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.
Crowding Indicator
Emergency Department
Emergency Medicine
Overcrowding
Waiting Time
Journal
BMC emergency medicine
ISSN: 1471-227X
Titre abrégé: BMC Emerg Med
Pays: England
ID NLM: 100968543
Informations de publication
Date de publication:
17 Oct 2024
17 Oct 2024
Historique:
received:
17
04
2024
accepted:
09
10
2024
medline:
18
10
2024
pubmed:
18
10
2024
entrez:
17
10
2024
Statut:
epublish
Résumé
There 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. To 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. Patients' 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. We 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.
Sections du résumé
BACKGROUND
BACKGROUND
There 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.
METHODS
METHODS
To 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.
RESULTS
RESULTS
Patients' 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.
CONCLUSIONS
CONCLUSIONS
We 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.
Identifiants
pubmed: 39420258
doi: 10.1186/s12873-024-01112-9
pii: 10.1186/s12873-024-01112-9
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
196Informations de copyright
© 2024. The Author(s).
Références
Hwang U, Concato J. Care in the emergency department: how crowded is overcrowded? Acad Emerg Med Off J Soc Acad Emerg Med. 2004;11(10):1097–101.
doi: 10.1197/j.aem.2004.07.004
Kulstad EB, Sikka R, Sweis RT, Kelley KM, Rzechula KH. ED overcrowding is associated with an increased frequency of medication errors. Am J Emerg Med. 2010;28(3):304–9.
doi: 10.1016/j.ajem.2008.12.014
Sun BC, Hsia RY, Weiss RE, Zingmond D, Liang LJ, Han W, et al. Effect of emergency department crowding on outcomes of admitted patients. Ann Emerg Med. 2013;61(6):605-611.e6.
doi: 10.1016/j.annemergmed.2012.10.026
Bernstein SL, Aronsky D, Duseja R, Epstein S, Handel D, Hwang U, et al. The effect of emergency department crowding on clinically oriented outcomes. Acad Emerg Med. 2009;16(1):1–10.
doi: 10.1111/j.1553-2712.2008.00295.x
Pines JM, Hollander JE. Emergency department crowding is associated with poor care for patients with severe pain. Ann Emerg Med. 2008;51(1):1–5.
doi: 10.1016/j.annemergmed.2007.07.008
Wu D, Zhou X, Ye L, Gan J, Zhang M. Emergency department crowding and the performance of damage control resuscitation in major trauma patients with hemorrhagic shock. Acad Emerg Med Off J Soc Acad Emerg Med. 2015;22(8):915–21.
doi: 10.1111/acem.12726
McKenna P, Heslin SM, Viccellio P, Mallon WK, Hernandez C, Morley EJ. Emergency department and hospital crowding: causes, consequences, and cures. Clin Exp Emerg Med. 2019;6(3):189–95.
doi: 10.15441/ceem.18.022
Montefiori M, Cremonesi P, di Bella E. Tempi d’attesa e sovraffollamento delle strutture di primo soccorso: un’analisi empirica. SIMEU J. 2011;1:4.
Mataloni F, Pinnarelli L, Perucci CA, Davoli M, Fusco D. Characteristics of ED crowding in the Lazio Region (Italy) and short-term health outcomes. Intern Emerg Med. 2019;14(1):109–17.
doi: 10.1007/s11739-018-1881-3
Weiss SJ, Ernst AA, Derlet R, King R, Bair A, Nick TG. Relationship between the national ED overcrowding scale and the number of patients who leave without being seen in an academic ED. Am J Emerg Med. 2005;23(3):288–94.
doi: 10.1016/j.ajem.2005.02.034
Morley C, Unwin M, Peterson GM, Stankovich J, Kinsman L. Emergency department crowding: a systematic review of causes, consequences and solutions. PLoS ONE. 2018;13(8):e0203316.
doi: 10.1371/journal.pone.0203316
Badr S, Nyce A, Awan T, Cortes D, Mowdawalla C, Rachoin JS. Measures of emergency department crowding, a systematic review. How to make sense of a long list. Open Access Emerg Med OAEM. 2022;4(14):5–14.
doi: 10.2147/OAEM.S338079
McCarthy ML, Aronsky D, Jones ID, Miner JR, Band RA, Baren JM, et al. The emergency department occupancy rate: a simple measure of emergency department crowding? Ann Emerg Med. 2008;51(1):15-24.e2.
doi: 10.1016/j.annemergmed.2007.09.003
Bernstein SL, Verghese V, Leung W, Lunney AT, Perez I. Development and validation of a new index to measure emergency department crowding. Acad Emerg Med Off J Soc Acad Emerg Med. 2003;10(9):938–42.
doi: 10.1197/S1069-6563(03)00311-7
Reeder TJ, Garrison HG. When the safety net is unsafe real-time assessment of the overcrowded emergency department. Acad Emerg Med. 2001;8(11):1070–4.
doi: 10.1111/j.1553-2712.2001.tb01117.x
Boyle A, Coleman J, Sultan Y, Dhakshinamoorthy V, O’Keeffe J, Raut P, et al. Initial validation of the International Crowding Measure in Emergency Departments (ICMED) to measure emergency department crowding. Emerg Med J EMJ. 2015;32(2):105–8.
doi: 10.1136/emermed-2013-202849
Asplin BR, Rhodes KV, Flottemesch T. Is this emergency department crowded? A multicenter derivation and evaluation of an emergency department crowding scale (EDCS). Acad Emerg Med. 2004;1(11):484–5.
doi: 10.1197/j.aem.2004.02.378
Epstein SK, Tian L. Development of an emergency department work score to predict ambulance diversion. Acad Emerg Med. 2006;13(4):421–6.
doi: 10.1197/j.aem.2005.11.081
Wang H, Robinson RD, Garrett JS, Bunch K, Huggins CA, Watson K, et al. Use of the SONET score to evaluate high volume emergency department overcrowding: a prospective derivation and validation study. Emerg Med Int. 2015;2015: 401757.
doi: 10.1155/2015/401757
Weiss SJ, Rogers DB, Maas F, Ernst AA, Nick TG. Evaluating community ED crowding: the community ED overcrowding scale study. Am J Emerg Med. 2014;32(11):1357–63.
doi: 10.1016/j.ajem.2014.08.035
Weiss SJ, Derlet R, Arndahl J, Ernst AA, Richards J, Fernández-Frackelton M, et al. Estimating the degree of emergency department overcrowding in academic medical centers: results of the National ED Overcrowding Study (NEDOCS). Acad Emerg Med Off J Soc Acad Emerg Med. 2004;11(1):38–50.
doi: 10.1197/j.aem.2003.07.017
Hargreaves D, Snel S, Dewar C, Arjan K, Parrella P, Hodgson LE. Validation of the National Emergency Department Overcrowding Score (NEDOCS) in a UK non-specialist emergency department. Emerg Med J EMJ. 2020Dec;37(12):801–6.
doi: 10.1136/emermed-2019-208836
Wang H, Robinson RD, Bunch K, Huggins CA, Watson K, Jayswal RD, et al. The inaccuracy of determining overcrowding status by using the national ED overcrowding study tool. Am J Emerg Med. 2014;32(10):1230–6.
doi: 10.1016/j.ajem.2014.07.032
Van Der Linden MC, Van Loon M, Gaakeer MI, Richards JR, Derlet RW, Van Der Linden N. A different crowd, a different crowding level? The predefined thresholds of crowding scales may not be optimal for all emergency departments. Int Emerg Nurs. 2018Nov;1(41):25–30.
doi: 10.1016/j.ienj.2018.05.004
Ilhan B, Kunt MM, Damarsoy FF, Demir MC, Aksu NM. NEDOCS: is it really useful for detecting emergency department overcrowding today? Medicine (Baltimore). 2020Jul 10;99(28): e20478.
doi: 10.1097/MD.0000000000020478
Colella Y, Di Laura D, Borrelli A, Triassi M, Amato F, Improta G. Overcrowding analysis in emergency department through indexes: a single center study. BMC Emerg Med. 2022Nov;18(22):181.
doi: 10.1186/s12873-022-00735-0
Improta G, Majolo M, Raiola E, Russo G, Longo G, Triassi M. A case study to investigate the impact of overcrowding indices in emergency departments. BMC Emerg Med. 2022Aug;9(22):143.
doi: 10.1186/s12873-022-00703-8
Raj K, Baker K, Brierley S, Murray D. National Emergency Department Overcrowding Study tool is not useful in an Australian emergency department. Emerg Med Australas. 2006;18(3):282–8.
doi: 10.1111/j.1742-6723.2006.00854.x
Strada A, Bravi F, Valpiani G, Bentivegna R, Carradori T. Do health care professionals’ perceptions help to measure the degree of overcrowding in the emergency department? A pilot study in an Italian University hospital. BMC Emerg Med. 2019;19(1):47.
doi: 10.1186/s12873-019-0259-9
Darraj A, Hudays A, Hazazi A, Hobani A, Alghamdi A. The association between emergency department overcrowding and delay in treatment: a systematic review. Healthcare. 2023;11(3):385.
doi: 10.3390/healthcare11030385
Rasouli HR, Esfahani AA, Nobakht M, Eskandari M, Mahmoodi S, Goodarzi H, et al. Outcomes of crowding in emergency departments; a systematic review. Arch Acad Emerg Med. 2019;7(1):e52.
Pearce S, Marchand T, Shannon T, Ganshorn H, Lang E. Emergency department crowding: an overview of reviews describing measures causes, and harms. Intern Emerg Med. 2023. Available from: https://doi.org/10.1007/s11739-023-03239-2 . Cited 2023 Mar 17.
McCarthy ML, Zeger SL, Ding R, Levin SR, Desmond JS, Lee J, et al. Crowding delays treatment and lengthens emergency department length of stay, even among high-acuity patients. Ann Emerg Med. 2009;54(4):492-503.e4.
doi: 10.1016/j.annemergmed.2009.03.006
Ministero della salute. Regolamento recante definizione degli standard qualitativi, strutturali, tecnologici e quantitativi relativi all’assistenza ospedaliera. 2015. Available from: https://www.camera.it/temiap/2016/09/23/OCD177-2353.pdf . Cited 2023 Oct 4.
Data Protection Working Party. Article 29. Opinion 05/2014 on Anonymisation Techniques. 2014. Available from: https://ec.europa.eu/justice/article-29/documentation/opinion-recommendation/files/2014/wp216_en.pdf.
Salute M della. Linee di indirizzo nazionali sul triage intraospedaliero. Available from: https://www.salute.gov.it/portale/documentazione/p6_2_2_1.jsp?lingua=italiano&id=3145 . Cited 2023 Nov 3.
Principali statistiche geografiche sui comuni. 2023. Available from: https://www.istat.it/it/archivio/156224 . Cited 2023 Sep 14.
Nguyen TL, Collins GS, Spence J, Daurès JP, Devereaux PJ, Landais P, et al. Double-adjustment in propensity score matching analysis: choosing a threshold for considering residual imbalance. BMC Med Res Methodol. 2017;17(1):78.
doi: 10.1186/s12874-017-0338-0