Factors Associated with the Misclassification of a New Triage Tool in Pediatric Emergency Departments in Korea: A Nationwide Retrospective Observational Study

Factors Associated with the Misclassification of a New Triage Tool in Pediatric Emergency Departments in Korea: A Nationwide Retrospective Observational Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Factors Associated with the Misclassification of a New Triage Tool in Pediatric Emergency Departments in Korea: A Nationwide Retrospective Observational Study Jisu Ryoo, Arum Choi, Beom Joon Kim, Sukil Kim, Woori Bae This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7449021/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background: This study aimed to investigate the factors affecting mistriage,including overtriage and undertriage, associated with the use of a new triage tool for assessing patient urgency in pediatric emergency departments (PEDs). Methods: This was a retrospective observational study based on the national registry data of patients aged < 15 years who visited PEDs between January 2016 and December 2019. Patients were classified into non-mistriage, overtriage, and undertriage groups, and the incidence and risk factors of mistriage and its characteristics according to hospital size were analyzed. Results: Overall, 5,462,964 patients were included, of whom 129,903 (2.4%) were excluded. Overtriage and undertriage occurred in 35,897 (0.7%) and 94,006 (1.7%) patients, respectively. The overtriage-associated factors were age of 1–4 years, female sex, evening visits, night, disease group, and self-referrals. The undertriage-associated factors were age of <1 year, male, daytime visits, trauma group, and referral from a clinic or outpatient department. There were also differences in the tendency for mistriage according to hospital size. Conclusion: This study identified major risk factors related to mistriage in patients in PEDs. Accurate triage that considers these factors is essential for providing appropriate treatment and efficient use of PED resources. Triage Mistriage Pediatric emergency medicine Child Figures Figure 1 Background Emergency department (ED) overcrowding has increased worldwide as the number of patients visiting EDs has increased [ 1 ]. The number of ED visits per 1000 individuals in 2023 was 187.9 in South Korea, with pediatric patients accounting for 20.4% of the total [ 2 ]. In such circumstances, rapid and accurate patient triage upon arrival, by an effective assessment of patient urgency, is essential for timely and appropriate medical care and resource optimization. Since the early 1990s, various triage systems have been established worldwide, including the Canadian Emergency Department Triage and Acuity Scale (CTAS), Emergency Severity Index (ESI), and Manchester Triage Scale (MTS) [ 3 ]. In South Korea, the Korean Triage and Acuity Scale (KTAS) was developed based on CTAS and has been applied to all patients visiting EDs since January 1, 2016 [ 4 ]. KTAS includes a pediatric version (PedKTAS) for patients aged < 15 years [ 5 ]. PedKTAS refines age-specific ranges for normal vital signs to reflect children’s physiological characteristics and developmental stages and considers nonverbal clinical signs such as general appearance, breathing, and circulation in the triage process [ 5 , 6 ]. However, the urgency triage process is complicated by age-based vital sign criteria, and factors such as pediatric patients' fear of the pediatric emergency department (PED) may influence subjective assessments, making it difficult to assess urgency [ 7 ]. Importance Mistriage is a situation where there is a discrepancy between the triage nurse-assigned urgency classification and the classification appropriate for the actual patient condition. It can be further divided into undertriage, where urgency is underestimated compared to the actual, or overtriage, where the urgency is overestimated. Mistriage has a marked negative effect on appropriate emergency medical care. Undertriage may delay the treatment of critically ill patients, whereas overtriage can cause overcrowding of PEDs and unnecessary resource utilization [ 8 , 9 ]. Although there have been some studies on mistriage, most of them focused on adult patients, leaving gaps in the understanding of pediatric mistriage. In particular, only a few studies have been conducted on PedKTAS-associated mistriage. Goals of This Investigation This study aimed to investigate mistriage rates in pediatric cases within the PedKTAS system and identify the factors contributing to undertriage and overtriage. Materials and methods Study Design, Setting, and Population This retrospective observational study used data from the National Emergency Department Information System (NEDIS). NEDIS is a nationwide emergency medical network that receives real-time data from 31 district emergency medical centers (EMCs), 120 regional EMCs, and 257 regional emergency medical institutions (EMIs). Data collected between January 1, 2016, and December 31, 2019, were used. The study included patients aged < 15 years who presented to a PED and excluded patients with a KTAS level of 8 or 9, those who presented for non-therapeutic reasons, and those with missing KTAS levels or medical records. District EMCs serve as tertiary-level facilities and provide comprehensive care to critically ill patients in general hospitals with 300 or more beds. These facilities receive an average of approximately 40,000 patient visits annually, of which approximately 12,000 are pediatric visits. Regional EMCs are designated as general hospitals suitable for emergency care and experience an average of approximately 30,000 patient visits annually, of which approximately 8,000 are pediatric visits. Regional EMIs, selected from general hospitals, receive an average of approximately 6,000 emergency visits annually, of which approximately 3,000 are pediatric visits. KTAS Algorithm When a patient arrives at the PED, the triage nurse uses the 5-level PedKTAS to determine the appropriate time for medical assessment. KTAS 1 signifies an immediate threat to life or limb and a need for aggressive treatment. KTAS 2 means there is a potential threat to life or limb and urgent care is needed. Conditions with the potential to develop into serious conditions requiring emergency care are categorized as KTAS 3 and those that could be treated or reassessed within 1–2 h are categorized as KTAS 4. KTAS 5 indicates an acute but not urgent situation and may be associated with a worsening or unchanging chronic condition [ 10 ]. Reassessment at designated time intervals is mandatory for all patients. Continuous monitoring is required for level 1, whereas reassessment at intervals of 10, 30, 60, and 120 min is necessary for levels 2, 3, 4, and 5, respectively [ 11 ]. Situations with KTAS levels 1–3 are generally considered urgent, whereas those with KTAS levels 4 and 5 are considered non-urgent. PedKTAS categorizes symptoms, including 166 specific symptoms, into 17 groups. Triage nurses look at the most important symptoms first, consider the pediatric assessment triangle, select the most relevant symptoms, and assign a severity level based on primary considerations, including vital signs, and secondary considerations, including nurse judgment [ 12 ]. Data Collection Each PED visit was considered an independent case. Variables including age, sex, initial and final triage levels, arrival shift, arrival mode, diagnosis, EMC class, and final disposition were extracted from the patient data in NEDIS. Mistriage was defined as a case where KTAS level 1, 2, or 3, corresponding to an emergency, changed to KTAS level 4 or 5, corresponding to a non-emergency, and vice versa, between the initial and final triage. Patients were categorized into non-mistriage, overtriage, and undertriage groups accordingly. Diagnoses were made using the Korean Standard Classification of Diseases-7, the Korean version of the International Classification of Diseases, 10th Revision [ 13 , 14 ]. Outcomes The primary outcome was the incidence of and risk factors for mistriage when PedKTAS was applied. The secondary outcomes were the characteristics of mistriage according to the type of the emergency medical facility. Statistical analysis The chi-square test was used to assess statistical differences between the mistriage and non-mistriage groups. Multivariate regression analysis adjusted for age, sex, arrival shift, arrival mode, and diagnosis was conducted to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for the overtriage and undertriage groups. All statistical analyses were conducted using R version 4.0.0 (R Foundation for Statistical Computing, Vienna, Austria); a p-value of < 0.05 was considered significant. Results Between January 2016 and December 2019, 6,847,960 cases were collected from PEDs nationwide. After excluding 1,322,689 patients with KTAS levels of 8 and 9 or unknown KTAS levels and an additional 62,307 patients with missing records, the final analysis included 5,462,964 patients. The analysis revealed 129,903 mistriage cases (2.4%). Of these, 35,897 (0.7%) and 94,006 were classified as overtriage and undertriage cases, respectively. The mistriage percentage at each level is shown in Fig. 1 . Table 1 shows the characteristics of patients visiting the PED, divided into non-mistriage, overtriage, and undertriage groups. Pediatric patients aged < 1 year and 1–4 years accounted for 11.8% and 48.2% of the non-mistriage group, respectively. Table 1 Characteristics of patients visiting the pediatric emergency department Variables Non-mistriage group (N = 5,313,997) Mistriage group (N = 129,903) P Overtriage group (N = 35,897) Undertriage group (N = 94,006) Age, yr < 1 626,553 (11.8%) 5,364 (14.9%) 15,004 (16%) < 0.001 1–4 2,561,256 (48.2%) 18,484 (51.5%) 40,680 (43.3%) 5–9 1,324,151 (24.9%) 7,055 (19.7%) 22,860 (24.3%) 10–14 802,037 (15.1%) 4,994 (13.9%) 15,462 (16.4%) Gender Male 3,038,030 (57.2%) 20,113 (56%) 54,845 (58.3%) < 0.001 Triage level KTAS 1 10,828 (0.2%) 168 (0.5%) < 0.001 KTAS 2 180,616 (3.4%) 2,368 (6.6%) KTAS 3 1,687,363 (31.8%) 33,361 (92.9%) KTAS 4 2,959,187 (55.7%) 85,364 (90.8%) KTAS 5 476,003 (9.0%) 8,642 (9.2%) Shift of arrival Day (7AM-3PM) 1,346,573 (25.3%) 8,191 (22.8%) 27,369 (29.1%) < 0.001 Evening (3PM-11PM) 2,956,392 (55.6%) 18,249 (50.8%) 46,714 (49.7%) Night (11PM-7AM) 1,011,032 (19.0%) 9,457 (26.3%) 19,923 (21.2%) Mode of arrival Self-referred 4,939,101 (92.9%) 33,632 (93.7%) 80,137 (85.2%) < 0.001 Outpatient department 40,792 (0.8%) 139 (0.4%) 1,297 (1.4%) Referred from clinic 334,104 (6.3%) 2,126 (5.9%) 12,572 (13.4%) Diagnosis Disease 3,728,950 (70.2%) 29,821 (83.1%) 69,370 (73.8%) < 0.001 Trauma 1,585,047 (29.8%) 6,076 (16.9%) 24,636 (26.2%) EMC class District EMC 1708789 (32.2%) 21,498 (59.9%) 39,674 (42.2%) < 0.001 Regional EMC 3157306 (59.4%) 7,010 (19.5%) 52,189 (55.5%) Regional EMI 447902 (8.4%) 7,389 (20.6%) 2,143 (2.3%) Final disposition Discharged 4,758,172 (89.5%) 34,343 (95.7%) 57,593 (61.3%) < 0.001 Hospitalization Admission to GW 499,276 (9.4%) 1,447 (4%) 32,494 (34.6%) Admission to ICU 19,986 (0.4%) 13 (0%) 908 (1%) Admission to OR 13,571 (0.3%) 21 (0.1%) 1,527 (1.6%) Transfer to other hospital 21,552 (0.4%) 72 (0.2%) 1,478 (1.6%) Expired 134 (0.0%) 0 (0%) 4 (0%) DOA 1,306 (0.0%) 1 (0%) 2 (0%) Values are presented as n (%) unless otherwise indicated. KTAS: Korean triage and acuity scale, EMC: emergency medical center, EMI: emergency medical institution, GW: general ward, ICU: intensive care unit, OR: operation room, DOA: dead on arrival. The corresponding proportions in the overtriage group were 14.9% and 51.5% and in the undertriage group were 16% and 43.3%. Daytime visits (7 AM to 3 PM) accounted for 25.3%, 22.8%, and 29.1% of the visits in the non-mistriage, overtriage, and undertriage groups, respectively. The corresponding proportions of nighttime visits (11 PM to 7 AM) in the non-mistriage and overtriage groups were 19% and 26.3%. Regarding referrals, self-referred patients accounted for 92.9% and 85.2% of the non-mistriage and undertriage groups, respectively, whereas the corresponding proportions of clinic-referred patients were 6.3% and 13.4%. Regarding final disposition, 9.4% and 0.4% of the patients in the non-mistriage group were admitted to a general ward and the intensive care unit, respectively. The corresponding percentages for the undertriage group were 34.6% and 1%. The details are listed in Table 1 . Table 2 shows the demographic factors affecting mistriage through multivariate logistic regression analysis. Table 2 Multivariate logistic regression analysis of demographic parameters contributing Mistriage Variables Overtriage group Undertriage group OR 95% CI P OR 95% CI P Age < 1 years Reference - - Reference - - 1–4 years 1.25 1.21–1.3 < 0.001 0.8 0.77–0.83 < 0.001 5–9 years 0.92 0.88–0.96 < 0.001 1.09 1.05–1.14 < 0.001 10–14 years 1.01 0.96–1.05 0.7824 0.99 0.95–1.04 0.7497 Gender Female Reference - - Reference - - Male 0.94 0.92–0.96 < 0.001 1.06 1.04–1.09 < 0.001 Shift of Arrival Day (7AM-3PM) Reference - - Reference - - Evening (3PM-11PM) 1.27 1.23–1.31 < 0.001 0.79 0.76–0.81 < 0.001 Night (11PM-7AM) 1.25 1.2–1.29 < 0.001 0.8 0.77–0.83 < 0.001 Diagnosis Disease Reference - - Reference - - Trauma 0.55 0.54–0.57 < 0.001 1.8 1.74–1.86 < 0.001 Mode of Arrival Self-referred Reference - - Reference - - Referred from clinic 0.4 0.38–0.42 < 0.001 2.48 2.36–2.6 < 0.001 Outpatient department 0.25 0.21–0.3 < 0.001 3.97 3.33–4.74 < 0.001 Logistic regression analysis was adjusted for age, gender, diagnosis, triage level, and mode of arrival. OR: odd ratio, CI: confidence intervals. When comparing the difference in mistriage by age in patients younger than 1 year, the ORs for overtriage and undertriage in patients aged 1–4 years were 1.25 (95% CI, 1.21–1.30) and 0.80 (95% CI, 0.77–0.83), respectively. In the analysis by sex, the OR for overtriage in male patients relative to that in female patients was 0.94 (95% CI, 0.92–0.96); the corresponding OR for undertriage was 1.06 (95% CI, 1.04–1.09). In the analysis by visiting time, the ORs for evening and night visits in the overtriage group were 1.27 (95% CI, 1.23–1.31) and 1.25 (95% CI, 1.20–1.29), respectively, and the corresponding ORs for undertriage were 0.79 (95% CI, 0.76–0.81) and 0.80 (95% CI, 0.77–0.83), compared to daytime visits. When comparing disease and trauma, the OR for trauma compared with disease in the overtriage group was 0.55 (95% CI, 0.54–0.57). The corresponding OR for the undertriage group was 1.80 (95% CI, 1.74–1.86). Differences in terms of arrival modes showed that compared with self-referrals, referrals from clinics had ORs of 0.40 (95% CI, 0.38–0.42) and 2.48 (95% CI, 2.36–2.60) in the overtriage and undertriage groups, respectively. For referrals from an outpatient department, the corresponding ORs were 0.25 (95% CI, 0.21–0.30) and 3.97 (95% CI, 3.33–4.74). Table 3 shows patient characteristics according to hospital size. In both the overtriage and undertriage groups, the proportion of patients younger than 1 year was the highest in district EMCs (overtriage: 19.2%, undertriage: 19.1%), followed by regional EMCs (overtriage: 12.2%, undertriage: 14.1%) and regional EMIs (overtriage: 5.1%, undertriage: 3.6%) (p < 0.001). Similarly, for patients aged 1–4 years, district EMCs had the highest proportions (overtriage: 56.2%, undertriage: 43.7%), followed by regional EMCs (overtriage: 48.8%, undertriage: 43.3%) and regional EMIs (overtriage: 40.3%, undertriage: 34.5%) (p < 0.001). Regarding the final disposition in the overtriage group, the proportions of general ward admissions in district EMCs, regional EMCs, and regional EMIs were 2.9%, 5.2%, and 6.3%, respectively, whereas the corresponding proportions in the undertriage group were 42.5%, 29.3%, and 17.3% (p < 0.001). Table 3 Comparison of mistriaged patients by hospital size Variables Overtriage group (N = 35,897) Undertriage group (N = 94,006) District EMC (N = 21,498) Regional EMC (N = 7,010) Regional EMI (N = 7,389) P District EMC (N = 39,674) Regional EMC (N = 52,189) Regional EMI (N = 2,143) P Age, yr < 1 years 4,133 (19.2%) 854 (12.2%) 377 (5.1%) < 0.001 7,594 (19.1%) 7,333 (14.1%) 77 (3.6%) < 0.001 1–4 years 12,089 (56.2%) 3,419 (48.8%) 2,976 (40.3%) 17,348 (43.7%) 22,593 (43.3%) 739 (34.5%) 5–9 years 3,379 (15.7%) 1,571 (22.4%) 2,105 (28.5%) 9,074 (22.9%) 13,154 (25.2%) 632 (29.5%) 10–14 years 1,897 (8.8%) 1,166 (16.6%) 1,931 (26.1%) 5,658 (14.3%) 9,109 (17.5%) 695 (32.4%) Gender Male 12,039 (56%) 3,944 (56.3%) 4,130 (55.9%) 0.897 23,121 (58.3%) 30,465 (58.4%) 1,259 (58.7%) 0.888 Triage level KTAS 1 76 (0.4%) 70 (1%) 22 (0.3%) < 0.001 - - - < 0.001 KTAS 2 1,550 (7.2%) 626 (8.9%) 192 (2.6%) - - - KTAS 3 19,872 (92.4%) 6,314 (90.1%) 7,175 (97.1%) - - - KTAS 4 - - - 35,175 (88.7%) 48,245 (92.4%) 1,944 (90.7%) KTAS 5 - - - 4,499 (11.3%) 3,944 (7.6%) 199 (9.3%) Shift of arrival Day (7AM-3PM) 5,336 (24.8%) 1,599 (22.8%) 1,256 (17%) < 0.001 12,353 (31.1%) 14,542 (27.9%) 474 (22.1%) < 0.001 Evening (3PM-11PM) 10,293 (47.9%) 3,582 (51.1%) 4,374 (59.2%) 19,091 (48.1%) 26,358 (50.5%) 1,265 (59%) Night (11PM-7AM) 5,869 (27.3%) 1,829 (26.1%) 1,759 (23.8%) 8,230 (20.7%) 11,289 (21.6%) 404 (18.9%) Mode of arrival Self-referred 19,688 (91.6%) 6,668 (95.1%) 7,276 (98.5%) < 0.001 32,203 (81.2%) 45,850 (87.9%) 2,084 (97.2%) < 0.001 Outpatient department 95 (0.4%) 35 (0.5%) 9 (0.1%) 668 (1.7%) 625 (1.2%) 4 (0.2%) Referred from clinic 1,715 (8%) 307 (4.4%) 104 (1.4%) 6,803 (17.1%) 5,714 (10.9%) 55 (2.6%) Diagnosis Disease 19,439 (90.4%) 5,454 (77.8%) 4,928 (66.7%) < 0.001 31,268 (78.8%) 36,819 (70.5%) 1,283 (59.9%) < 0.001 Trauma 2,059 (9.6%) 1,556 (22.2%) 2,461 (33.3%) 8,406 (21.2%) 15,370 (29.5%) 860 (40.1%) Final disposition Discharged 20,822 (96.9%) 6,613 (94.3%) 6,908 (93.5%) < 0.001 21,023 (53%) 34,886 (66.8%) 1,684 (78.6%) < 0.001 Hospitalization Admission to GW 614 (2.9%) 368 (5.2%) 465 (6.3%) 16,843 (42.5%) 15,280 (29.3%) 371 (17.3%) Admission to ICU 7 (0%) 6 (0.1%) 0 (0%) 504 (1.3%) 397 (0.8%) 7 (0.3%) Admission to OR 13 (0.1%) 3 (0%) 5 (0.1%) 786 (2%) 721 (1.4%) 20 (0.9%) Transfer to other hospital 42 (0.2%) 19 (0.3%) 11 (0.1%) 517 (1.3%) 900 (1.7%) 61 (2.8%) Expired - - - 1 (0%) 3 (0%) 0 (0%) DOA 0 (0.0%) 1 (0.0%) 0 (0.0%) 0 (0%) 2 (0%) 0 (0%) Values are presented as n (%) unless otherwise indicated. KTAS: Korean triage and acuity scale, EMC: emergency medical center, EMI: emergency medical institution, GW: general ward, ICU: intensive care unit, OR: operation room, DOA: dead on arrival. Limitations This study has several limitations. First, the data used were anonymized; therefore, there is a possibility of inclusion of duplicate information for the same patient. Such a limitation is inherent and unavoidable in studies using anonymized data. Second, we analyzed triage results from NEDIS data. Therefore, we could not verify the accuracy of the final triage categorization using medical records. This is an inevitable limitation of retrospective observational studies. Finally, given that this study was based on data from South Korea, the findings may not be directly applicable to settings with different healthcare systems. Discussion In this study, we analyzed 5,462,964 patients who visited PEDs across South Korea between 2016 and 2019 to determine the mistriage rate and the risk factors affecting it. The overall proportion of mistriage was 2.4%, of which undertriage and overtriage accounted for 1.7% and 0.7%, respectively. Age, sex, arrival time, diagnosis, and arrival mode were significantly associated with mistriage, and the impact of these factors varied according to hospital size. The proportions of mistriage, overtriage, and undertriage reported previously were 32–66%, 29–59%, and 3–7%, respectively, which are significantly higher than those in this study [ 15 – 17 ]. These differences were probably owing to variations in the definitions of mistriage, triage tools, and study designs. Previously, overtriage and undertriage were defined as cases categorized one or more levels higher or lower than the actual triage level. However, in this study, overtriage was defined as when a patient categorized as KTAS 1–3 was actually KTAS 4–5, with undertriage defined conversely. Differences in inclusion criteria were also observed. In previous studies, clinicians reviewed the medical records of patients who visited PEDs to identify cases that required a change in the triage level and included them in the studies. However, we only included patients if the PED clinicians changed the triage level prior to discharge from the PED. A previous KTAS-based study in adult patients that applied the same definition of mistriage and used the same inclusion criteria reported mistriage, overtriage, and undertriage rates of 3.5%, 0.6%, and 2.9%, respectively [ 18 ]. The overtriage risk was higher in pediatric patients aged 1–4 years. This is consistent with previous studies. In a study of pediatric patients presenting to a US PED, the overtriage risk was higher in the 1–5 year age group [ 19 ]. Accurate triage level assessment is challenging in the 1–4 year age group. The first reason for this is that the children recognize the hospital environment and react negatively to it, which makes accurate vital sign determination difficult. Another reason is that such young children may not be able to articulate their symptoms and may even exaggerate them. Therefore, PED clinicians should focus more on understanding and considering age-appropriate normal vital signs and assessing nonverbal clinical signs in this age group. The undertriage risk was higher in pediatric patients aged < 1 year than in those aged 1–4 years. This finding is in line with that of a previous study, in which the undertriage rate was the highest (10.9%) in infants among pediatric trauma patients [ 20 ]. It is difficult to assess infants because healthy and sick infants can exhibit similar symptoms such as crying and irritability. Therefore, some symptoms may be easily overlooked even in cases of severe disease [ 21 ]. These characteristics can lead to delays in early recognition and treatment. Additionally, this age group is particularly susceptible to bacterial infections. One study reported that infants aged < 1 year accounted for approximately 70.8% of all pediatric bacteremia cases [ 22 ]. Specifically, infants aged < 3 months are classified as a high-risk group, with fever alone increasing the possibility of bacteremia [ 23 ]. Therefore, to assess this age group accurately, triage that considers age-related characteristics is required. Previous research suggests reinforcing specific vital signs with high sensitivity in infants, such as heart rate and oxygen saturation, in addition to current assessments, even in infants who do not appear sick [ 21 ]. When analyzed by sex, the overtriage risk was higher in female patients. To our knowledge, no previous study has examined mistriage trends according to sex in pediatric patients. Meanwhile, a study analyzing data from PED visits in five European countries found that, after adjusting for age, triage level, and clinical presentation, girls tended to undergo more diagnostic tests compared with boys [ 24 ]. This suggests that girls may be perceived as having a more severe condition or an uncertain diagnosis by healthcare providers in the same clinical setting. This perception may be due to sex-specific differences in symptom presentation, communication skills, caregiver responses, and implicit sex bias [ 24 ]. On the other hand, undertriage risk was higher in male patients. This may be attributed to sex-specific differences in the expression of pain and discomfort. For instance, a neonatal pain response study revealed that compared with girls, boys were more likely to suppress pain when exposed to the same stimulus immediately after birth [ 25 ]. These expressive characteristics of boys, when combined with differences in healthcare providers’ perceptions, may lead to undertriage. Considering these possible sex differences in triage assessment, a more objective and sex-sensitive assessment system is necessary, and further research is required. There was also a difference in triage accuracy based on the time of day of the PED visits. Visits during the evening and night shifts were associated with a higher overtriage risk than daytime visits, whereas daytime visits were more likely to result in undertriage. This trend was partially reported in previous studies. One study reported that increased PED crowding during these hours may lead providers to assign higher triage levels as a safety-focused approach, potentially resulting in overtriage, which is comparable to the results of our study [ 26 ]. However, another study on US PEDs reported an increased risk of undertriage in patients visiting in the evening and at night, which contrasts with the findings of our study [ 27 ]. The authors interpreted that differences in patient populations and PED crowding at different times of the day may have contributed to the underestimation of urgency. Although the results were different, both studies provided the shared implication that PED crowding by time of day can affect triage accuracy. These findings suggest that systematic interventions that consider time-specific patient characteristics and clinician workload are necessary for improving triage accuracy. Further research is required to reduce the risk of mistriage according to time zone and crowding. Pediatric patients who visited PEDs for diseases were overtriaged more often than those who visited for trauma. No previous study has directly compared overtriage rates between the aforementioned two groups of children. The reason for this difference is probably that many pediatric patients visiting PEDs for diseases have a fever. According to previous studies, the most common complaint in PED visits was fever, and the proportion of patients with diseases accompanied by fever was reported to be 19.4–30.8% of all visits [ 28 , 29 ]. Children have physiological characteristics that make them have a higher than normal body temperature and more prone to fever than adults; therefore, in triage based on vital signs in children, disease severity may be overestimated [ 30 ]. Therefore, a careful evaluation of the physiological characteristics of children is necessary. In contrast, pediatric patients who visited for trauma were more likely to be undertriaged than those who visited for diseases. A previous study using data from the Nationwide Emergency Department Sample in the US reported that undertriage was more common in pediatric patients aged < 16 years with trauma [ 31 ]. Pediatric trauma often appears mild; therefore, PED clinicians may underestimate its severity and misclassify it. Therefore, careful evaluation of pediatric patients with trauma is necessary, and supplementation of the triage system to reflect these characteristics may be required. Self-referred pediatric patients are at a higher risk of overtriage than those referred by outpatient departments or clinics. No previous study has directly analyzed the association between arrival mode and triage accuracy. However, previous studies have suggested that caregivers of self-referred patients perceive their child's condition as more severe and urgent [ 32 ]. These perceptions may affect the triage assessment, making PED clinicians more cautious and conservative when assigning triage levels [ 32 ]. Meanwhile, patients referred by clinics or outpatient departments are at a greater risk of undertriage compared with self-referred patients. In physician-referred patients, simple initial treatments such as antipyretics may temporarily stabilize vital signs or appearance, even if the actual severity of the illness has not changed. This suggests that the patient's course and treatment history should be considered during triage. Further research is needed on the relationship between the arrival mode and mistriage. The proportion of pediatric patients aged < 1 year and 1–4 years was the highest among both overtriaged and undertriaged patients and increased with hospital size. These findings suggest that triage assessment of infants and young children is challenging and that this age group should be more carefully assessed in larger hospitals. Therefore, in district EMCs with a high influx of critically ill patients, specialized training providers and systematic response strategies are needed to increase triage accuracy in young pediatric patients. The hospitalization rate for undertriaged patients was the highest in district EMCs, followed by regional EMCs and EMIs. District EMCs are tertiary care hospitals with a higher capacity for critically ill patients and a potentially higher influx of such patients. Considering this, the high hospitalization rate in the undertriage group in district EMCs suggests that some critically ill patients may have been undertriaged during the early stages. Undertriage in this setting may lead to greater clinical risk. Therefore, further research is required on methods that can more accurately reflect the severity of the early triage process. In conclusion, this study identified the factors associated with PedKTAS mistriage in children who visited PEDs. Factors associated with overtriage were age of 1–4 years, female sex, evening and nighttime visits, visits for diseases, and self-referrals. Factors associated with undertriage were infancy, age of 5–9 years, male sex, daytime visits, visits for trauma, and referrals by clinics or outpatient departments. Accurate triage that considers these factors will help ensure timely care for pediatric patients and the efficient use of PED resources. Abbreviations CI Confidence Interval CTAS Canadian Emergency Department Triage and Acuity Scale ED Emergency Department EMC Emergency Medical Center EMI Emergency Medical Institution ESI Emergency Severity Index KTAS Korean Triage and Acuity Scale MTS Manchester Triage Scale NEDIS National Emergency Department Information System OR Odds Ratio PED Pediatric Emergency Department PedKTAS Pediatric Korean Triage and Acuity Scale R R Foundation for Statistical Computing Declarations Ethics approval and consent to participate The study was conducted in accordance with the Declaration of Helsinki and was approved by the Institutional Review Board of the Catholic University of Korea (IRB approval no. KC21ZASI0798). The requirement for informed consent was waived due to the retrospective nature of the study. Consent for publication Not applicable Availability of data and materials The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests No financial or non-financial benefits have been received or will be received from any party related directly or indirectly to the subjects of this article. Funding The authors wish to acknowledge the financial support of the Catholic Medical Center Research Foundation made in the program year of 2024. They wish to acknowledge the financial support of the Catholic Medical Center Research Foundation made in the program year of 2025. Authors' contributions All authors conceived and designed the study. JR and AC drafted the original manuscript. JR and WB reviewed and edited the manuscript. AC and SK carried out visualization, validation, software, formal analysis, and data curation. SK, BJ and WB supervised the study, provided resources, managed project administration, and were responsible for methodology, investigation, and conceptualization. All authors have read and approved the final manuscript, and WB serves as guarantor of the work. Acknowledgements Not applicable References Di Somma S, Paladino L, Vaughan L, Lalle I, Magrini L, Magnanti M. Overcrowding in emergency department: an international issue. Intern Emerg Med. 2015;10(2):171-5. Center NEM. 2023 Emergency Medical Statistics Annual Report. Seoul: National Emergency Medical Center; 2024 2024. de Magalhães-Barbosa MC, Robaina JR, Prata-Barbosa A, de Souza Lopes C. Validity of triage systems for paediatric emergency care: a systematic review. Emerg Med J. 2017;34(11):711-9. Lee K, Cho S, Lee J, Lim T, Park I, Lee J. Study for standardization of Korean triage and acuity scale. Ministry of Health and Welfare; 2012. Lee B, Park JD, Kwak YH. Clinical considerations when applying vital signs in pediatric Korean triage and acuity scale. J Korean Med Sci. 2017;32(10):1702. Lim T, Park I, Je S. Pediatric Korean triage and acuity scale. Pediatr Emerg Med J. 2015;2(2):53-8. Bae W, Choi A, Youn CS, Kim S, Park KN, Kim K. Predictive validity of a new triage system for outcomes in patients visiting pediatric emergency departments: a nationwide study in Korea. Children (Basel). 2023;10(6):935. Dengler BA, Plaza-Wüthrich S, Chick RC, Muir MT, Bartanusz V. Secondary overtriage in patients with complicated mild traumatic brain injury: an observational study and socioeconomic analysis of 1447 hospitalizations. Neurosurgery. 2020;86(3):374-82. Grossmann FF, Zumbrunn T, Ciprian S, Stephan FP, Woy N, Bingisser R, et al. Undertriage in older emergency department patients—tilting against windmills? PLoS One. 2014;9(8):e106203. Park J, Lim T. Korean triage and acuity scale (KTAS). J Korean Soc Emerg Med. 2017;28(6):547-51. Committee K. Korean Triage and Acuity Scale manual version 3. Korean Triage and Acuity Scale manual version 3. Paju: Koonja; 2019. p. 11–30. Yang J, Lee E. Inter-rater reliability of Korean Triage and Acuity Scale (KTAS) among the research nurses and the triage nurses. J East-West Nurs Res. 2020;26(1):91–9. Korea S. The 7th Korean Standard Disease Classification (KCD-7) Revision and Announcement: Statistics Korea; 2022 [Available from: http://www.kostat.go.kr/portal/korea/kor_nw/1/15/index.board?bmode=read&aSeq=346904. Organization WH. International Statistical Classification of Diseases and Related Health Problems (ICD): World Health Organization; 2022 [Available from: https://www.who.int/standards/classifications/classification-of-diseases. Travers DA, Waller AE, Katznelson J, Agans R. Reliability and validity of the emergency severity index for pediatric triage. Acad Emerg Med. 2009;16(9):843–9. Frankenberger WD, Zorc JJ, Ten Have ED, Brodecki D, Faig WG. Triage accuracy in pediatrics using the Emergency Severity Index. J Emerg Nurs. 2024;50(2):207–14. Sax DR, Warton EM, Kene MV, Ballard DW, Vitale TJ, Timm JA, et al. Emergency severity index version 4 and triage of pediatric emergency department patients. JAMA Pediatr. 2024;178(10):1027–34. Jung S, Yi Y. Incidence of overtriage and undertriage and associated factors: A cross‐sectional study using a secondary data analysis. J Adv Nurs. 2024;80(4):1405–16. Geanacopoulos AT, Peltz A, Melton K, Neuman MI, Gutman CK, Walsh KE, et al. Pediatric triage accuracy in pediatric and general emergency departments. Hosp Pediatr. 2025;15(1):37–45. Ngo LC, Carroll HM, Massimilian SS, Garapaty N, Palladino K, Samuels SK, et al. Optimizing triage practice in pediatric trauma: lessons from under-triage and over-triage rates and risk factors. Am Surg. 2024;90(7):1892–5. Hopman A, Talsma ES, Mook-Kanamori DO, Pas ABT, Narayen IC. Aspects of triage for infants: a narrative review. Eur J Pediatr. 2025;184(5):294. Kellogg JA, Manzella JP, Bankert DA. Frequency of low-level bacteremia in children from birth to fifteen years of age. J Clin Microbiol. 2000;38(6):2181–5. Ferreira M, Santos M, Rodrigues J, Diogo C, Resende C, Baptista C, et al. Epidemiology of bacteremia in a pediatric population – A 10-year study. Enferm Infecc Microbiol Clin (Engl Ed). 2023;41(2):85–91. Zachariasse JM, Borensztajn DM, Nieboer D, Alves CF, Greber-Platzer S, Keyzer-Dekker CM, et al. Sex-specific differences in children attending the emergency department: prospective observational study. BMJ Open. 2020;10(9):e035918. Guinsburg R, de Araújo Peres C, de Almeida MFB, Balda RdCX, Berenguel RC, Tonelotto J, et al. Differences in pain expression between male and female newborn infants. Pain. 2000;85(1-2):127–33. Huabbangyang T, Rojsaengroeng R, Tiyawat G, Silakoon A, Vanichkulbodee A, Sri-On J, et al. Associated factors of under and over-triage based on the emergency severity index; a retrospective cross-sectional study. Arch Acad Emerg Med. 2023;11(1):e57. Zachariasse JM, Kuiper JW, de Hoog M, Moll HA, van Veen M. Safety of the Manchester triage system to detect critically ill children at the emergency department. J Pediatr. 2016;177:232–7.e1. Chai H-S, Park GJ, Kim YM, Kim SC, Lee JH, Kim H, et al. Characteristics of frequent pediatric emergency department users at a tertiary university hospital. J Korean Soc Emerg Med. 2022;33(5):421–8. Piller S, Herzog D. The burden of visits for fever at a paediatric emergency room: A retrospective study on patients presenting at the cantons hospital of Fribourg, a peripheral public hospital of Switzerland. Pediatr Health Med Ther. 2019:147–52. El-Radhi ASM. Why is the evidence not affecting the practice of fever management? Arch Dis Child. 2008;93(11):918–20. Peng J, Wheeler K, Groner JI, Haley KJ, Xiang H. Undertriage of pediatric major trauma patients in the United States. Clin Pediatr. 2017;56(9):845–53. Butun A, Linden M, Lynn F, McGaughey J. Exploring parents’ reasons for attending the emergency department for children with minor illnesses: a mixed methods systematic review. Emerg Med J. 2019;36(1):39–46. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 18 Sep, 2025 Editor invited by journal 28 Aug, 2025 Editor assigned by journal 26 Aug, 2025 Submission checks completed at journal 26 Aug, 2025 First submitted to journal 24 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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1","display":"","copyAsset":false,"role":"figure","size":141017,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7449021/v1/410bfbf03947255f1ee791f1.png"},{"id":92480274,"identity":"2a4583e0-4e79-4b6c-9067-59bb8f2510c5","added_by":"auto","created_at":"2025-09-30 07:40:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1231164,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7449021/v1/a29e6be2-cdeb-4de1-8b58-4d80b1b7e434.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Factors Associated with the Misclassification of a New Triage Tool in Pediatric Emergency Departments in Korea: A Nationwide Retrospective Observational Study","fulltext":[{"header":"Background","content":"\u003cp\u003eEmergency department (ED) overcrowding has increased worldwide as the number of patients visiting EDs has increased [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The number of ED visits per 1000 individuals in 2023 was 187.9 in South Korea, with pediatric patients accounting for 20.4% of the total [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In such circumstances, rapid and accurate patient triage upon arrival, by an effective assessment of patient urgency, is essential for timely and appropriate medical care and resource optimization. Since the early 1990s, various triage systems have been established worldwide, including the Canadian Emergency Department Triage and Acuity Scale (CTAS), Emergency Severity Index (ESI), and Manchester Triage Scale (MTS) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn South Korea, the Korean Triage and Acuity Scale (KTAS) was developed based on CTAS and has been applied to all patients visiting EDs since January 1, 2016 [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. KTAS includes a pediatric version (PedKTAS) for patients aged\u0026thinsp;\u0026lt;\u0026thinsp;15 years [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. PedKTAS refines age-specific ranges for normal vital signs to reflect children\u0026rsquo;s physiological characteristics and developmental stages and considers nonverbal clinical signs such as general appearance, breathing, and circulation in the triage process [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. However, the urgency triage process is complicated by age-based vital sign criteria, and factors such as pediatric patients' fear of the pediatric emergency department (PED) may influence subjective assessments, making it difficult to assess urgency [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eImportance\u003c/h3\u003e\n\u003cp\u003eMistriage is a situation where there is a discrepancy between the triage nurse-assigned urgency classification and the classification appropriate for the actual patient condition. It can be further divided into undertriage, where urgency is underestimated compared to the actual, or overtriage, where the urgency is overestimated. Mistriage has a marked negative effect on appropriate emergency medical care. Undertriage may delay the treatment of critically ill patients, whereas overtriage can cause overcrowding of PEDs and unnecessary resource utilization [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Although there have been some studies on mistriage, most of them focused on adult patients, leaving gaps in the understanding of pediatric mistriage. In particular, only a few studies have been conducted on PedKTAS-associated mistriage.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eGoals of This Investigation\u003c/h2\u003e\u003cp\u003eThis study aimed to investigate mistriage rates in pediatric cases within the PedKTAS system and identify the factors contributing to undertriage and overtriage.\u003c/p\u003e\u003c/div\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design, Setting, and Population\u003c/h2\u003e\u003cp\u003eThis retrospective observational study used data from the National Emergency Department Information System (NEDIS). NEDIS is a nationwide emergency medical network that receives real-time data from 31 district emergency medical centers (EMCs), 120 regional EMCs, and 257 regional emergency medical institutions (EMIs). Data collected between January 1, 2016, and December 31, 2019, were used. The study included patients aged\u0026thinsp;\u0026lt;\u0026thinsp;15 years who presented to a PED and excluded patients with a KTAS level of 8 or 9, those who presented for non-therapeutic reasons, and those with missing KTAS levels or medical records. District EMCs serve as tertiary-level facilities and provide comprehensive care to critically ill patients in general hospitals with 300 or more beds. These facilities receive an average of approximately 40,000 patient visits annually, of which approximately 12,000 are pediatric visits. Regional EMCs are designated as general hospitals suitable for emergency care and experience an average of approximately 30,000 patient visits annually, of which approximately 8,000 are pediatric visits. Regional EMIs, selected from general hospitals, receive an average of approximately 6,000 emergency visits annually, of which approximately 3,000 are pediatric visits.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eKTAS Algorithm\u003c/h3\u003e\n\u003cp\u003eWhen a patient arrives at the PED, the triage nurse uses the 5-level PedKTAS to determine the appropriate time for medical assessment. KTAS 1 signifies an immediate threat to life or limb and a need for aggressive treatment. KTAS 2 means there is a potential threat to life or limb and urgent care is needed. Conditions with the potential to develop into serious conditions requiring emergency care are categorized as KTAS 3 and those that could be treated or reassessed within 1\u0026ndash;2 h are categorized as KTAS 4. KTAS 5 indicates an acute but not urgent situation and may be associated with a worsening or unchanging chronic condition [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Reassessment at designated time intervals is mandatory for all patients. Continuous monitoring is required for level 1, whereas reassessment at intervals of 10, 30, 60, and 120 min is necessary for levels 2, 3, 4, and 5, respectively [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Situations with KTAS levels 1\u0026ndash;3 are generally considered urgent, whereas those with KTAS levels 4 and 5 are considered non-urgent. PedKTAS categorizes symptoms, including 166 specific symptoms, into 17 groups. Triage nurses look at the most important symptoms first, consider the pediatric assessment triangle, select the most relevant symptoms, and assign a severity level based on primary considerations, including vital signs, and secondary considerations, including nurse judgment [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003eEach PED visit was considered an independent case. Variables including age, sex, initial and final triage levels, arrival shift, arrival mode, diagnosis, EMC class, and final disposition were extracted from the patient data in NEDIS. Mistriage was defined as a case where KTAS level 1, 2, or 3, corresponding to an emergency, changed to KTAS level 4 or 5, corresponding to a non-emergency, and vice versa, between the initial and final triage. Patients were categorized into non-mistriage, overtriage, and undertriage groups accordingly. Diagnoses were made using the Korean Standard Classification of Diseases-7, the Korean version of the International Classification of Diseases, 10th Revision [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eOutcomes\u003c/h2\u003e\u003cp\u003eThe primary outcome was the incidence of and risk factors for mistriage when PedKTAS was applied. The secondary outcomes were the characteristics of mistriage according to the type of the emergency medical facility.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eThe chi-square test was used to assess statistical differences between the mistriage and non-mistriage groups. Multivariate regression analysis adjusted for age, sex, arrival shift, arrival mode, and diagnosis was conducted to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for the overtriage and undertriage groups. All statistical analyses were conducted using R version 4.0.0 (R Foundation for Statistical Computing, Vienna, Austria); a p-value of \u0026lt;\u0026thinsp;0.05 was considered significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003c/p\u003e\u003cp\u003eBetween January 2016 and December 2019, 6,847,960 cases were collected from PEDs nationwide. After excluding 1,322,689 patients with KTAS levels of 8 and 9 or unknown KTAS levels and an additional 62,307 patients with missing records, the final analysis included 5,462,964 patients. The analysis revealed 129,903 mistriage cases (2.4%). Of these, 35,897 (0.7%) and 94,006 were classified as overtriage and undertriage cases, respectively. The mistriage percentage at each level is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the characteristics of patients visiting the PED, divided into non-mistriage, overtriage, and undertriage groups. Pediatric patients aged\u0026thinsp;\u0026lt;\u0026thinsp;1 year and 1\u0026ndash;4 years accounted for 11.8% and 48.2% of the non-mistriage group, respectively.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCharacteristics of patients visiting the pediatric emergency department\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eNon-mistriage group \u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;5,313,997)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eMistriage group (N\u0026thinsp;=\u0026thinsp;129,903)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOvertriage group\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;35,897)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUndertriage group\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;94,006)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, yr\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt; 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e626,553 (11.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5,364 (14.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15,004 (16%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026ndash;4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2,561,256 (48.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18,484 (51.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e40,680 (43.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026ndash;9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,324,151 (24.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7,055 (19.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22,860 (24.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u0026ndash;14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e802,037 (15.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4,994 (13.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15,462 (16.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3,038,030 (57.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20,113 (56%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54,845 (58.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTriage level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKTAS 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10,828 (0.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e168 (0.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKTAS 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e180,616 (3.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2,368 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKTAS 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,687,363 (31.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33,361 (92.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKTAS 4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2,959,187 (55.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e85,364 (90.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKTAS 5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e476,003 (9.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8,642 (9.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eShift of arrival\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDay (7AM-3PM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,346,573 (25.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8,191 (22.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27,369 (29.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEvening (3PM-11PM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2,956,392 (55.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18,249 (50.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46,714 (49.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNight (11PM-7AM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,011,032 (19.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9,457 (26.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19,923 (21.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMode of arrival\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSelf-referred\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4,939,101 (92.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33,632 (93.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e80,137 (85.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutpatient department\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40,792 (0.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e139 (0.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1,297 (1.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReferred from clinic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e334,104 (6.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2,126 (5.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12,572 (13.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiagnosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDisease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3,728,950 (70.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29,821 (83.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e69,370 (73.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrauma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,585,047 (29.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6,076 (16.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24,636 (26.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEMC class\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDistrict EMC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1708789 (32.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21,498 (59.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39,674 (42.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegional EMC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3157306 (59.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7,010 (19.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e52,189 (55.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegional EMI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e447902 (8.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7,389 (20.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2,143 (2.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFinal disposition\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDischarged\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4,758,172 (89.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34,343 (95.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e57,593 (61.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"7\" rowspan=\"8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHospitalization\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdmission to GW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e499,276 (9.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,447 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32,494 (34.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdmission to ICU\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19,986 (0.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e908 (1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdmission to OR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13,571 (0.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21 (0.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1,527 (1.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTransfer to other hospital\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21,552 (0.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e72 (0.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1,478 (1.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExpired\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e134 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDOA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,306 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eValues are presented as n (%) unless otherwise indicated.\u003c/p\u003e\u003cp\u003eKTAS: Korean triage and acuity scale, EMC: emergency medical center, EMI: emergency medical institution, GW: general ward, ICU: intensive care unit, OR: operation room, DOA: dead on arrival.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe corresponding proportions in the overtriage group were 14.9% and 51.5% and in the undertriage group were 16% and 43.3%. Daytime visits (7 AM to 3 PM) accounted for 25.3%, 22.8%, and 29.1% of the visits in the non-mistriage, overtriage, and undertriage groups, respectively. The corresponding proportions of nighttime visits (11 PM to 7 AM) in the non-mistriage and overtriage groups were 19% and 26.3%. Regarding referrals, self-referred patients accounted for 92.9% and 85.2% of the non-mistriage and undertriage groups, respectively, whereas the corresponding proportions of clinic-referred patients were 6.3% and 13.4%. Regarding final disposition, 9.4% and 0.4% of the patients in the non-mistriage group were admitted to a general ward and the intensive care unit, respectively. The corresponding percentages for the undertriage group were 34.6% and 1%. The details are listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the demographic factors affecting mistriage through multivariate logistic regression analysis.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMultivariate logistic regression analysis of demographic parameters contributing Mistriage\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eOvertriage group\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003eUndertriage group\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt; 1 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026ndash;4 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.21\u0026ndash;1.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.77\u0026ndash;0.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026ndash;9 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.88\u0026ndash;0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.05\u0026ndash;1.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u0026ndash;14 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.96\u0026ndash;1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.7824\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.95\u0026ndash;1.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.7497\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.92\u0026ndash;0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.04\u0026ndash;1.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eShift of Arrival\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDay (7AM-3PM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEvening (3PM-11PM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.23\u0026ndash;1.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.76\u0026ndash;0.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNight (11PM-7AM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.2\u0026ndash;1.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.77\u0026ndash;0.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003eDiagnosis\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDisease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrauma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.54\u0026ndash;0.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.74\u0026ndash;1.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003eMode of Arrival\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSelf-referred\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReferred from clinic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.38\u0026ndash;0.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.36\u0026ndash;2.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutpatient department\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.21\u0026ndash;0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.33\u0026ndash;4.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003eLogistic regression analysis was adjusted for age, gender, diagnosis, triage level, and mode of arrival.\u003c/p\u003e\u003cp\u003eOR: odd ratio, CI: confidence intervals.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWhen comparing the difference in mistriage by age in patients younger than 1 year, the ORs for overtriage and undertriage in patients aged 1\u0026ndash;4 years were 1.25 (95% CI, 1.21\u0026ndash;1.30) and 0.80 (95% CI, 0.77\u0026ndash;0.83), respectively. In the analysis by sex, the OR for overtriage in male patients relative to that in female patients was 0.94 (95% CI, 0.92\u0026ndash;0.96); the corresponding OR for undertriage was 1.06 (95% CI, 1.04\u0026ndash;1.09). In the analysis by visiting time, the ORs for evening and night visits in the overtriage group were 1.27 (95% CI, 1.23\u0026ndash;1.31) and 1.25 (95% CI, 1.20\u0026ndash;1.29), respectively, and the corresponding ORs for undertriage were 0.79 (95% CI, 0.76\u0026ndash;0.81) and 0.80 (95% CI, 0.77\u0026ndash;0.83), compared to daytime visits. When comparing disease and trauma, the OR for trauma compared with disease in the overtriage group was 0.55 (95% CI, 0.54\u0026ndash;0.57). The corresponding OR for the undertriage group was 1.80 (95% CI, 1.74\u0026ndash;1.86). Differences in terms of arrival modes showed that compared with self-referrals, referrals from clinics had ORs of 0.40 (95% CI, 0.38\u0026ndash;0.42) and 2.48 (95% CI, 2.36\u0026ndash;2.60) in the overtriage and undertriage groups, respectively. For referrals from an outpatient department, the corresponding ORs were 0.25 (95% CI, 0.21\u0026ndash;0.30) and 3.97 (95% CI, 3.33\u0026ndash;4.74).\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows patient characteristics according to hospital size. In both the overtriage and undertriage groups, the proportion of patients younger than 1 year was the highest in district EMCs (overtriage: 19.2%, undertriage: 19.1%), followed by regional EMCs (overtriage: 12.2%, undertriage: 14.1%) and regional EMIs (overtriage: 5.1%, undertriage: 3.6%) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similarly, for patients aged 1\u0026ndash;4 years, district EMCs had the highest proportions (overtriage: 56.2%, undertriage: 43.7%), followed by regional EMCs (overtriage: 48.8%, undertriage: 43.3%) and regional EMIs (overtriage: 40.3%, undertriage: 34.5%) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Regarding the final disposition in the overtriage group, the proportions of general ward admissions in district EMCs, regional EMCs, and regional EMIs were 2.9%, 5.2%, and 6.3%, respectively, whereas the corresponding proportions in the undertriage group were 42.5%, 29.3%, and 17.3% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of mistriaged patients by hospital size\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eOvertriage group\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;35,897)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003eUndertriage group\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;94,006)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDistrict EMC\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;21,498)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRegional EMC\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;7,010)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRegional EMI\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;7,389)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDistrict EMC\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;39,674)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eRegional EMC\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;52,189)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eRegional EMI\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;2,143)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e\u003cp\u003eAge, yr\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt; 1 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4,133 (19.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e854 (12.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e377 (5.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7,594 (19.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7,333 (14.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e77 (3.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026ndash;4 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12,089 (56.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3,419 (48.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2,976 (40.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e17,348 (43.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e22,593 (43.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e739 (34.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026ndash;9 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3,379 (15.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,571 (22.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2,105 (28.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9,074 (22.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13,154 (25.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e632 (29.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u0026ndash;14 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,897 (8.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,166 (16.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1,931 (26.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5,658 (14.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9,109 (17.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e695 (32.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12,039 (56%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3,944 (56.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4,130 (55.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.897\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e23,121 (58.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e30,465 (58.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1,259 (58.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.888\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e\u003cp\u003eTriage level\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKTAS 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e76 (0.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e70 (1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22 (0.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKTAS 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,550 (7.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e626 (8.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e192 (2.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKTAS 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19,872 (92.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6,314 (90.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7,175 (97.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKTAS 4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e35,175 (88.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e48,245 (92.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1,944 (90.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKTAS 5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4,499 (11.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3,944 (7.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e199 (9.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e\u003cp\u003eShift of arrival\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDay (7AM-3PM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5,336 (24.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,599 (22.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1,256 (17%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e12,353 (31.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e14,542 (27.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e474 (22.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEvening (3PM-11PM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10,293 (47.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3,582 (51.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4,374 (59.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19,091 (48.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e26,358 (50.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1,265 (59%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNight (11PM-7AM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5,869 (27.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,829 (26.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1,759 (23.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8,230 (20.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e11,289 (21.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e404 (18.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e\u003cp\u003eMode of arrival\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSelf-referred\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19,688 (91.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6,668 (95.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7,276 (98.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e32,203 (81.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e45,850 (87.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2,084 (97.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutpatient department\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e95 (0.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35 (0.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (0.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e668 (1.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e625 (1.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4 (0.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReferred from clinic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,715 (8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e307 (4.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e104 (1.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6,803 (17.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5,714 (10.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e55 (2.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e\u003cp\u003eDiagnosis\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDisease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19,439 (90.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5,454 (77.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4,928 (66.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e31,268 (78.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e36,819 (70.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1,283 (59.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrauma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2,059 (9.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,556 (22.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2,461 (33.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8,406 (21.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e15,370 (29.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e860 (40.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e\u003cp\u003eFinal disposition\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDischarged\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20,822 (96.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6,613 (94.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6,908 (93.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"7\" rowspan=\"8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e21,023 (53%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e34,886 (66.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1,684 (78.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"7\" rowspan=\"8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHospitalization\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdmission to GW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e614 (2.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e368 (5.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e465 (6.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16,843 (42.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e15,280 (29.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e371 (17.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdmission to ICU\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (0.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e504 (1.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e397 (0.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e7 (0.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdmission to OR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13 (0.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (0.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e786 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e721 (1.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e20 (0.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTransfer to other hospital\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42 (0.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (0.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11 (0.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e517 (1.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e900 (1.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e61 (2.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExpired\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDOA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e\u003cp\u003eValues are presented as n (%) unless otherwise indicated.\u003c/p\u003e\u003cp\u003eKTAS: Korean triage and acuity scale, EMC: emergency medical center, EMI: emergency medical institution, GW: general ward, ICU: intensive care unit, OR: operation room, DOA: dead on arrival.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eThis study has several limitations. First, the data used were anonymized; therefore, there is a possibility of inclusion of duplicate information for the same patient. Such a limitation is inherent and unavoidable in studies using anonymized data. Second, we analyzed triage results from NEDIS data. Therefore, we could not verify the accuracy of the final triage categorization using medical records. This is an inevitable limitation of retrospective observational studies. Finally, given that this study was based on data from South Korea, the findings may not be directly applicable to settings with different healthcare systems.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we analyzed 5,462,964 patients who visited PEDs across South Korea between 2016 and 2019 to determine the mistriage rate and the risk factors affecting it. The overall proportion of mistriage was 2.4%, of which undertriage and overtriage accounted for 1.7% and 0.7%, respectively. Age, sex, arrival time, diagnosis, and arrival mode were significantly associated with mistriage, and the impact of these factors varied according to hospital size.\u003c/p\u003e\u003cp\u003eThe proportions of mistriage, overtriage, and undertriage reported previously were 32\u0026ndash;66%, 29\u0026ndash;59%, and 3\u0026ndash;7%, respectively, which are significantly higher than those in this study [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. These differences were probably owing to variations in the definitions of mistriage, triage tools, and study designs. Previously, overtriage and undertriage were defined as cases categorized one or more levels higher or lower than the actual triage level. However, in this study, overtriage was defined as when a patient categorized as KTAS 1\u0026ndash;3 was actually KTAS 4\u0026ndash;5, with undertriage defined conversely. Differences in inclusion criteria were also observed. In previous studies, clinicians reviewed the medical records of patients who visited PEDs to identify cases that required a change in the triage level and included them in the studies. However, we only included patients if the PED clinicians changed the triage level prior to discharge from the PED. A previous KTAS-based study in adult patients that applied the same definition of mistriage and used the same inclusion criteria reported mistriage, overtriage, and undertriage rates of 3.5%, 0.6%, and 2.9%, respectively [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe overtriage risk was higher in pediatric patients aged 1\u0026ndash;4 years. This is consistent with previous studies. In a study of pediatric patients presenting to a US PED, the overtriage risk was higher in the 1\u0026ndash;5 year age group [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Accurate triage level assessment is challenging in the 1\u0026ndash;4 year age group. The first reason for this is that the children recognize the hospital environment and react negatively to it, which makes accurate vital sign determination difficult. Another reason is that such young children may not be able to articulate their symptoms and may even exaggerate them. Therefore, PED clinicians should focus more on understanding and considering age-appropriate normal vital signs and assessing nonverbal clinical signs in this age group.\u003c/p\u003e\u003cp\u003eThe undertriage risk was higher in pediatric patients aged\u0026thinsp;\u0026lt;\u0026thinsp;1 year than in those aged 1\u0026ndash;4 years. This finding is in line with that of a previous study, in which the undertriage rate was the highest (10.9%) in infants among pediatric trauma patients [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. It is difficult to assess infants because healthy and sick infants can exhibit similar symptoms such as crying and irritability. Therefore, some symptoms may be easily overlooked even in cases of severe disease [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. These characteristics can lead to delays in early recognition and treatment. Additionally, this age group is particularly susceptible to bacterial infections. One study reported that infants aged\u0026thinsp;\u0026lt;\u0026thinsp;1 year accounted for approximately 70.8% of all pediatric bacteremia cases [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Specifically, infants aged\u0026thinsp;\u0026lt;\u0026thinsp;3 months are classified as a high-risk group, with fever alone increasing the possibility of bacteremia [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Therefore, to assess this age group accurately, triage that considers age-related characteristics is required. Previous research suggests reinforcing specific vital signs with high sensitivity in infants, such as heart rate and oxygen saturation, in addition to current assessments, even in infants who do not appear sick [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWhen analyzed by sex, the overtriage risk was higher in female patients. To our knowledge, no previous study has examined mistriage trends according to sex in pediatric patients. Meanwhile, a study analyzing data from PED visits in five European countries found that, after adjusting for age, triage level, and clinical presentation, girls tended to undergo more diagnostic tests compared with boys [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This suggests that girls may be perceived as having a more severe condition or an uncertain diagnosis by healthcare providers in the same clinical setting. This perception may be due to sex-specific differences in symptom presentation, communication skills, caregiver responses, and implicit sex bias [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. On the other hand, undertriage risk was higher in male patients. This may be attributed to sex-specific differences in the expression of pain and discomfort. For instance, a neonatal pain response study revealed that compared with girls, boys were more likely to suppress pain when exposed to the same stimulus immediately after birth [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. These expressive characteristics of boys, when combined with differences in healthcare providers\u0026rsquo; perceptions, may lead to undertriage. Considering these possible sex differences in triage assessment, a more objective and sex-sensitive assessment system is necessary, and further research is required.\u003c/p\u003e\u003cp\u003eThere was also a difference in triage accuracy based on the time of day of the PED visits. Visits during the evening and night shifts were associated with a higher overtriage risk than daytime visits, whereas daytime visits were more likely to result in undertriage. This trend was partially reported in previous studies. One study reported that increased PED crowding during these hours may lead providers to assign higher triage levels as a safety-focused approach, potentially resulting in overtriage, which is comparable to the results of our study [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. However, another study on US PEDs reported an increased risk of undertriage in patients visiting in the evening and at night, which contrasts with the findings of our study [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The authors interpreted that differences in patient populations and PED crowding at different times of the day may have contributed to the underestimation of urgency. Although the results were different, both studies provided the shared implication that PED crowding by time of day can affect triage accuracy. These findings suggest that systematic interventions that consider time-specific patient characteristics and clinician workload are necessary for improving triage accuracy. Further research is required to reduce the risk of mistriage according to time zone and crowding.\u003c/p\u003e\u003cp\u003ePediatric patients who visited PEDs for diseases were overtriaged more often than those who visited for trauma. No previous study has directly compared overtriage rates between the aforementioned two groups of children. The reason for this difference is probably that many pediatric patients visiting PEDs for diseases have a fever. According to previous studies, the most common complaint in PED visits was fever, and the proportion of patients with diseases accompanied by fever was reported to be 19.4\u0026ndash;30.8% of all visits [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Children have physiological characteristics that make them have a higher than normal body temperature and more prone to fever than adults; therefore, in triage based on vital signs in children, disease severity may be overestimated [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Therefore, a careful evaluation of the physiological characteristics of children is necessary. In contrast, pediatric patients who visited for trauma were more likely to be undertriaged than those who visited for diseases. A previous study using data from the Nationwide Emergency Department Sample in the US reported that undertriage was more common in pediatric patients aged\u0026thinsp;\u0026lt;\u0026thinsp;16 years with trauma [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Pediatric trauma often appears mild; therefore, PED clinicians may underestimate its severity and misclassify it. Therefore, careful evaluation of pediatric patients with trauma is necessary, and supplementation of the triage system to reflect these characteristics may be required.\u003c/p\u003e\u003cp\u003eSelf-referred pediatric patients are at a higher risk of overtriage than those referred by outpatient departments or clinics. No previous study has directly analyzed the association between arrival mode and triage accuracy. However, previous studies have suggested that caregivers of self-referred patients perceive their child's condition as more severe and urgent [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. These perceptions may affect the triage assessment, making PED clinicians more cautious and conservative when assigning triage levels [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Meanwhile, patients referred by clinics or outpatient departments are at a greater risk of undertriage compared with self-referred patients. In physician-referred patients, simple initial treatments such as antipyretics may temporarily stabilize vital signs or appearance, even if the actual severity of the illness has not changed. This suggests that the patient's course and treatment history should be considered during triage. Further research is needed on the relationship between the arrival mode and mistriage.\u003c/p\u003e\u003cp\u003eThe proportion of pediatric patients aged\u0026thinsp;\u0026lt;\u0026thinsp;1 year and 1\u0026ndash;4 years was the highest among both overtriaged and undertriaged patients and increased with hospital size. These findings suggest that triage assessment of infants and young children is challenging and that this age group should be more carefully assessed in larger hospitals. Therefore, in district EMCs with a high influx of critically ill patients, specialized training providers and systematic response strategies are needed to increase triage accuracy in young pediatric patients.\u003c/p\u003e\u003cp\u003eThe hospitalization rate for undertriaged patients was the highest in district EMCs, followed by regional EMCs and EMIs. District EMCs are tertiary care hospitals with a higher capacity for critically ill patients and a potentially higher influx of such patients. Considering this, the high hospitalization rate in the undertriage group in district EMCs suggests that some critically ill patients may have been undertriaged during the early stages. Undertriage in this setting may lead to greater clinical risk. Therefore, further research is required on methods that can more accurately reflect the severity of the early triage process.\u003c/p\u003e\u003cp\u003eIn conclusion, this study identified the factors associated with PedKTAS mistriage in children who visited PEDs. Factors associated with overtriage were age of 1\u0026ndash;4 years, female sex, evening and nighttime visits, visits for diseases, and self-referrals. Factors associated with undertriage were infancy, age of 5\u0026ndash;9 years, male sex, daytime visits, visits for trauma, and referrals by clinics or outpatient departments. Accurate triage that considers these factors will help ensure timely care for pediatric patients and the efficient use of PED resources.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConfidence Interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCTAS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCanadian Emergency Department Triage and Acuity Scale\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eED\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEmergency Department\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eEMC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEmergency Medical Center\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eEMI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEmergency Medical Institution\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eESI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEmergency Severity Index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eKTAS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eKorean Triage and Acuity Scale\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMTS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eManchester Triage Scale\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNEDIS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNational Emergency Department Information System\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eOdds Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePED\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePediatric Emergency Department\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePedKTAS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePediatric Korean Triage and Acuity Scale\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eR Foundation for Statistical Computing\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki and was approved by the Institutional Review Board of the Catholic University of Korea (IRB approval no. KC21ZASI0798). The requirement for informed consent was waived due to the retrospective nature of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo financial or non-financial benefits have been received or will be received from any party related directly or indirectly to the subjects of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors wish to acknowledge the financial support of the Catholic Medical Center Research Foundation made in the program year of 2024. They wish to acknowledge the financial support of the Catholic Medical Center Research Foundation made in the program year of 2025.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors conceived and designed the study. JR and AC drafted the original manuscript. JR and WB reviewed and edited the manuscript. AC and SK carried out visualization, validation, software, formal analysis, and data curation. SK, BJ and WB supervised the study, provided resources, managed project administration, and were responsible for methodology, investigation, and conceptualization. All authors have read and approved the final manuscript, and WB serves as guarantor of the work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDi Somma S, Paladino L, Vaughan L, Lalle I, Magrini L, Magnanti M. Overcrowding in emergency department: an international issue. Intern Emerg Med. 2015;10(2):171-5.\u003c/li\u003e\n\u003cli\u003eCenter NEM. 2023 Emergency Medical Statistics Annual Report. Seoul: National Emergency Medical Center; 2024 2024.\u003c/li\u003e\n\u003cli\u003ede Magalh\u0026atilde;es-Barbosa MC, Robaina JR, Prata-Barbosa A, de Souza Lopes C. Validity of triage systems for paediatric emergency care: a systematic review. Emerg Med J. 2017;34(11):711-9.\u003c/li\u003e\n\u003cli\u003eLee K, Cho S, Lee J, Lim T, Park I, Lee J. Study for standardization of Korean triage and acuity scale. Ministry of Health and Welfare; 2012.\u003c/li\u003e\n\u003cli\u003eLee B, Park JD, Kwak YH. Clinical considerations when applying vital signs in pediatric Korean triage and acuity scale. J Korean Med Sci. 2017;32(10):1702.\u003c/li\u003e\n\u003cli\u003eLim T, Park I, Je S. Pediatric Korean triage and acuity scale. Pediatr Emerg Med J. 2015;2(2):53-8.\u003c/li\u003e\n\u003cli\u003eBae W, Choi A, Youn CS, Kim S, Park KN, Kim K. Predictive validity of a new triage system for outcomes in patients visiting pediatric emergency departments: a nationwide study in Korea. Children (Basel). 2023;10(6):935.\u003c/li\u003e\n\u003cli\u003eDengler BA, Plaza-W\u0026uuml;thrich S, Chick RC, Muir MT, Bartanusz V. Secondary overtriage in patients with complicated mild traumatic brain injury: an observational study and socioeconomic analysis of 1447 hospitalizations. Neurosurgery. 2020;86(3):374-82.\u003c/li\u003e\n\u003cli\u003eGrossmann FF, Zumbrunn T, Ciprian S, Stephan FP, Woy N, Bingisser R, et al. Undertriage in older emergency department patients\u0026mdash;tilting against windmills? PLoS One. 2014;9(8):e106203.\u003c/li\u003e\n\u003cli\u003ePark J, Lim T. Korean triage and acuity scale (KTAS). J Korean Soc Emerg Med. 2017;28(6):547-51.\u003c/li\u003e\n\u003cli\u003eCommittee K. Korean Triage and Acuity Scale manual version 3. Korean Triage and Acuity Scale manual version 3. Paju: Koonja; 2019. p. 11\u0026ndash;30.\u003c/li\u003e\n\u003cli\u003eYang J, Lee E. Inter-rater reliability of Korean Triage and Acuity Scale (KTAS) among the research nurses and the triage nurses. J East-West Nurs Res. 2020;26(1):91\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eKorea S. The 7th Korean Standard Disease Classification (KCD-7) Revision and Announcement: Statistics Korea; 2022 [Available from: http://www.kostat.go.kr/portal/korea/kor_nw/1/15/index.board?bmode=read\u0026amp;aSeq=346904.\u003c/li\u003e\n\u003cli\u003eOrganization WH. International Statistical Classification of Diseases and Related Health Problems (ICD): World Health Organization; 2022 [Available from: https://www.who.int/standards/classifications/classification-of-diseases.\u003c/li\u003e\n\u003cli\u003eTravers DA, Waller AE, Katznelson J, Agans R. Reliability and validity of the emergency severity index for pediatric triage. Acad Emerg Med. 2009;16(9):843\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eFrankenberger WD, Zorc JJ, Ten Have ED, Brodecki D, Faig WG. Triage accuracy in pediatrics using the Emergency Severity Index. J Emerg Nurs. 2024;50(2):207\u0026ndash;14.\u003c/li\u003e\n\u003cli\u003eSax DR, Warton EM, Kene MV, Ballard DW, Vitale TJ, Timm JA, et al. Emergency severity index version 4 and triage of pediatric emergency department patients. JAMA Pediatr. 2024;178(10):1027\u0026ndash;34.\u003c/li\u003e\n\u003cli\u003eJung S, Yi Y. Incidence of overtriage and undertriage and associated factors: A cross‐sectional study using a secondary data analysis. J Adv Nurs. 2024;80(4):1405\u0026ndash;16.\u003c/li\u003e\n\u003cli\u003eGeanacopoulos AT, Peltz A, Melton K, Neuman MI, Gutman CK, Walsh KE, et al. Pediatric triage accuracy in pediatric and general emergency departments. Hosp Pediatr. 2025;15(1):37\u0026ndash;45.\u003c/li\u003e\n\u003cli\u003eNgo LC, Carroll HM, Massimilian SS, Garapaty N, Palladino K, Samuels SK, et al. Optimizing triage practice in pediatric trauma: lessons from under-triage and over-triage rates and risk factors. Am Surg. 2024;90(7):1892\u0026ndash;5.\u003c/li\u003e\n\u003cli\u003eHopman A, Talsma ES, Mook-Kanamori DO, Pas ABT, Narayen IC. Aspects of triage for infants: a narrative review. Eur J Pediatr. 2025;184(5):294.\u003c/li\u003e\n\u003cli\u003eKellogg JA, Manzella JP, Bankert DA. Frequency of low-level bacteremia in children from birth to fifteen years of age. J Clin Microbiol. 2000;38(6):2181\u0026ndash;5.\u003c/li\u003e\n\u003cli\u003eFerreira M, Santos M, Rodrigues J, Diogo C, Resende C, Baptista C, et al. Epidemiology of bacteremia in a pediatric population \u0026ndash; A 10-year study. Enferm Infecc Microbiol Clin (Engl Ed). 2023;41(2):85\u0026ndash;91.\u003c/li\u003e\n\u003cli\u003eZachariasse JM, Borensztajn DM, Nieboer D, Alves CF, Greber-Platzer S, Keyzer-Dekker CM, et al. Sex-specific differences in children attending the emergency department: prospective observational study. BMJ Open. 2020;10(9):e035918.\u003c/li\u003e\n\u003cli\u003eGuinsburg R, de Ara\u0026uacute;jo Peres C, de Almeida MFB, Balda RdCX, Berenguel RC, Tonelotto J, et al. Differences in pain expression between male and female newborn infants. Pain. 2000;85(1-2):127\u0026ndash;33.\u003c/li\u003e\n\u003cli\u003eHuabbangyang T, Rojsaengroeng R, Tiyawat G, Silakoon A, Vanichkulbodee A, Sri-On J, et al. Associated factors of under and over-triage based on the emergency severity index; a retrospective cross-sectional study. Arch Acad Emerg Med. 2023;11(1):e57.\u003c/li\u003e\n\u003cli\u003eZachariasse JM, Kuiper JW, de Hoog M, Moll HA, van Veen M. Safety of the Manchester triage system to detect critically ill children at the emergency department. J Pediatr. 2016;177:232\u0026ndash;7.e1.\u003c/li\u003e\n\u003cli\u003eChai H-S, Park GJ, Kim YM, Kim SC, Lee JH, Kim H, et al. Characteristics of frequent pediatric emergency department users at a tertiary university hospital. J Korean Soc Emerg Med. 2022;33(5):421\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003ePiller S, Herzog D. The burden of visits for fever at a paediatric emergency room: A retrospective study on patients presenting at the cantons hospital of Fribourg, a peripheral public hospital of Switzerland. Pediatr Health Med Ther. 2019:147\u0026ndash;52.\u003c/li\u003e\n\u003cli\u003eEl-Radhi ASM. Why is the evidence not affecting the practice of fever management? Arch Dis Child. 2008;93(11):918\u0026ndash;20.\u003c/li\u003e\n\u003cli\u003ePeng J, Wheeler K, Groner JI, Haley KJ, Xiang H. Undertriage of pediatric major trauma patients in the United States. Clin Pediatr. 2017;56(9):845\u0026ndash;53.\u003c/li\u003e\n\u003cli\u003eButun A, Linden M, Lynn F, McGaughey J. Exploring parents\u0026rsquo; reasons for attending the emergency department for children with minor illnesses: a mixed methods systematic review. Emerg Med J. 2019;36(1):39\u0026ndash;46.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-emergency-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emmd","sideBox":"Learn more about [BMC Emergency Medicine](http://bmcemergmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/emmd","title":"BMC Emergency Medicine","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Triage, Mistriage, Pediatric emergency medicine, Child","lastPublishedDoi":"10.21203/rs.3.rs-7449021/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7449021/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eThis study aimed to investigate the factors affecting mistriage,including overtriage and undertriage, associated with the use of a new triage tool for assessing patient urgency in pediatric emergency departments (PEDs).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThis was a retrospective observational study based on the national registry data of patients aged \u0026lt; 15 years who visited PEDs between January 2016 and December 2019. Patients were classified into non-mistriage, overtriage, and undertriage groups, and the incidence and risk factors of mistriage and its characteristics according to hospital size were analyzed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eOverall, 5,462,964 patients were included, of whom 129,903 (2.4%) were excluded. Overtriage and undertriage occurred in 35,897 (0.7%) and 94,006 (1.7%) patients, respectively. The overtriage-associated factors were age of 1–4 years, female sex, evening visits, night, disease group, and self-referrals. The undertriage-associated factors were age of \u0026lt;1 year, male, daytime visits, trauma group, and referral from a clinic or outpatient department. There were also differences in the tendency for mistriage according to hospital size.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e This study identified major risk factors related to mistriage in patients in PEDs. Accurate triage that considers these factors is essential for providing appropriate treatment and efficient use of PED resources.\u003c/p\u003e","manuscriptTitle":"Factors Associated with the Misclassification of a New Triage Tool in Pediatric Emergency Departments in Korea: A Nationwide Retrospective Observational Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-30 07:16:33","doi":"10.21203/rs.3.rs-7449021/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-09-18T08:29:51+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-28T08:48:25+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-26T05:00:15+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-26T04:59:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Emergency Medicine","date":"2025-08-25T02:29:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-emergency-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emmd","sideBox":"Learn more about [BMC Emergency Medicine](http://bmcemergmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/emmd","title":"BMC Emergency Medicine","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"db494ff0-f9d2-47c3-9be3-b5e665e4bfa3","owner":[],"postedDate":"September 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-09-30T07:16:33+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-30 07:16:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7449021","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7449021","identity":"rs-7449021","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}