Abstract
The purpose of this study was to reduce the length of stay (LOS) for patients stranded in the emergency department (ED) of a Grade III A hospital in China, and to improve patient flow and increase bed capacity. We utilized a pre-/postintervention design and employed the Six Sigma methodology, which is based on the DMAIC cycle (define, measure, analyze, improve, and control), to evaluate and improve the existing process. Data from 18,631 patients who were stranded in the ED were collected and analyzed. The median LOS for stranded patients decreased from 17.21 (6.22, 27.36) hours to 13.45 (5.56, 25.85) hours (P < .05). Similarly, the median LOS for admitted patients decreased from 19.64 (7.77, 27.68) hours to 15.92 (6.19, 26.24) hours (P < .05). The median LOS for patients with an ED triage Level IV decreased from 16.15 (5.80, 26.62) hours to 12.59 (5.20, 24.97) hours (P < .05). In addition, the average hospitalization days of hospitalized patients decreased from 0.92 days to 0.82 days (P < .05). Furthermore, the bed utilization rate increased from 66.79% to 72.29% (P < .05). The number of bed turnovers in the ED resuscitation room increased from 20.30 to 21.96 (P < .05). We had effectively met our goal of minimizing ED patient LOS. Six Sigma method can effectively shorten patient LOS by measuring and analyzing the key factors affecting patient LOS, and by implementing measures such as strict implementation of emergency classification and triage system, establishment of multidisciplinary cooperative team, reasonable allocation of human resources, information management of bed resources, and improvement of performance appraisal scheme to improve and control the effectiveness of patient LOS.
Keywords: crowding, emergency department, emergency department length of stay, resuscitation room, Six Sigma
1. Introduction
Stranding of patients in the emergency department (ED) has become a global public health issue.[1,2] The problem of stranded patients in the ED refers to the situation where patients who require hospitalization are forced to remain in the ED for an extended period of time after completing assessment, diagnosis, and treatment.[3] Prior studies have demonstrated that a longer length of stay (LOS) can have negative effects on patients, including delays in assessment and receiving necessary care.[4–6] Longer LOS is associated with an increased frequency of errors, including medication errors. It also leads to decreased patient satisfaction, reduced willingness to seek medical treatment, and poorer outcomes, including increased in-hospital mortality. The negative effects on staff have been identified, which include increased stress and exposure to violence.[7] Additionally, during times of ED overcrowding, there has been observed nonadherence to best practice guidelines.[8] Reducing LOS is becoming a pressing issue in global healthcare systems.
Based on the reality of China’s large population and the increasingly prominent aging problem, there is a significant contradiction between the limited availability of medical resources and the high demand for these resources in the ED.[9] The stranding of critically ill patients in ED not only prevents existing patients from receiving high-quality medical services but also increases the waiting time for new patients,[10] severely hindering the effective operation of emergency centers. This evidence highlights the urgent need for healthcare organizations to improve their processes and strive for a higher quality of care. Among several process improvement strategies, ranging from simulation models to quality management principles, Six Sigma (SS) has proven to be a reliable and promising approach in healthcare settings.[11–14]
SS is a structured and systematic problem-solving management method which achieves by improving service processes and managing quality defects. The methodology is based on the DMAIC cycle, which consists of 5 stages: define, measure, analyze, improve, and control.[15] In January 2022, the hospital’s executive management team identified shortening the LOS as a targeted area for improvement. Our objective was to evaluate the effect of the SS methodology on the LOS for stranded patients in the ED.
2. Methods
2.1. Study design and data sources
This is a single-center retrospective study with data prospectively collected. The study was conducted in the resuscitation room of the ED of Fujian Medical University Union Hospital in China. The hospital, situated in Fuzhou, Fujian Province, is a public Grade III general hospital with a capacity of 2500 beds. This study was approved by the Medical Ethics Review Committee of Fujian Medical University Union Hospital (ethics approval number: 2023KY219).
The hospital’s information system is used to collect data on the demographic and clinical variables associated with each patient. The information included patient gender, age, LOS (the time difference between when patients left the ED and when they entered), preliminary diagnosis, patient endpoints, admission department, and other relevant variables. We included patients with complete data on standard ED resuscitation room care from January 2021 to October 2022. However, we excluded patients with significant data flaws, such as missing standard LOS, primary diagnosis, endpoint, admission department, and other similar issues. In addition, we excluded frequent users of the ED during the data analysis process. We found that frequent users were more likely to have abnormal conditions, resulting in either a shorter or longer LOS. After reviewing the relevant literature,[16–18] we have excluded those studies and are planning to conduct further research on the topic in our future work. Data were divided into 2 distinct groups of patients who visited the resuscitation unit of the ED. The first group was observed before the implementation of the SS, from January 1 to December 31, 2021. The second group was observed after the implementation of the SS, from January 1 to October 24, 2022. The first group included 9904 patients, while the second group included 8727 patients. Considering that the ED of the hospital where the study was conducted has experienced a significant influx of pneumonia patients due to the COVID-19 outbreak since November 2022,[19] data collected after October 25th, 2022, were excluded to prevent any potential bias in the study findings. This article adheres to the stated list of observational research report items provided by STROBE-MR.[20]
Statistical analysis was performed using the SPSS software package (version 26, SPSS Inc., Chicago, IL). The measurement data were tested for normality. The continuous variables involved did not conform to a normal distribution, so they were presented in the form of a median interquartile interval, that is, M(P25, P75), and the rank sum test was used for comparison. Count data are expressed in frequency or proportion and compared using the Chi-square test. All the P values reported were 2-tailed, and a significance level of P < .05 was considered statistically significant.
2.2. DMAIC cycle
The core of SS is to improve work efficiency, patient satisfaction, and trust. It includes 5 steps: define, measure, analyze, improve, and control. In the definition phase, the project objectives are defined, specific issues are addressed, and processes are improved. In the measurement phase, the indicators that truly require improvement and can be accurately measured are assessed. During the analysis phase, we evaluated patients who were staying in the ED to identify the root cause of prolonged LOS. During the improvement phase, the root cause identified in the analysis phase should be addressed using the appropriate program. Finally, in the control stage, the existing improvement process is strengthened and adjusted to maintain efficiency in the process of improvement.
2.2.1. Define phase.
The primary objectives of our study were to reduce the LOS for patients in the ED and improve the utilization rate of ED beds. In order to implement this study smoothly, we set up an emergency department length of stay (EDLOS) management team. The team consisted of administrators from the medical department of Fujian Medical University Union Hospital and clinicians from the ED, all of whom had experience in hospital management.
2.2.2. Measure phase.
The primary outcome of interest in this study was the EDLOS. This included the median LOS for patients in the resuscitation room, the ratio of LOS, the LOS for patients with different destinations, and the LOS for patients with different triage levels. The secondary outcomes included the average LOS for discharged patients, the average LOS for hospitalized patients, the utilization rate of ED beds, and the bed turnover rate for ED beds.
EDLOS refers to the total amount of time that elapses from the moment a patient arrives at the ED (either for triage or check-in) until they leave. Since the LOS in this study were skewed, they were described using the median LOS. LOS was divided into 6 groups: LOS ≤ 6h, 6h < LOS ≤ 12h, 12h < LOS ≤ 18h, 18h < LOS ≤ 24h, 24h < LOS ≤ 30h, and LOS > 30h. The nurse categorized patients into 1 of 4 broad groups using the national ED prescreening triage scale: Level I (critical), Level II (urgent), Level III (acute), and Level IV (suburgent). Patient endpoints were categorized into 4 options: admission, discharge, transfer to another hospital, and death.
The average LOS for discharged patients was calculated by dividing the total number of bed days occupied by discharged patients in the resuscitation room of the ED by the number of discharged patients. The average LOS for inpatients is calculated by dividing the total number of bed days occupied by inpatients in the resuscitation room of the ED by the number of inpatients. The bed utilization rate is calculated by dividing the number of discharged patients by the number of beds and then multiplying it by the number of days in the ED resuscitation room. Bed turnover refers to the ratio of discharged patients to the number of beds in the resuscitation room of the ED.
2.2.3. Analyze phase.
The admission of patients to the ED resuscitation room is the result of complex interactions among multiple systems and factors. After organizing the team members for a brainstorming session, we discussed and analyzed the key factors that affect the duration of emergency hospital stays.
2.2.3.1. Increase in nonemergency patients.
Due to a lack of medical knowledge and easy access to medical care, some patients with nonurgent conditions often mistakenly believe that their condition is urgent. As a result, they go to a public Grade III general hospital and expect to be seen immediately.
2.2.3.2. Patients with complex and multidisciplinary diseases are easily rejected.
Emergency patients are often critically ill with complex medical conditions that involve multiple systems. Disputes may arise regarding the attribution of a specialty, which can lead to an extension of the EDLOS. With the recent advancements in specialization, there may be cognitive disparities among experts in various disciplines when it comes to disease diagnosis, treatment methods, and disposal capabilities.[21]
2.2.3.3. ED staffing is inadequate.
The allocation of emergency medical staff was unreasonably structured, and they had to undertake heavy daily workload and high work intensity.[22]
2.2.3.4. The beds of hospital wards are overcrowded.
Public Grade III general hospital experiences a high volume of patients throughout the year. As a result, there are certain challenges, such as limited bed availability in the wards, high bed utilization in the emergency rooms,[23] and a high turnover rate among medical staff.[24]
2.2.3.5. Patient’s own factors.
Patients are concerned about their own medical conditions, lack of trust in lower-level medical institutions, or personal preference for specific medical facilities.
2.2.4. Improve phase.
2.2.4.1. Strictly implement the grading and triage system for emergency care.
According to the international pretest triage standard, patients’ conditions are objectively and scientifically graded using the Modified Early Warning Score (MEWS), which is based on “3 zones and 4 levels.” The triage doctors and nurses were trained to learn and master the rules and standards of the MEWS scoring system.[25] Level I patients who were in danger and Level II patients who were critically ill were transferred to the red zone for immediate treatment. Level III patients, who were not in life-threatening conditions but had unstable vital signs, were directed to the yellow zone for immediate medical attention. Level IV patients who were not in an emergency situation were advised to wait in the designated green zone.
2.2.4.2. Set up a multidisciplinary team.
A multidisciplinary team of experts evaluate the patient’s clinical symptoms and the results of the physical examination. This is particularly important for patients whose diagnosis is unclear or well-defined, but whose condition involves multiple systemic conditions and cannot be determined by a single department. Through thorough discussion and evaluation of the patient’s condition, the team determined the most appropriate treatment plan for the patient.
2.2.4.3. Rational staffing of human resources.
Dynamically adjust the working hours of emergency personnel to meet the demands of patients during peak times. Establishing a second-line service system to support frontline staff can help increase overall efficiency and enhance patient care. Improve the training and assessment of medical staff skills in the ED.
2.2.4.4. Information-based management of bed resources.
The hospital’s medical management department has established a WeChat working group comprising hospital leaders, medical directors, ED directors, clinical department directors, and chiefs of diagnosis and treatment groups. The information regarding emergency stranded patients can be systematically shared among all hospital departments. The doctors on duty in the ED report preliminary patient information for each department during the daily morning group meeting. The doctors in the clinical departments understand the urgency of the situation and allocate outpatient and emergency beds in a reasonable manner. If there is a situation where specialized departments have available beds but are not promptly receiving stranded patients, the director of the ED has decided to reserve the beds until the stranded patients have a confirmed destination.
2.2.4.5. Improve performance assessment program.
Whenever possible, patients in the ED resuscitation room should be admitted within 24 hours, based on performance evaluation. Departments that admit patients but fail to implement treatment, resulting in patients’ LOS exceeding 48 hours, should receive performance deductions and score penalties. Departments that admit patients to the ward in a timely manner should fully utilize the incentivizing role of rewards to enhance their enthusiasm for patient care.
2.2.5. Control phase.
The main process involves inspection, feedback, and correction. Special personnel from the medical department were responsible for monitoring the treatment of emergency room patients on a monthly basis. The top 5 departments with the median LOS were continuously analyzed to determine the reasons for their delays. This analysis provides a foundation for improvement.
3. Results
Our study analyzed data from 18,631 patients after excluding duplicate entries and missing values. During the SS study, a total of 2978 patients were discharged from the ED resuscitation room, 5961 were admitted, 16 were transferred to another hospital, and 42 patients died in the ED resuscitation room. Detailed patient inclusion criteria and endpoints are shown in Figure 1. Table 1 describes the essential characteristics of the patients.
Figure 1.
Flow chart of inclusion and exclusion process.
Table 1.
Patient characteristics before and after Six Sigma intervention.
| Basic information | Preintervention | Postintervention | P | |
|---|---|---|---|---|
| Gender | Male | 6111 (61.70%) | 5370 (61.53%) | .813 |
| Female | 3793 (38.30%) | 3357 (38.47%) | ||
| Age | 0–17 | 554 (5.59%) | 390 (4.46%) | .000 |
| 18–65 | 5335 (53.87%) | 4626 (53.01%) | ||
| 66–79 | 2961 (29.90%) | 2686 (30.78%) | ||
| ≥80 | 1054 (10.64%) | 1025 (11.75%) | ||
| Endpoint | Admission | 6275 (63.36%) | 5691 (65.22%) | .020 |
| Discharged | 3575 (36.10%) | 2978 (34.12%) | ||
| Transferred to another hospital | 20 (0.20%) | 16 (0.18%) | ||
| Mortality | 34 (0.34%) | 42 (0.48%) | ||
| Triage level | I | 342 (3.45%) | 294 (3.37%) | .000 |
| II | 644 (6.51%) | 520 (5.96%) | ||
| III | 1264 (12.76%) | 941 (10.78%) | ||
| IV | 7654 (77.28%) | 6972 (79.89%) | ||
| LOS component ratio | LOS ≤ 6h | 2395 (24.18%) | 2387 (27.35%) | .000 |
| 6 < LOS ≤ 12h | 1621 (16.37%) | 1711 (19.61%) | ||
| 12 < LOS ≤ 18h | 1090 (11.01%) | 994 (11.39%) | ||
| 18 < LOS ≤ 24h | 1597 (16.12%) | 1171 (13.42%) | ||
| 24 < LOS ≤ 30h | 1176 (11.87%) | 891 (10.21%) | ||
| LOS > 30h | 2025 (20.45%) | 1573 (18.02%) | ||
LOS = length of stay.
P < .05.
After the SS intervention, we compared the overall LOS of the 2 groups and found that the overall median LOS was reduced from 17.21 (6.22, 27.36) hours to 13.45 (5.56, 25.85) hours (Table 2). Our study found that the median LOS changed after the SS intervention for patients at various endpoints and different triage levels. The median LOS for admitted patients decreased from 19.64 (7.77, 27.68) hours to 15.92 (6.19, 26.24) hours (P < .05). The median LOS for emergency triage Level IV patients decreased from 16.15 (5.80, 26.62) hours to 12.59 (5.20, 24.97) hours (P < .05). The specific details are presented in Table 3.
Table 2.
Comparison of LOS before and after Six Sigma intervention.
| Time | Number of patients | Median LOS |
|---|---|---|
| Preintervention | 9904 | 17.21 (6.22, 27.36) |
| Postintervention | 8727 | 13.45 (5.56, 25.85) |
| Z | 7.56 | |
| P | .000 |
LOS = length of stay.
P < .05.
Table 3.
Comparison of endpoint and triage level before and after intervention.
| Index | Median LOS | P | ||
|---|---|---|---|---|
| Preintervention | Postintervention | |||
| Endpoint | Admission | 19.64 (7.77, 27.68) | 15.92 (6.19, 26.24) | .000 |
| Discharged | 11.33 (4.51, 25.49) | 10.57 (4.67, 23.80) | .122 | |
| Transferred to another hospital | 23.09 (11.79, 46.72) | 17.05 (5.10, 44.69) | .390 | |
| Mortality | 4.8 (1.99, 24.42) | 7.98 (1.94, 32.48) | .541 | |
| Triage level | I | 20.12 (8.32, 29.98) | 15.00 (5.93, 30.92) | .179 |
| II | 20.23 (7.40, 30.82) | 17.27 (7.10, 28.52) | .053 | |
| III | 20.48 (8.27, 28.79) | 18.33 (7.42, 28.57) | .080 | |
| IV | 16.15 (5.80, 26.62) | 12.59 (5.20, 24.97) | .000 | |
LOS = length of stay.
P < .05.
The data in Table 4 show that after the SS intervention, the average hospitalization days of discharged patients decreased from 0.80 days to 0.74 days (P = .130). Additionally, the average hospitalization days of hospitalized patients decreased from 0.92 days to 0.82 days (P < .05). Furthermore, the bed utilization rate increased from 66.79% to 72.29% (P < .05). The number of bed turnovers in the ED resuscitation room increased from 20.30 to 21.96 (P < .05).
Table 4.
Comparison of the efficiency of health resource utilization before and after the Six Sigma intervention.
| Intervention | Average hospitalization days of discharged patients (days) | Average hospitalization days of hospitalized patients (days) | Bed utilization rate (%) | Number of bed turnovers (times) | ||||
|---|---|---|---|---|---|---|---|---|
| Pre | Post | Pre | Post | Pre | Post | Pre | Post | |
| January | 0.87 | 0.69 | 0.97 | 0.85 | 0.66 | 0.72 | 20.58 | 22.42 |
| February | 0.72 | 0.71 | 0.86 | 0.88 | 0.66 | 0.76 | 18.49 | 21.3 |
| March | 0.82 | 0.76 | 1.04 | 0.86 | 0.66 | 0.73 | 20.35 | 22.74 |
| April | 0.78 | 0.67 | 0.94 | 0.77 | 0.71 | 0.64 | 21.19 | 19.07 |
| May | 0.71 | 0.76 | 0.98 | 0.77 | 0.68 | 0.74 | 21.21 | 22.84 |
| June | 0.7 | 0.81 | 0.93 | 0.85 | 0.69 | 0.81 | 20.79 | 24.3 |
| July | 0.83 | 0.9 | 0.9 | 0.91 | 0.65 | 0.71 | 20.26 | 22.07 |
| August | 0.82 | 0.73 | 0.86 | 0.82 | 0.67 | 0.67 | 20.84 | 20.91 |
| September | 0.82 | 0.68 | 0.92 | 0.76 | 0.65 | 0.73 | 19.4 | 21.86 |
| October | 0.96 | 0.69 | 0.83 | 0.71 | 0.64 | 0.71 | 19.93 | 22.12 |
| P | .130 | .003 | .037 | .022 | ||||
P < .05.
4. Discussion
There are numerous factors contributing to the strain on ED patients and an increase in complexity. The issue of stranded patients in ED is not solely the responsibility of the ED. It is the result of collaborative efforts among hospitals, the entire medical system, and various levels of society. The harm caused by this issue is also significant and varied. Our study applied SS management to improve the experience of patients stranding in ED. We analyzed the reasons for patients being stranded and proposed solutions to address the problem, while consistently monitoring and adjusting our approach.
The results showed that the median LOS of stay decreased in both groups for patients overall, admitted patients, and emergency triage grade IV patients. In addition, the average hospitalization days of admitted patients decreased, the utilization rate of ED beds increased, and the number of bed turnovers increased.
In our study, we adhered to international standards, which recommend patients in the ED to be transferred to the appropriate specialized ward within 6 hours and receive prompt and effective treatment. We therefore utilized a cutoff value of 6 hours to categorize the LOS, classifying it into 6 groups.[26] After implementing the SS method in management, we observed a difference between the pre- and postintervention periods. Specifically, there was a decrease in the proportion of patients with LOS between 18 and 24 hours, between 24 and 30 hours, and >30 hours. The Chi-square test indicated that the P-value was <0.05. We attribute this result to the implementation of the performance program. Our team-imposed performance deductions and scoring penalties on patients whose LOS exceeded 48 hours. And for those patients who need to be admitted to the ward promptly, it is crucial to offer incentives as a reward for their cooperation. This will increase the enthusiasm of clinical staff in diagnosing and treating patients. However, simultaneously, the proportion of individuals with a LOS between 6 and 12 hours increased, while there was minimal or no change in the group with a LOS between 12 and 18 hours. We have acknowledged the necessity for implementing additional control measures to facilitate the transfer of patients with prolonged LOS,[27–29] particularly those who have been hospitalized for more than 30 hours, to a category with a LOS of 6 hours or less. This will help us achieve shorter wait times and greater efficiency.
The management team at SS has efficiently reduced the LOS for hospitalized patients by effectively allocating bed resources through the use of the hospital information management system. This has also been linked to the establishment of a WeChat working group, which has facilitated the systematic management of bed resources. This not only improves bed utilization in the ED resuscitation room, but it also increases bed turnover and ensures that the needs of inpatients are met.
As the number of ED visits increases year by year, the medical demand from patients begins to exceed the capacity of emergency services. Studies have shown that, in addition to the elderly, critically ill patients, and frequent visitors to the ED, the inappropriate utilization of emergency care by nonemergency patients is also a significant factor in prolonging the EDLOS. In this investigation, our team strictly controlled the process of preexamination triage levels and significantly reduced the length of hospital stay for patients classified as Level IV. Triage doctors and nurses classified patients with no acute symptoms, fewer complaints of discomfort, fewer emergency resources, and no increased possibility of adverse events in the short term as Level IV. They were then directed to outpatient consultation rooms or transferred to medical institutions other than emergency resuscitation rooms, such as primary health service centers, for appropriate treatment. In order to better meet the medical needs of nonemergency patients, the management team proposed and implemented a method of providing outpatient services on holidays. This initiative aims to redirect Level IV patients and increase business volume. Due to a lack of medical knowledge and understanding of emergency treatment concepts, many patients are unaware of the important characteristics of “urgent, severe, and critical” emergency diagnoses. Triage doctors and nurses also work to correct patients’ misconceptions through public awareness campaigns and education, aiming to improve the efficient utilization of the emergency resuscitation room. Finally, the number of Level IV patients is significant, and the team should also consider transferring hospitalized patients with stable conditions, clear diagnoses, and a very low risk to lower-level hospitals in a timely manner. This will allow them to continue treatment in the wards of community service centers. In addition, our study found that the median LOS for critically ill patients in the ED resuscitation room, specifically Level I patients, decreased from 20.12 (8.32, 29.98) hours to 15.00 (5.93, 30.92) hours. The median LOS for Level II patients decreased from 20.23 (7.40, 30.82) hours to 17.27 (7.10, 28.52) hours. However, there was no statistically significant difference. The reason we consider this phenomenon is that emergency care for critically ill patients is often complex and involves multiple systems. Patients may have various professional affiliations, and it may be necessary to perform relevant clinical examination procedures, such as computed tomography, contrast imaging, and X-rays, before confirming a diagnosis. This can result in a prolonged EDLOS.
We are aware of several limitations of the current study. First, a single-center study would undermine the credibility of our findings. Conducting a retrospective analysis of the data prior to our intervention increases the likelihood of bias in the recorded information. In addition, the study excluded patients who frequently visited the emergency room, as stated in the exclusion criteria. However, further investigation is necessary to assess the impact of this exclusion. Third, our study must acknowledge that the reduction in LOS is not solely the result of strategic intervention. On the contrary, hospital management may have a greater impact than the technical level, and implementing rigorous performance management programs can encourage frontline staff to be more proactive in promptly addressing patient needs. We believe that the environment of ED care is highly complex, and the reduction of LOS is the result of multiple factors working in conjunction. We will continue to investigate and identify measurable indicators in future studies and make every effort to demonstrate the effectiveness of our intervention program.
5. Conclusions
As a tool for continuous improvement and optimal management, SS is applied to the ED to manage the treatment process for emergency patients. It helps our team to define project goals, measure specific metrics, analyze root causes, and implement improvements and continuous adjustments. The application of SS in the treatment of stranded emergency patients has yielded positive results. It has reduced the LOS for emergency patients, improved the quality and efficiency of ED resuscitation rooms and care, and fostered a new culture of hospital management.
Author contributions
Data curation: Manman Shang.
Formal analysis: Guifang Zheng, Zhenyu Li.
Investigation: Manman Shang, Qin Wei.
Methodology: Manman Shang.
Project administration: Qin Liu, Ling Lin, Yong Wu, Qin Wei.
Software: Manman Shang.
Supervision: Qin Liu, Ling Lin, Yong Wu, Qin Wei.
Validation: Manman Shang, Qin Wei.
Visualization: Manman Shang.
Writing – original draft: Manman Shang.
Writing – review & editing: Yueping Li, Qin Wei.
Abbreviations:
- ED
- emergency department
- EDLOS
- emergency department length of stay
- LOS
- length of stay
- SS
- Six Sigma
This study was supported by the Special Funds of the Fujian Provincial Department of Finance (2020CZ001).
The authors have no conflicts of interest to disclose.
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
How to cite this article: Shang M, Zheng G, Li Z, Liu Q, Lin L, Li Y, Wu Y, Wei Q. Reducing the length of stay for patients stranded in the emergency department: A single-center prospective study of 18,631 patients in China. Medicine 2024;103:10(e37427).
Contributor Information
Manman Shang, Email: 1481194153@qq.com.
Guifang Zheng, Email: 773496720@qq.com.
Zhenyu Li, Email: fmulyp@163.com.
Qing Liu, Email: liuqfj@qq.com.
Ling Lin, Email: 598368219@qq.com.
Yueping Li, Email: fmulyp@163.com.
Yong Wu, Email: wuyong9195@126.com.
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