key: cord-0994648-9zv01yrj authors: Lee, Ji Hwan; Kim, Ji Hoon; Park, Incheol; Lee, Hyun Sim; Park, Joon Min; Chung, Sung Phil; Kim, Hyeon Chang; Son, Won Jeong; Roh, Yun Ho; Kim, Min Joung title: Effect of a Boarding Restriction Protocol on Emergency Department Crowding date: 2022-04-20 journal: Yonsei Med J DOI: 10.3349/ymj.2022.63.5.470 sha: 3519b0e686ecb38f7a58a0b9787d7385a0175ded doc_id: 994648 cord_uid: 9zv01yrj PURPOSE: Access block due to the lack of hospital beds causes crowding of emergency departments (ED). We initiated the “boarding restriction protocol” that limits the time of stay in the ED for patients awaiting hospitalization to 24 hours from arrival. The purpose of this study was to determine the effect of the boarding restriction protocol on ED crowding. MATERIALS AND METHODS: The primary outcome was ED occupancy rate, which was calculated as the ratio of the number of occupying patients to the total number of ED beds. Time factors, such as length of stay (LOS), treatment time, and boarding time, were investigated. RESULTS: The mean of the ED occupancy rate decreased from 1.532±0.432 prior to implementation of the protocol to 1.273±0.353 after (p<0.001). According to time series analysis, the absolute effect caused by the protocol was -0.189 (-0.277 to -0.110) (p=0.001). The proportion of patients with LOS exceeding 24 hours decreased from 7.6% to 4.0% (p<0.001). Among admitted patients, ED LOS decreased from 770.7 (421.4–1587.1) minutes to 630.2 (398.0–1156.8) minutes (p<0.001); treatment time increased from 319.6 (198.5–482.8) minutes to 344.7 (213.4–519.5) minutes (p<0.001); and boarding time decreased from 298.9 (109.5–1149.0) minutes to 204.1 (98.7–545.7) minutes (p<0.001). In pre-protocol period, boarding patients accumulated in the ED during the weekdays and resolved on Friday, but this pattern was alleviated in post-period. CONCLUSION: The boarding restriction protocol was effective in alleviating ED crowding by reducing the accumulation of boarding patients in the ED during the weekdays. Crowding in the emergency department (ED) is a critical pub-lic health problem. 1, 2 Research has shown that crowding in the ED elicits many adverse effects, including increased mortality, medical errors, return visits, ambulance diversion, and costs, as well as decreased patient satisfaction. [3] [4] [5] [6] Accordingly, numerous studies have been conducted to solve crowding in the ED over the past decade. [7] [8] [9] One of main contributors to crowding in the ED is access block, which refers to an inability to transfer patients from the ED to hospital beds, such that the patients remain in the ED even after emergency treatment has been completed. 10 Access block occurs when hospital bed occupancy increases. [11] [12] [13] Forster, et al. 14 reported that the length of stay (LOS) of admitted patients in the ED increased by 18 min for every 10% increase in hospital bed occupancy and increased greatly when bed occupancy exceeded 90%. In order to solve this situation, several countries have imple- mented a mandatory national policies limiting the staying time of patients in the ED. In 2004, the UK's National Health Service first introduced the "4-hour target" requiring 98% of patients who visit the ED to leave within 4 hours of arrival. 15, 16 Since then, similar national policies have been initiated in several countries: the Australian government applied the National Emergency Access Target, which limited ED LOS to 4 hours, as in the UK; New Zealand adopted a longer 6-hour target. 17, 18 The governments of these countries had a strong will to improve the crowding of ED and demanded the improvement from hospitals rather than ED alone, and this mandatory policies have had a great effect on improving the indicators of ED crowding. 15, 16, 19 In Korea, crowding in the ED has been a serious public issue for a long time; however, there are no national regulations on staying time in the ED: the Korean government only recommends keeping patients who stay for more than 24 hours below 5%. Addressing access block requires changing rules on hospital bed arrangement; however, hospital leadership is not easily motivated without government policies. 20 , 21 We initiated a new protocol, the so-called "boarding restriction protocol", to control the situation in which patients who needed to be hospitalized was waiting in the ED without any time limit due to hospital crowding. The core content was to limit the staying time of each patient waiting for hospitalization to 24 hours from ED arrival. The hypothesis of this study was that the boarding restriction protocol would alleviate ED crowding. We conducted this study to confirm this protocol's effect on ED crowding. This study was a pre-post comparative study conducted in the ED of a tertiary university hospital located in an urban area. The hospital operates about 2200 beds, with an average annual bed utilization rate of 80%. The ED was divided into an adult ED and a pediatric ED, and the adult ED, in which this study was conducted, consisted of a monitoring area (13 beds), a bed area (29 beds), a chair area (20 recliners), and a fast track area. The adult ED treated patients over 16 years of age, and the number of visiting patients was about 90000 per year. 20% of visiting patients were hospitalized, and the average waiting time for hospitalization was 10 hours. About 5% of patients stayed in the ED for more than 24 hours. An emergency physician or emergency medicine trainee began the treatment for all patients who came to the ED, and if hospitalization was deemed necessary, consultation with a relevant specialist was conducted to determine whether the patients ought to be hospitalized. When hospitalization was decided, the attending physician became the subject of treatment for the patient, and treatment continued in the ED until the hospital bed was ready. When transferring a patient to another hospital, the hospital was ar-ranged by requesting to the ED coordinator. The boarding restriction protocol began in November 2019; however, coronavirus disease (COVID-19) infection began to spread in Korea from February 2020, which greatly affected the treatment process of the ED. [22] [23] [24] Therefore, the duration of this study was set for 9 weeks starting from the first week of December 2019, and we compared the same period 1 year previous in consideration of seasonal variations in ED crowding. All data were collected by the hospital information system and processed anonymously, and this study was exempt from the obligation to obtain patient informed consent from the Institutional Review Board of Severance hospital (approval number: 4-2020-1164). The boarding restriction protocol is directed for patients requiring hospitalization, and the purpose of the protocol is to move these patients out of the ED within 24 hours from ED arrival (Fig. 1 ). The strategy seeks to allocate hospital beds as much as possible within 18 hours from ED arrival. If bed assignment is not made within 18 hours, a text message is sent to the attending physician informing that the patient could not be admitted due to the absence of a hospital bed. When the attending physician decides to transfer the patient to another hospital, the ED coordinator arranges an appropriate hospital according to the patient's condition and dispatches the patient within 24 hours. If the patient cannot be transferred to another hospital for a severe condition or patient disagreement with the transfer, the attending physician can decide to keep the patient in this hospital. Patients who decide to keep waiting for hospitalization are given priority bed allocation over other waiting patients at the attending physician's outpatient clinic. As the primary outcome of this study, we investigated ED occupancy rate. The definition of ED occupancy rate was the ratio of the number of occupying patients to the total number of beds in the ED. 25 Although there is no universally accepted tool to measure ED crowding, ED occupancy rate is one reliable method that has been used in many previous studies. 26, 27 To obtain ED occupancy rate, we reconstructed the dataset of the number of ED occupying patients at 10-minute intervals from the time of arrival and departure of each patient. A total of 9072 ED occupancy rate values were generated for the pre-and post-period, and the difference in crowding between the two periods was examined. Time series analysis of ED occupancy rate at 10-minute intervals from January 2018 was performed to confirm whether there was a significant change in crowding trends after implementation of the boarding restriction protocol. The secondary outcome was the proportion of patients who stayed longer than 24 hours and ED LOS. Time factors were also investigated according to the ED treatment process. The treatment time was the time taken from ED arrival to the decision of disposition (admission, discharge, or transfer). The decision time of transferred patients was based on the time when doctors requested the arrangement of proper hospital to the coordinator. Boarding time was defined as the time from the decision of disposition to the time of leaving the ED. Since the target of this protocol is boarding patients, their LOS and occupancy in the ED were analyzed in more detail. ED occupancy by patients who were deemed to require hospitalization but remained in the ED was reconstructed at 10-minute intervals using each patient's admission decision time and ED departure time. Since hospitalization patterns vary between weekdays and weekends, the number of patients admitted to hospital beds and ED LOS were analyzed according to the day of the week. At this hospital, every morning, the administrative team counted the number of patients who were hospitalized and discharged the previous day, as well as the number of occupying patients at 8:00 am to calculate the hospital bed occupancy rate. The hospital bed occupancy rate was the number of occupying patients out of the total number of hospital beds. We used this data to compare hospital crowding between the pre-and post-periods. Patient data were extracted from the hospital information system and electric medical records. We checked whether the patient was transferred from another hospital and whether the patient arrived via emergency medical service. The result of triage by Korean Triage and Acuity Scale (KTAS), a five-point classification scale (1=resuscitation, 5=non-emergent), was investigated. 28 The complaint category was the organ system that corresponded to the main symptom of which the patient complained. Non-medical problems referred to visits due to external reasons, such as trauma, poisoning, or environmental factors. Severe disease corresponded to diagnosis of a disease that has been designated with a severe diagnosis code by the Central Emergency Medical Center under the Ministry of Health and Welfare (Supplementary Table 1 , only online). 29 We investigated whether the emergency physician treated and the area where the treatment started. Time of ED arrival and weekend were classified based on the time the patient arrived at the ED. Laboratory study, imaging study (x-ray, computed tomography, magnetic resonance imaging), and specialty consultation performed during the stay in the ED were also confirmed. Nominal variables of the pre-and post-periods were compared using the chi-square test and presented as numbers with percentages. Continuous variables were analyzed using Student's t-test and presented as means and standard deviations. Time factor variables were analyzed using Mann-Whitney U test considering the positive skewness of the data distribution and are presented as medians and interquartile ranges. The time-series analysis of the ED occupancy rate was analyzed using a Bayesian structural time series model. 30 A logistic regression for patients staying longer than 24 hours and a generalized linear regression for ED LOS were performed by selecting influencing variables with p-value less than 0.05 in univariable analysis. Data reconstruction and statistical analysis were performed using SAS (version 9.4, SAS Inc., Cary, NC, USA). The time series analysis was performed with the R package, version 4.0.1 (R Foundation for Statistical Computing, Vienna, Austria). A p value less than 0.05 was deemed to be statistically significant. 12498 patients during the pre-period and 13050 patients during the post-period were treated in the ED ( Table 1 ). The sex and age of both groups were similar, and the proportion of patients who were transferred from other hospitals decreased from 12.9% in the pre-period to 10.8% in the post-period (p<0.001). The proportion of less urgent patients with KTAS 4 and 5 decreased during the post-period, and the proportion of patients diagnosed with severe disease increased from 17.8% to 18.9% (p=0.031). The rates of laboratory study and specialty consultation were similar between the two periods; however, among imaging studies, computed tomography was performed more in the post-period (37.5% vs. 38.9%, p=0.020). As a result of treatment, the number of hospitalized patients decreased from 2853 (22.8%) to 2793 (21.4%), and the number of patients who were sent to other hospitals increased from 347 (2.8%) to 399 (3.1%) (p=0.013). As a result of analyzing ED occupancy rate at 10-minute intervals, the mean ED occupancy rate decreased from 1.532±0.432 in the pre-period to 1.273±0.353 in the post-period (p<0.001). Fig. 2 shows the distribution of ED occupancy rates according to the day and time of the week. Overall, ED occupancy rates in the post-period decreased throughout the week, compared to the pre-period. The pattern of crowding resolved at dawn and worsening in the afternoon was observed in both periods. Crowding gradually worsened from Monday to Thursday in the pre-period, although this feature was not observed in the postperiod. Fig. 3 shows the results of the time series analysis of the ED occupancy rate. During the post-period, the mean (95% confidence interval) ED occupancy rate predicted by the time series model was 1.462 (1.383-1.550). However, after implementation of the protocol, the mean ED occupancy rate was 1.273, which was lower than the predicted value, resulting in an absolute effect of the protocol of -0.189 (-0.277 to -0.110). (p=0.001). The number of patients leaving the ED beyond the goal of this protocol of 24 hours decreased from 951 (7.6%) to 525 (4.0%) (p<0.001). The results of logistic regression analysis for the proportion of patients with LOS exceeding 24 hours are shown in Table 2 Fig. 4 shows the distribution of the arrival and departure days of the admitted patients by day of the week. During the preperiod, the number of patients admitted to hospital beds was smaller than the number of patients who arrived at the ED from Monday to Thursday, maintaining a positive difference, and from Friday, more patients could be hospitalized. During the post-period, the number of patients arriving and leaving on Tuesday and Wednesday remained similar, and hospitalization was less concentrated on Friday, compared to the preperiod. In the pre-period, the ED LOS of patients arriving from Tuesday to Thursday was significantly delayed, although this feature was alleviated in the post-period. The median number of boarding patients measured at 10minute intervals was 21.0 (12.0-37.0) in the pre-period and 10.0 (7.0-19.0) in post-period, a decrease of 52.4% (p<0.001). In the distribution of boarding patients, the number of patients continuously increased from Monday to Thursday and then rapidly decreased on Friday in the pre-period (Fig. 5) . The number of boarding patients during the post-period was also higher on weekdays than on weekends, although the difference was much less than that in the pre-period. The total number of patients admitted to this hospital was 21626 in the pre-period and 21258 in the post-period. Among them, 2839 (13.1%) and 2794 (13.1%) patients were admitted via ED, respectively, and there was no statistically significant difference between the two periods (p=0.962). The hospital bed occupancy rate in both groups was similar to 0.863 (0.812-0.876) in the pre-period and 0.838 (0.792-0.888) in the post-period (p= 0.361). In this study, we confirmed that the boarding restriction protocol significantly reduces ED occupancy rates by reducing the LOS of admitting patients. It is well known that the main driver of ED crowding is obstruction of outflow. 13, 31, 32 Since access block is caused by crowding of the entire hospital, the solution should not be limited to the ED to be effective, and bed capacity must be increased in consideration of patient flow throughout the whole hospital. 20, 33, 34 However, there is still not much leadership in recognition the ED crowding as a whole hospital problem, and it can be also related to the hospital's profits, making it difficult to change hospitalization policies for the entire hospital to solve ED crowding. 20, 21 For this reason, we could not apply the boarding protocol to the entire hospital and had to start targeting only emergency patients inside the ED, even though our protocol aimed to solve output from the ED. Even so, our protocol likely would have affected patient flow throughout the entire hospital, because we not only moved patients out of the hospital, but also gave the attending physician the authority to decide whether to hospitalize emergency patients over patients in outpatient clinics. As discharged patients accounted for 75.5% of all patients who were not subject to this protocol, the entire ED LOS was not reduced. Among admitted patients, we were able to see an interesting phenomenon in which ED LOS decreased as boarding time was significantly reduced while treatment time increased. We suspect that it took a longer time to make admission decisions because patients could not board indefinitely in the ED until hospitalization, thereby making the attending physician more cautious with their decision making. This finding is in line with previous studies indicating that increased ED crowding is associated with a decrease in decision making for hospitalization. 35, 36 Crowding of the ED is a desperate situation for emergency staff as it hinders providing adequate first aid to new emergency patients; however, attending physicians outside the ED are generally not directly affected by ED crowding. Until this protocol was initiated, the attending physicians made admission decisions without considering the availability of hospital beds, and allocating beds was the responsibility of administrative staff. Since administrative staff could not consider the medical condition of patients, patient safety was inevitably threatened when hospital beds were insufficient. With implementation of this protocol, attending physicians were forced to face the problem of hospital bed shortages and intervene in the assignment of beds. As such, emergency patients were given the opportunity to have bed priority. Through this study, we could see that patients waiting for hospitalization were congested in the ED on weekdays and resolved on Friday and Saturday, which was resolved considerably after this protocol. A significantly longer ED LOS for admitted patients who arrived at the ED on Tuesday, Wednesday, and Thursday was also resolved. Since scheduled hospitalization is primarily conducted on weekdays, a delay in emergency hospitalization during weekdays has been reported in previous studies. 11, 37, 38 In most hospitals, medical staff prefer to perform the procedure at the beginning of the week and to discharge the patient before the weekend. This preference is because doctors do not want to work on the weekends; however, if a patient is still in the hospital on the weekends, they will have to take responsibility or continue care. 39 Variations in the hospital's daily inpatient census are the result of a combination of natural variations in emergency hospitalization and an artificial peak and valley of scheduled hospitalizations. A discrepancy between a hospital's available resources and patient demand is a major culprit that degrades the quality of care, impedes access to care, and ultimately threatens the safety of patients. 40, 41 In order to efficiently use hospital resources and ensure patient safety, the peaks and valleys of patient demand must be smoothed. [42] [43] [44] Interventions introduced in previous studies to smooth demand were accompanied by system changes, such as weekend staffing relocation to alleviate the weekend effect. 20, 42, 43, 45 Although our boarding protocol did not directly intervene in artificial variations, it achieved smoothing of weekly variations in hospitalization through the ED by limiting boarding time in the ED. Further studies should be conducted to determine the effect of smoothing of weekly fluctuations in emergency admission on patient flow throughout the hospital and patient safety. Since it is difficult to cancel scheduled surgeries and procedures, hospitalization of patients who need conservative treatment may be delayed. Excessive delay in scheduled hospitalization, however, may be a factor that hinders patient safety from a longterm perspective, such as delayed chemotherapy. Thus, a system that proactively coordinates overall hospitalizations is essential. The present study has several limitations. First, because our study has a pre-post comparative design and was performed retrospectively, some confounders may have been unidentified. Second, to avoid the COVID-19 outbreak period, which had a major impact on ED processes, a short study period of 9 weeks was inevitable. Thus, it was impossible to ascertain the long-term effects of this protocol. Finally, this study was conducted at a single tertiary hospital with a high bed occupancy of more than 80% and a significantly long boarding time in the ED. Therefore, the effect of this protocol may be different at hospitals where the degree of crowding and the patterns of patient flow are different. In conclusion, we confirmed that a boarding restriction protocol was effective in reducing ED crowding. This was possible because weekly variations in emergency hospitalization were alleviated by facilitating hospitalization of emergency patients during weekdays. Further research is needed to study changes brought on patient flow throughout the hospital and their impact on patient safety and hospital revenue. 5 . Distribution of the number of boarding patients in the emergency department according to day of week and time. The number of boarding patients continuously increased from Monday to Thursday and decreased on Friday in the pre-period. In the post-period, the number of boarding patients was higher on weekdays than on weekends, but the difference was small compared to the pre-period. Overcrowding in emergency department: an international issue Emergency department crowding: a systematic review of causes, consequences and solutions Emergency department crowding is associated with reduced satisfaction scores in patients discharged from the emergency department Increases in emergency department occupancy are associated with adverse 30-day outcomes Further characterization of the influence of crowding on medication errors Influence of overcrowding in the emergency department on return visit within 72 hours Emergency department expansion versus patient flow improvement: impact on patient experience of care Medical team evaluation: effect on emergency department waiting time and length of stay Effects of a short text message reminder system on emergency department length of stay Emergency department overcrowding and access block Time series analysis of variables associated with daily mean emergency department length of stay Emergency department (ED) overcrowding: evidence-based answers to frequently asked questions The International Federation for Emergency Medicine report on emergency department crowding and access block: a brief summary The effect of hospital occupancy on emergency department length of stay and patient disposition Implications of England's four-hour target for quality of care and resource use in the emergency department Time patients spend in the emergency department: England's 4-hour rule-a case of hitting the target but missing the point? The National Emergency Access Target (NEAT) and the 4-hour rule: time to review the target Impact of a national time target for ED length of stay on patient outcomes The good, the bad, and the four hour target Solutions to emergency department 'boarding' and crowding are underused and may need to be legislated Directors of emergency medicine's beliefs about, barriers to, and enablers of solutions to emergency department crowding and access block Analysis of the impact of the coronavirus disease epidemic on the emergency medical system in South Korea using the Korean triage and acuity scale A comprehensive review of coronavirus disease 2019: epidemiology, transmission, risk factors, and international responses. Yonsei Protection of healthcare workers against COVID-19 at a large teaching hospital in Seoul, Korea The emergency department occupancy rate: a simple measure of emergency department crowding? Emergency department crowding is associated with delayed antibiotics for sepsis Maximum emergency department overcrowding is correlated with occurrence of unexpected cardiac arrest Korean triage and acuity scale (KTAS) Analysis of emergency department length of stay in patient with severe illness code Inferring causal impact using Bayesian structural time-series models Strategies and solutions to alleviate access block and overcrowding in emergency departments Emergency department flow and the boarded patient: how to get admitted patients upstairs Emergency short-stay wards and boarding time in emergency departments Access block and emergency department overcrowding Evaluating the impact of emergency department crowding on disposition patterns and outcomes of discharged patients Pediatric emergency department crowding is associated with a lower likelihood of hospital admission Evaluating the effects of increasing surgical volume on emergency department patient access Scheduled surgery admissions and occupancy at a children's hospital: variation we can control to improve efficiency and value in health care delivery Berwick DM. Managing unnecessary variability in patient demand to reduce nursing stress and improve patient safety Emergency department diversion: causes and solutions Variability in surgical caseload and access to intensive care services Smoothing the way to high quality, safety, and economy More patients, less payment: increasing hospital efficiency in the aftermath of health reform Patient flow in hospitals: understanding and controlling it better Re-engineering the operating room using variability methodology to improve health care value We would like to thank Young Ho Lee, deputy general manager of the Department of Planning and Budgeting, for his support in establishing and implementing this protocol.