exported from the U.S.
No
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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