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The Emergency Department represents the main entry point to the hospital and a key setting for the management of urgent healthcare needs in the population. To date, the assessment of care quality has mainly focused on organizational aspects, with limited structured tools to systematically measure clinical and care processes.
Overcrowding and limited resources make dedicated data collection unsustainable; therefore, it is necessary to rely on data already available from routine healthcare information systems. In this context, the study aims to assess the feasibility of using these data to construct quality indicators, as well as to evaluate their availability and reliability across participating centers.
The study will also analyze variability in indicators among participating Emergency Departments, with the goal of identifying differences in care processes and potential areas for improvement.
The Emergency Department (ED) is the primary gateway to the hospital system, yet its quality has traditionally been measured only by organizational efficiency rather than clinical care.
This study introduces a program to monitor the quality of assistance through standardized indicators, shifting the focus toward clinical and care appropriateness. Because Italian EDs face chronic overcrowding and resource shortages, the study is designed to be sustainable by using data already collected during routine clinical practice (current data flows) instead of requiring new, active data collection by staff.
The main goal of this pilot study is to build a reliable monitoring system. First, it verifies if the necessary data are actually available and accurate within existing hospital databases. Second, it measures the quality of care provided by participating centers to identify significant variations in clinical processes.
Finally, it aims to provide centers with detailed reports to help them interpret these findings and identify areas for improvement.
This is a multicenter, retrospective, observational cohort study involving at least 10 EDs. The study analyzes all patient visits over a three-year period, from January 2023 to December 2025, to account for seasonal trends and the evolution of care over time.
A total of 13 indicators are evaluated:
Data are extracted from hospital information systems and transferred via secure protocols for analysis. All information is pseudonymized at the source to protect patient privacy. The analysis assesses the reliability of the data and uses statistical tests to compare performance between different centers and over time. As a pilot project, this study serves to identify which indicators are robust enough to be included in a permanent, large-scale quality improvement framework.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Eligible population | Adult patients (age >18 years) who presented to the participating Emergency Departments between 1/1/2023 and 31/12/2025. |
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| Measure | Description | Time Frame |
|---|---|---|
| To verify the availability and reliability of data for the construction of indicators on the quality of care in Emergency Departments (EDs) in the hospital databases of the participating centers. | Data availability for calculating quality-of-care indicators in emergency departments will be assessed without statistical analyses. Data reliability will be evaluated by a multidisciplinary working group (statisticians, emergency physicians, nurses, and hospital information/management staff), considering clinical relevance, missing or incomplete data, and internal consistency. This approach will document potential limitations in data quality across participating hospital databases. | July 2026 - November 2026 |
| Rate of adherence to quality-of-care indicators per participating emergency department | Quality-of-care indicators will be calculated and, for each of them, 95% confidence intervals will be reported to quantify estimation uncertainty. Differences across participating emergency departments will be assessed using descriptive statistics (means, standard deviations, medians, interquartile ranges, boxplots, and histograms) and inferential tests appropriate to the indicator type: ANOVA and Kruskal-Wallis tests for quantitative indicators, and proportion difference tests for indicators expressed as percentages. | April 2027 - July 2027 |
| Change in quality-of-care indicator rates over the three-year study period | Temporal trends in quality-of-care indicators will be analyzed across the three-year data collection period (2023-2025) to quantify variations observed over time within and across participating emergency departments. | December 2026 - March 2027 |
| Proportion of patients managed in accordance with predefined quality-of-care indicators per participating emergency department | Quality-of-care indicators will be calculated according to predefined criteria, with 95% confidence intervals to quantify estimation uncertainty. Variability across participating emergency departments will be assessed using descriptive methods (means, standard deviations, medians, interquartile ranges, boxplots, and histograms) and inferential statistics, including ANOVA, Kruskal-Wallis tests, and proportion tests as appropriate. Temporal trends over the three-year study period will be analyzed. A retrospective application of the methodology will be performed to evaluate potential improvement signals under continuous monitoring conditions. |
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Inclusion Criteria:
Exclusion Criteria:
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Adult patients aged 18 years and older presenting to participating Emergency Departments during the period from 1 January 2023 to 31 December 2025.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Giovanni Nattino | Contact | +39 0354535351 | giovanni.nattino@marionegri.it |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Ospedale Civile SS.Antonio e Biagio | Alessandria | Italy |
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| ID | Term |
|---|---|
| D004630 | Emergencies |
| ID | Term |
|---|---|
| D020969 | Disease Attributes |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
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| December 2026 - March 2027 |
| Number of improvement signals per quality-of-care indicator under simulated continuous monitoring | A retrospective application of the continuous monitoring methodology will be performed to evaluate the number of improvement signals that would have been detected had the monitoring system been continuously active across participating emergency departments during the study period. | December 2026 - March 2027 |