Abstract
Background
Extending the time patients spend in the emergency department (ED) not only diminishes the quality of care but also heightens the potential for harm and adversely impacts patient satisfaction. However, there exists a dearth of accessible information regarding the length of stay (LOS) in emergency departments and the factors associated with it in Indonesia. This study aims to analyze the factors that influence the LOS of patients in the emergency department of a public hospital in Padang, Indonesia.
Methods
This research design is a cross-sectional approach. The sample was patients who visited the ED in a tertiary public hospital in Padang (n = 328). The data collected from the medical records included length of stay, mode of arrival, case type, triage scale, diagnostic examination, specialist consultation needs, and needs for admission. Data analysis was performed using the chi-square statistical test and binary logistic regression.
Results
The percentage of patients with LOS > 6 h in the emergency department was 29 %. There was a significant relationship between the triage scale, diagnostic tests, and the need for hospitalization with LOS (p < 0.05). The results of the multivariate analysis showed that the case type and the need for admission to hospitalization influence 12.4 % of LOS in ED.
Conclusion
This study enriches our comprehension of the variables exerting the most substantial impact on the average duration of stay in the emergency department of a hospital in Indonesia. The findings will assist policymakers in crafting enduring strategies to optimize patient flow in the emergency department.
Keywords: Emergency, Length of stay, Nursing, Triage
Introduction
The emergency department (ED) is the most essential and vital service because it is the first point of contact for all hospital patients needing emergency assistance.1 The high demand for ED services is a global issue with an imbalance between the number of patients, capacity, and facility availability in hospitals, which affects the patient flow in the ED.2 Unlike inpatient units with predetermined capacities, the ED can receive patients beyond its designated capacity, leading to overcrowding.3 The increasing demand for care and complex management procedures can result in extended waiting times and length of stay in the ED.4 Most patients visiting the ED have complex conditions and more comorbidities than the general population.5 When the ED becomes overwhelmed with a high number of patients, the ability of healthcare professionals to respond to emergencies may be questioned.6 Additionally, during increased visits, patients may need more timely and appropriate care.7
Studies have found that managing patients' length of stay in the ED can improve the quality and performance of ED services in hospitals.8 Prolonged length of stay has been identified as impacting increased mortality rates, extended hospital length of stay (HLOS), delayed interventions, medication errors, and increased infection rates among ED patients.2 Therefore, evaluating the factors influencing prolonging the length of ED stay is essential.
The treatment process in the ED starts with patient admission, followed by triage assessment, diagnosis, initial treatment, and the decision for discharge or hospitalization.9 Asplin et al. developed a conceptual model that characterizes the ED with input, throughput, and output elements.10 Each element has been identified as a significant factor influencing the length of stay in the ED.4 Input factors refer to patient visit-related factors, including mode of arrival, case type, and patient triage scale.4,11 This factor is identified during patient arrival, namely during triage.11 Throughput factors refer to internal factors in the ED service process, including specialist consultations and diagnostic examinations conducted on patients.3,4,11 The number of procedures, examinations, and consultations contribute to the long waiting time for patients. The consultation process is related to the availability of specialists when a consultant is needed. In contrast, the diagnostic examination process is associated with the time of sampling and processing of the results.4 Output factors affect patients' discharge from the ED, such as the need for hospitalization.3,4 The output factor is often associated with the unavailability of space in the inpatient unit, which causes patients to wait longer in the emergency room.10 (Fig. 1).
Fig. 1.
Conceptual framework representing the areas of a patient's journey through the emergency department.
Some governments in different countries have adopted a 4-hour rule as the standard time for ED patient length of stay, while others have adopted a 4–12-hour rule.12 Public hospital's ED in Padang has established a quality indicator standard that patients should only stay in the ED for 6 h without compromising the quality of care. In Indonesia, there currently needs to be clear guidance on improving the quality of care and smooth patient flow in the ED, and existing regulations require being well-implemented, making it difficult to determine the factors influencing patient length of stay in the ED.4 Based on these issues, it is essential to study the factors related to the Length of Stay (LOS) of patients in the Emergency Department (ED).
Material and methods
The present study was a cross-sectional design using a retrospective method that involved medical record data in the form of summary data from patients in the ED. The data were collected to investigate the factors influencing the LOS of patients in the ED, including mode of arrival, triage, case type, diagnostic examination, specialist consultation needs, and hospitalization needs.
The study was conducted in a tertiary public hospital in Padang, West Sumatra. This hospital is the primary referral center from Sumatera, Bengkulu, Jambi province. Patients who visit the ED undergo triage (using the ATS 5-level triage system). After the triage process, patients are transferred to resuscitation/medical/pediatric/surgical/obstetrics rooms to receive appropriate treatment. Subsequently, patients undergo an initial assessment, intervention, and diagnostic examinations. A specialist/consultant team then reviews the patient's condition until a decision is made regarding KRS (patient discharge), MRS (hospitalization), surgery, or other specific procedures. The population in this study included all patients who visited the ED in a tertiary public hospital in Padang, West Sumatra. The results of medical record data for patients from 1 to 30 March 2023 indicated a total of 2234 visits. Using the Isaac and Michael sample formula, a sample size of 328 data points was obtained. The inclusion criteria for this study included all emergency patients who visited in March 2023. The exclusion criteria included patients who died upon arrival, patients who left or were forced to leave against medical advice, and incomplete medical record data. The sampling technique used in this study was systematic random sampling, where the first sample was randomly selected, and subsequent samples were selected based on a multiple of 6 intervals from the registration number of the patient selected as the sample.
The data collected in this study were secondary data obtained from medical records in summary data from patients who visited the ED of a tertiary public hospital in Padang, West Sumatra, in March 2023. The collected data included length of stay, mode of arrival, case type, triage scale, diagnostic examination, specialist consultation needs, and needs for admission to hospitalization. Initially, the researcher obtained permission from the head of the ED unit to conduct the study and explained the purpose and objectives of the research. The researcher then selected patients in the sample based on the inclusion and exclusion criteria. Afterward, the researcher transferred the data to a data collection table. Once data collection was complete, further data analysis was conducted to determine the factors influencing patients' length of stay in the ED.
The data was analyzed using the software. The description of each variable was obtained through descriptive analysis of frequency distribution. The relationship between the independent and dependent variables was determined using Chi-Square analysis. Once the relationship between variables was determined, binary logistic regression analysis was conducted to identify factors significantly influencing ED LOS.
The Research and Health Ethics Committee approved the research with reference number LB.02.05/5.7/259/2023. The study was deemed ethically appropriate according to the WHO 2011 standards. Researchers maintained the identity and confidentiality of patient data by creating a patient identification code. Informed consent from all patients was obtained and they were assured patient data will only be used for research purposes. All guidelines as per the Declaration of Helsinki and good clinical practice guidelines were followed.
Results
Characteristic respondents and LOS
A total of 328 patient records were reviewed. It was found that the percentage of patients who had LOS > 6 h (29 %) and ≤ 6 h (71 %), and most of the patients arrival bypass (59.1 %), cases non-trauma (80.8 %), categorized into triage scale 3 (64.9 %), patients receive specialist consultation (100 %), patients receive diagnostic examinations (67.4 %), and are admitted to be hospitalized (74.4 %) (Table 1).
Table 1.
Characteristic respondents and LOS (n = 328).
| Variable | f | % |
|---|---|---|
| Length of stay (hours) | ||
| > 6 | 95 | 29 |
| ≤ 6 | 233 | 71 |
| Input | ||
| Mode of arrival | ||
| Bypass | 194 | 59.1 |
| Arrival by system | 134 | 40.9 |
| Cases type | ||
| Non-trauma | 265 | 80.8 |
| Trauma | 63 | 19.2 |
| Triage scale | ||
| 1 | 19 | 5.8 |
| 2 | 42 | 12.8 |
| 3 | 213 | 64.9 |
| 4 | 54 | 16.5 |
| Throughput | ||
| Specialist consultation | ||
| Receive specialist consultation | 328 | 100 |
| No specialist consultation | 0 | 0 |
| Diagnostic examinations | ||
| Receive diagnostic examinations | 221 | 67.4 |
| No diagnostic examinations | 107 | 32.6 |
| Output | ||
| Need for admission | ||
| Discharged | 84 | 25.6 |
| Inpatient | 244 | 74.4 |
LOS and related factors
The results of the analysis showed that the triage scale, diagnostic tests, and need for admission had a significant relationship with LOS (p < 0.05). There was no significant relationship between the arrival method, case type, and specialist consultation with LOS (p > 0.05) (Table 2). Variables that contributed significantly to the lengthening of LOS >6 h were patients with triage scale 3 (75.8 %), patients who consulted specialists (100 %), and patients who were disposed to be hospitalized (90.5 %) (Table 3).
Table 2.
Relationship between length of stay and independent variables (n = 328).
| Variable independent | LOS (hours) |
P- value |
||||
|---|---|---|---|---|---|---|
| ≤6 |
>6 |
Total (f) | ||||
| f | % | f | % | |||
| Input | ||||||
| Referral type | 0.963 | |||||
| Bypass | 56 | 58.9 | 138 | 59.2 | 194 | |
| Referral by system | 39 | 41.1 | 95 | 40.8 | 134 | |
| Cases type | 0.246 | |||||
| Trauma | 41 | 65.1 | 22 | 34.9 | 63 | |
| Non-trauma | 192 | 72.5 | 73 | 27.5 | 265 | |
| Triage scale | 0.012a | |||||
| 1 | 13 | 68.4 | 6 | 31.6 | 19 | |
| 2 | 31 | 73.8 | 11 | 26.2 | 42 | |
| 3 | 141 | 66.2 | 72 | 33.8 | 213 | |
| 4 | 48 | 88.9 | 6 | 11.1 | 54 | |
| Throughput | ||||||
| Specialist consultation | – | |||||
| Receive specialist consultation | 233 | 71 | 95 | 29 | 328 | |
| No specialist consultation | 0 | 0 | 0 | 0 | 0 | |
| Diagnostic examinations | 0.004a | |||||
| No diagnostic examinations | 82 | 76.6 | 25 | 23.4 | 107 | |
| Receive diagnostic examinations | 151 | 68.3 | 70 | 31.7 | 221 | |
| Output | ||||||
| Need for admission | 0.000a | |||||
| Discharged | 75 | 89.3 | 9 | 10.7 | 84 | |
| Inpatient | 158 | 64.8 | 86 | 35.2 | 244 | |
Analysis chi-square, statistically significant at p < 0.05.
Table 3.
Factors influencing LOS in ED.
| Variable | B | P-value | Exp(B) | 95 % Cl for Exp (B) |
Nagelkerke R Square | |
|---|---|---|---|---|---|---|
| Lower | Upper | |||||
| Input | 0.124 | |||||
| Cases type | 1054 | 0.003 | 2868 | 1422 | 5782 | |
| Output | ||||||
| Need for admission | 1928 | 0.000 | 6873 | 3010 | 15.691 | |
Multivariate analysis was performed on four variables (case type, triage scale, specialist consultation, diagnostic examination, and need for admission) according to the requirements of logistic regression analysis, namely p-value < 0.25. Furthermore, an analysis was carried out with a binary logistic regression test with the backward LR method. The test results were obtained through 3 steps, with the final result being that two variables significantly influenced LOS, where the value of the need for hospitalization had the most significant p-value p = 0.000 and the type of case p = 0.003 (p-value <0.05).
The results of the multivariate analysis showed that two variables affected LOS in the ED, contributing to Nagelkerke R Square 0.124 = 12.4 %. This means that 12.4 % of LOS in the ED is influenced by the type of case and the need for admission to hospitalization. From the analysis results, the highest value of Exp (B) was obtained by the variable need for admission of 6.873, meaning that patients who needed admission to hospitalization were at risk of experiencing LOS lengthening by 6.873 times compared to patients discharged. The B value (natural logarithm) of 6.873 = 1.928; because the B value is positive, the need for admission to hospitalization has a positive relationship with LOS in the ED. So, the dominant factor affecting the LOS of patients in the ER is the output factor, namely, the need for admission.
Discussion
Waiting time is the most important indicator that directly affects patient satisfaction and the ED performance.13 This study discusses the factors that influence the LOS in the ED, which are classified into input, throughput, and output factors. The research findings indicate that the factor significantly affecting LOS is the inpatient factor.
This research showed that several hospitals in Indonesia's ED still exist where extended LOS occurrences exist. In this hospital, a standard has been set in the quality of service indicators that the length of stay for patients in the ED should be at most 6 h, calculated from the time they arrive at the ED until they are recorded as leaving. The extended LOS in the ED is caused by several factors that lead to patients staying longer. In this study, the extended LOS in the ED can be attributed to the lack of timeliness in the service flow within the ED. The prolonged LOS in the ED is associated with inefficient management, untimely care, and inadequate adherence to standard operating procedures (SOPs). Furthermore, it relates to input, throughput, and output factors. The length of patient treatment is an indicator that reflects the overall quality and efficiency of the hospital's ED services.14
Input factors
Based on the LOS model influenced by input, throughput, and output factors, hospitals with higher-level EDs have more significant input factors than hospitals with lower levels.4 Each factor has been identified as a significant influencer of LOS in the ED. The input factors refer to patient visits and the readiness of the ED, including the mode of arrival, case types, patient triage scale, the quantity and quality of healthcare personnel, and hospital facilities. However, in this study, the investigated input factors are only related to the mode of arrival, case types, and triage scale. The research was conducted in a tertiary public hospital in Padang, West Sumatra. It is one of the most comprehensive hospitals in Indonesia under the Ministry of Health. The hospital has 76 healthcare personnel, including doctors, nurses, midwives, and pharmacists.
Additionally, high-level ED hospitals receive a more significant number of critically ill patients, leading to longer LOS.14 The research results show that the triage scale factor relates to LOS (P < 0.05). Patients with higher acuity levels or more critical and life-threatening conditions are prioritized over patients with lower acuity levels. High-acuity patients are treated as soon as possible and receive faster decisions regarding further care. However, high-acuity patients also require more in-depth assessments and diagnostic tests, which result in a longer time spent in the ED.15 These findings are consistent with previous studies by Suriyawongpaisal et al. and Kusumawati et al., which found a significant relationship between LOS and patients' triage scale/acuity level.4,12 Another study by Nhdi et al. also found that patients with higher triage levels spend more time than lower-level patients due to their condition requiring minimal waiting time for initial assessment but more time and resources for treatment.13 Sarıyer et al. stated that patients with urgent conditions have a short waiting time for assessment but experience longer treatment times.16
The research findings also indicate that patients with triage scale three experience a 75.8 % longer LOS. This is because patients with a triage scale of 3 often have unclear clinical pictures (whether to be admitted or discharged), requiring observation, examinations, and more prolonged treatment in the ED.16
Throughput factors
The research findings indicate that diagnostic examinations are the throughput factor related to LOS. Patients undergoing diagnostic examinations experience a LOS of more than 6 h by 31.7 %. Although the hospital where this research was conducted is a tertiary public hospital in Padang and one of the most comprehensive hospitals in Indonesia under the Ministry of Health, equipped with complete diagnostic equipment and 76 healthcare personnel, including doctors, nurses, midwives, and pharmacists, the prolonged length of stay (LOS) cannot be avoided. Diagnostic examinations are required for 90 % of patients treated in the ED, and this factor often contributes to prolonged LOS in ED.11 These results are consistent with the studies by Driesen et al. and Suriyawongpaisal et al., which identified diagnostic examinations as contributing factors to prolonged LOS in the ED.5,12 Patients with multiple comorbidities often experience prolonged LOS due to diagnostic examinations, which can be prevented promptly. Prolonged diagnostic examinations are associated with laboratory sample processing, the need for more computerized systems, inadequate laboratory staff, and the absence of specific indicators for samples originating from the ED requiring immediate results.4 Moreover, unnecessary requests for diagnostic examinations can increase the workload in the laboratory and indirectly affect patient LOS in the ED.3 To reduce waiting time for patients requiring diagnostic examinations, early requests can be made as soon as the symptoms are known, faster transportation for examinations, faster and more efficient reporting systems, and specific examinations performed for ED patients.12 Patients with multiple comorbidities often experience prolonged lengths of stay (LOS) due to diagnostic examinations. This can be prevented by promptly making a disposition if there are indications for hospital admission. Conversely, patients who do not require hospitalization but still need some diagnostic tests can be conducted through outpatient units.17,18
Output factors
The results of this study indicate that output factors are related to prolonged length of stay (LOS) in the Emergency Department (ED), specifically the need for hospitalization (p < 0.05). This study revealed that 31.7 % of patients needed for hospitalization experienced a LOS longer than 6 h. Multivariate analysis also showed that hospitalized patients significantly influenced the LOS in the ED of the public hospital in Padang. This finding is consistent with the study by Paling et al., which found that ED patients admitted to the hospital had longer waiting times than non-admitted patients.19 Suriyawongpaisal et al. also found a relationship between hospitalized patients and LOS, indicating bed blockage in inpatient units.12 Similarly, Hosseininejad et al. found that decisions regarding continued patient care or disposition time significantly affected the prolongation of LOS in the ED.20
Patients who have completed their treatment in the ED then undergo disposition or decision-making regarding their care. The waiting time for patients who have decided to be admitted to the hospital is known as boarding time, during which patients wait for bed availability and inpatient unit preparation.13 This affects the focus of healthcare providers, as they must provide care to newly arrived patients while still monitoring patients waiting for hospital admission.20 These patients are rarely reassessed, even though their condition may change at any time, thus reducing the efficiency of the ED.11 Patients in general and referral hospitals often stay for hours or even days after being decided for hospitalization.3 This is related to bed availability, procedures, and the preparation for transferring to inpatient units.12 Mashao et al. also found that bed availability in inpatient units contributes to prolonged LOS, reducing patient output from the ED.11 Hospitals with high-level EDs require a more significant number of beds, mainly due to admitting critically ill patients.14
Measures that can be taken include removing barriers to patient transfer to inpatient units, standardizing the transfer process, and avoiding non-urgent care in the ED. These steps can effectively reduce LOS in the ED.3 Further studies are needed to develop more comprehensive solutions that also address units outside the ED.
Conclusion
Evaluation of the factors causing prolonged LOS of patients in the ED is one of the solutions to help improve the quality of care and patient satisfaction. The results of this study showed that LOS in the ED has a significant relationship with the triage scale, diagnostic tests, and the need for hospitalization. The results of the multivariate analysis showed that the case type and the need for admission to hospitalization influence 12.4 % of LOS in ED. In addition, the nurse's role, in this case, is crucial to monitor and ensure patient care in the emergency department is efficient and timely. The findings of this study contribute to our understanding of the critical factors that have a significant impact on the length of stay (LOS) in the Emergency Department (ED) of a hospital in Indonesia. This information can be valuable for policymakers in formulating strategic plans to enhance the flow of patients in the ED and improve overall efficiency.
However, it's essential to acknowledge the limitations of this research. Firstly, the data source is confined to a single institution, restricting the generalizability of results to other healthcare facilities. Secondly, the retrospective nature of the study, utilizing secondary hospital data, means researchers relied on variables recorded in the ER data summary. Most previous studies were conducted as retrospective studies; it is hoped that future studies can use real-time primary data to discover other factors that cause delays in the flow of emergency department services.
Patients/ Guardians/ Participants consent
Patients informed consent was obtained.
Ethical clearance
Institute/hospital ethical clearance certificate was obtained.
Source of support
Nil.
Disclosure of competing interest
The authors have none to declare.
Acknowledgment
The author acknowledges the research and community service institution Universitas Andalas for helping to write this manuscript. The author is thankful to Faculty of Nursing Universitas Andalas for financial support (Contract Number: 104/SPK/PTN-BH/Fkep/Unand-2023).
References
- 1.El-Guindy H., El-Shahate M., Allah N.A. Enhancing nurse Interns' knowledge and practice regarding triage at emergency units during COVID-19 pandemic. Assiut Scientific Nursing Journal. 2021;9(27):10–20. [Google Scholar]
- 2.Faidh Ramzee A., El-Menyar A., Asim M., et al. The impact of emergency department length of stay on the outcomes of trauma patients requiring hospitalization: a retrospective observational study. World Journal of Emergency Medicine. 2023;14(2):96. doi: 10.5847/wjem.j.1920-8642.2023.016. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Esmaeili R., Aghili S.M., Sedaghat M., Afzalimoghaddam M. Causes of prolonged emergency department stay; a cross-sectional action research. Advanced Journal of Emergency Medicine. 2018;2(2):e18. doi: 10.22114/AJEM.v0i0.58. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Kusumawati H.I., Magarey J., Rasmussen P. Analysis of factors influencing length of stay in the Emergency Department in public hospital, Yogyakarta, Indonesia. Australasian Emergency Care. 2019;22(3):174–179. doi: 10.1016/j.auec.2019.06.001. [DOI] [PubMed] [Google Scholar]
- 5.Driesen B.E.J.M., Van Riet B.H.G., Verkerk L., Bonjer H.J., Merten H., Nanayakkara P.W.B. Long length of stay at the emergency department is mostly caused by organisational factors outside the influence of the emergency department: a root cause analysis. PLoS One. 2018;13(9):1–15. doi: 10.1371/journal.pone.0202751. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Simkhada P., Acharya S., Lama R., Dahal S., Lohala N., Thapa A. Emergency stay duration of patients in emergency department of a tertiary care hospital in Nepal: a descriptive cross-sectional study. J Nepal Med Assoc JNMA. 2020;58(222):84–87. doi: 10.31729/jnma.4806. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Yang Z., Song K., Lin H., Li C., Ding N. Factors associated with emergency department length of stay in critically Ill Patients: a single-center retrospective study. Med Sci Mon Int Med J Exp Clin Res. 2021;27:1–9. doi: 10.12659/MSM.931286. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Gurazada S.G., Gao S., Burstein F., Buntine P. Predicting patient length of stay in Australian emergency departments using data mining. Sensors. 2022;22(13):1–15. doi: 10.3390/s22134968. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Otto R., Blaschke S., Schirrmeister W., Drynda S., Walcher F., Greiner F. Length of stay as quality indicator in emergency departments: analysis of determinants in the German Emergency Department Data Registry (AKTIN registry) Intern Emerg Med. 2022;17(4):1199–1209. doi: 10.1007/s11739-021-02919-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Asplin B.R., Magid D.J., Rhodes K.V., Solberg L.I., Lurie N., Camargo C.A. A conceptual model of emergency department crowding. Ann Emerg Med. 2003;42(2):173–180. doi: 10.1067/mem.2003.302. [DOI] [PubMed] [Google Scholar]
- 11.Mashao K., Heyns T., White Z. Areas of delay related to prolonged length of stay in an emergency department of an academic hospital in South Africa. African J Emerg Med. 2021;11(2):237–241. doi: 10.1016/j.afjem.2021.02.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Suriyawongpaisal P., Kamlungkuea T., Chiawchantanakit N., et al. Relevance of using length of stay as a key indicator to monitor emergency department performance: case study from a rural hospital in Thailand. EMA - Emerg Med Australasia. 2019;31(4):646–653. doi: 10.1111/1742-6723.13254. [DOI] [PubMed] [Google Scholar]
- 13.Nhdi N Al, Asmari H Al, Thobaity A Al. Investigating indicators of waiting time and length of stay in emergency departments. Open Access Emerg Med. 2021;13:311–318. doi: 10.2147/OAEM.S316366. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Ahmed A.A., ISA, MG, SSS, & TT Length of stay in the emergency department and its associated factors at Jimma medical center, southwest Ethiopia. Open Access Emerg Med. 2020;12:227–235. doi: 10.2147/OAEM.S254239. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Lee K.S., Min H.S., Moon J.Y., et al. Patient and hospital characteristics predict prolonged emergency department length of stay and in-hospital mortality: a nationwide analysis in Korea. BMC Emerg Med. 2022;22(1):1–12. doi: 10.1186/s12873-022-00745-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Sarıyer G., Ataman M.G., Kızıloğlu İ. Analyzing main and interaction effects of length of stay determinants in emergency departments. Int J Health Pol Manag. 2020;9(5):198–205. doi: 10.15171/ijhpm.2019.107. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Yoon P., Steiner I., Reinhardt G. Analysis of factors influencing length of stay in the emergency department. Can J Emerg Med. 2003;5(3):155–161. doi: 10.1017/s1481803500006539. [DOI] [PubMed] [Google Scholar]
- 18.van der Veen D., Remeijer C., Fogteloo A.J., Heringhaus C., de Groot B. Independent determinants of prolonged emergency department length of stay in a tertiary care centre: a prospective cohort study. Scand J Trauma Resuscitation Emerg Med. 2018;26(1):1–9. doi: 10.1186/s13049-018-0547-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Paling S., Lambert J., Clouting J., González-Esquerré J., Auterson T. Waiting times in emergency departments: exploring the factors associated with longer patient waits for emergency care in England using routinely collected daily data. Emerg Med J. 2020;37(12):781–786. doi: 10.1136/emermed-2019-208849. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Hosseininejad S.M., Aminiahidashti H., Pashaei S.M., et al. Determinants of prolonged length of stay in the emergency department; a cross-sectional study. Arch Acad Emerg Med. 2019;7(1):1–6. [PMC free article] [PubMed] [Google Scholar]