Measuring emergency department crowding: comparing the NEDOCS and Fenice crowding scores against staff perception
Year: 2025
Type: article
Study design: Observational Study
Abstract: This study assesses the feasibility of collecting real-time perceptions of emergency department (ED) crowding from different professional roles and compares the recorded perceptions with two crowding indicators: the NEDOCS and the recently proposed Fenice score. We conducted a prospective observational study in an Italian university hospital. ED staff received two SMS questionnaires daily, assessing perceived crowding and workload pressure on 0–10 scales. Simultaneously, the NEDOCS and Fenice scores were recorded every 15 min. Spearman correlations, regression models, and generalized additive models were used to assess associations. Among 49 staff members, 830 valid on-shift responses were collected (response rate: 62.6%). Perceived crowding was generally high (median: 7; Q 1– Q 3: 5–9) and varied significantly by role ( p -value < 0.001), with healthcare assistants and boarding nurses perceiving the ED as more crowded and process management nurses perceiving it as less crowded. The Fenice and NEDOCS scores correlated strongly with perceived crowding ( ρ : 0.71 and 0.69; p value = 0.06) and moderately with workload pressure ( ρ < 0.60). The Fenice score explained slightly more variance in perceived crowding ( R 2 : 0.65 vs. 0.59). While the correlation between the two scores in the study ED was high ( ρ : 0.85), a wide range of correlation coefficients emerged in a cohort of 83 Italian EDs (average ρ : 0.80; min–max: 0.24–0.99; Q 1– Q 3: 0.73–0.93). Real-time monitoring of ED staff perceptions is feasible and informative. Both the NEDOCS and Fenice scores correlate well with staff perception, but the simplicity and fully automatable implementation of the Fenice score make it a promising alternative to be evaluated in future studies.
Source: Internal and Emergency Medicine
Authors: Riccardo Boverio, Fabiola Signorini, Carlotta Rossi, Roberta Irene Maria Bellini, Cristian Zanelli, Giulia Irene Ghilardi, Daniela Zatelli, Giovanni Nattino, Guido Bertolini, the FENICE network, Michela Alciati, Madalina Maria Amuntencei, Simona Arcidiacono, Marco Bidoggia, Patrizia Boido, Giada Bruno, Giuseppe Cangemi, Lara Caravella, Gianluca Cascina, Federico Castello, Pietro Cerasa, Salvatore Conte, Chiara Cordero, Monica Cosby, Davide Costagliola, Manuela Di Buono, Stefania Di Santo, Monica Doglio, Carmen Dumitrescu, Martina Fendoni, Anita Ferranti, Roberta Ferraro, Guido Gianluca, Liryana Lima, Aurora Litta, Sonia Loddo, Chiara Macario, Victor Malatesti, Chiara Mattiazzo, Enrica Mensi, Francesca Minetti, Riccardo Morrone, Alexandru Nistor, Matteo Nocito, Lorenzo Noto, Maria Teresa Palumbo, Iacoban Paraschiva, Cinzia Pareti, Vadis Pretato, Uberti Rana, Alessia Ri, Manuela Salera, Vincenzo Savino, Claudia Sosa, Laura Tirri’, Carla Vigliano, Elisabetta Vigutto, Martina Villanova, Lila Xesika, Giulia Zunino
Language: English
Subfield: Emergency Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,790
Funders: European Commission, Regione Piemonte
OpenAlex ID: W4417276760
