Emergency and Urgent Care Indicators in Piedmont

Trial statusNot yet recruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorMario Negri Institute for Pharmacological Research

About this trial

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.

Eligibility criteria

This trial does not accept healthy volunteers

Qualifiers

Adult patients (age >18 years) who presented to the participating Emergency Departments between 1/1/2023 and 31/12/2025.

Disqualifiers

All patients under 18 years.

Trial population

Adult patients aged 18 years and older presenting to participating Emergency Departments during the period from 1 January 2023 to 31 December 2025.

Trial design

Design model

Cohort

Time perspective

Retrospective

Treatments tested in this trial

Not listed

Trial groups

650,000 Participants
are grouped into 1 trial group
Group A: Eligible population

Trial outcomes

Primary outcomes

1

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.

Time frame
July 2026 - November 2026
2

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.

Time frame
April 2027 - July 2027
3

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.

Time frame
December 2026 - March 2027
4

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.

Time frame
December 2026 - March 2027

Secondary outcomes

Other outcomes

Sponsors and contacts

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