Evidence map›Paper›PMID 39420258›Full record

ArticleBMC emergency medicine2024

Measuring the crowding of emergency departments: an assessment of the NEDOCS in Lombardy, Italy, and the development of a new objective indicator based on the waiting time for the first clinical assessment.

Fabiola Signorini, Giovanni Nattino, Carlotta Rossi, Walter Ageno, Felice Catania, Francesca Cortellaro, Giorgio Costantino, Andrea Duca, Giulia Irene Ghilardi, Stefano Paglia and 4 more

Abstract read
In one paragraph

Article in BMC emergency medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
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2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Fabiola SignoriniLaboratory of Clinical Epidemiology, Department of Medical Epidemiology, Istituto Di Ricerche Farmacologiche Mario Negri IRCCS, Ranica, BG, Italy.
Giovanni NattinoLaboratory of Clinical Epidemiology, Department of Medical Epidemiology, Istituto Di Ricerche Farmacologiche Mario Negri IRCCS, Ranica, BG, Italy. giovanni.nattino@marionegri.it.
Carlotta RossiLaboratory of Clinical Epidemiology, Department of Medical Epidemiology, Istituto Di Ricerche Farmacologiche Mario Negri IRCCS, Ranica, BG, Italy.
Walter AgenoEmergency Unit, Ospedale Di Circolo Di Varese and Department of Medicine and Surgery, University of Insubria, Varese, VA, Italy.
Felice CataniaAstir S.R.L, Milan, Italy.
Francesca CortellaroAgenzia Regionale Emergenza Urgenza, Milan, MI, Italy.
Giorgio CostantinoPronto Soccorso E Medicina d'Urgenza, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, MI, Italy.
Andrea DucaAgenzia Regionale Emergenza Urgenza, Milan, MI, Italy.
Giulia Irene GhilardiLaboratory of Clinical Epidemiology, Department of Medical Epidemiology, Istituto Di Ricerche Farmacologiche Mario Negri IRCCS, Ranica, BG, Italy.
Stefano PagliaEmergency Unit, Ospedale Di Lodi, Lodi (LO), Italy.
Paolo PausilliAgenzia Regionale Emergenza Urgenza, Milan, MI, Italy.
Cristiano PeraniEmergency Unit, ASST Spedali Civili Di Brescia, Brescia, BS, Italy.
Giuseppe SechiAgenzia Regionale Emergenza Urgenza, Milan, MI, Italy.
Guido BertoliniLaboratory of Clinical Epidemiology, Department of Medical Epidemiology, Istituto Di Ricerche Farmacologiche Mario Negri IRCCS, Ranica, BG, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is no ubiquitous definition of Emergency Department (ED) crowding and several indicators have been proposed to measure it. The National ED Overcrowding Study (NEDOCS) score is among the most popular, even though it has been severely criticised. We used the waiting time for the physician's initial assessment to evaluate the performance of the NEDOCS and proposed a new crowding indicator based on this objective measure.

methodsTo evaluate the NEDOCS, we used the 2022 data of all the Lombardy EDs and compared the distribution of waiting times across the five levels of the NEDOCS at ED arrival. To construct the new indicator, we estimated the centre-specific relationship between the total number of ED patients and the waiting time of those with minor or deferrable urgency. We defined seven classes of waiting times and calculated how many patients corresponded to an average waiting time in the classes. These centre-specific cutoffs were used to define the 7-level crowding indicator. The indicator was then compared to the NEDOCS score and validated on the first six months of 2023 data.

resultsPatients' waiting time did not increase at the increase of the NEDOCS score, suggesting the absence of a relationship between this score and the effect of ED crowding on the ED capacity of evaluating new patients. The indicator we propose is easy to estimate in real-time and based on centre-specific cutoffs, which depend on the volume of yearly accesses. We observed minimal agreement between the proposed indicator and the NEDOCS in most EDs, both in the development and validation datasets.

conclusionsWe proposed to quantify ED crowding using the waiting time for physician's initial assessment of patients with minor or deferrable urgency, which increases in crowding situations due to the prioritization of urgent patients. The centre-specific cutoffs avoid the problem of the heterogeneity of the volume of accesses and organization among EDs, while enabling a fair comparison between centres.

Indexed as

CrowdingEmergency Service, HospitalWaiting ListsHumansItalyTime FactorsCrowding IndicatorEmergency DepartmentEmergency MedicineOvercrowdingWaiting Time

Identifiers

PMID39420258
PMCPMC11488125

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.