Emergency and Urgent Care Indicators in Piedmont (PRIME)

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:

• Mandatory Indicators: These focus on critical issues like "boarding" (the time spent waiting for a hospital bed), overall overcrowding, wait times for clinical visits, and the management of time-dependent conditions like sepsis.
• Optional Indicators: These explore aspects such as the re-evaluation of patients in the waiting room, the use of "fast-track" assignments, and safety metrics like the frequency of falls among elderly patients.

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.