Archives of Academic Emergency Medicine. 2022; 10(1): e30 OR I G I N A L RE S E A RC H Factors Associated with 24-Hour Clinical Outcome of Emergency Patients; a Cohort Study Kannika Katsomboon1, Siriorn Sindhu2∗, Ketsarin Utriyaprasit2, Chukiat Viwatwongkasem3 1. DNS candidate, Faculty of Nursing, Mahidol University, Thailand. 2. Department of Surgical Nursing, Faculty of Nursing, Mahidol University, Thailand. 3. Biostatistics Department, Faculty of Public Health, Mahidol University, Thailand. Received: February 2022; Accepted: March 2022; Published online: 24 April 2022 Abstract: Introduction: Pre-hospital and in-hospital emergency management play an important role in quality of care for emergency patients. This prospective cohort study aimed to determine factors associated with the 24-hour clinical outcome of emergency patients. Methods: The sample included 1,630 patients, randomly selected through multi-stage stratified sampling from 13 hospitals in 13 provinces of Thailand. Data were collected dur- ing January-November 2018. Clinical outcome was determined using pre-arrest sign score. Data were analyzed via ordinal multivariate regression analysis. Results: Factors influencing 24-hour clinical outcome of emer- gency patients were age (OR: 0.965; 95% CI: 0.96-0.97), having coronary vascular disease (CAD) (OR: 1.41; 95% CI: 1.05-1.88), and severity of illness based on Rapid Emergency Medical Score (REMS) (OR:1.09; 95% CI: 1.05- 1.15). Self-transportation and being transported by emergency medical service ambulance with non-advanced life support (EMS-Non-ALS) did not influence clinical outcome when compared to EMS-ALS transport. Being transported from a community hospital increased pre-arrest sign score 1.78 times when compared to EMS-ALS (OR: 1.78; 95% CI: 1.17-2.72). Increased transportation distance increased the risk of poor clinical outcome (OR: 1.01; 95% CI: 1.002-1.011). Length of stay in emergency department (ED-LOS) more than 4 hours (OR: 0.21; 95% CI: 0.15-0.29) and between 2-4 hours (OR: 0.60; 95% CI: 0.47-0.75) decreased the risk of poor clinical outcome when compared to ED-LOS less than 2 hours. Conclusion: Having CAD, severity of illness, increased transport distance, and ED-LOS less than 2 hours were found to negatively influence 24-hour clinical outcome of emer- gency patients. Keywords: Outcome assessment; health care; clinical decision rules; transportation of patients; patient care management; emergency treatment Cite this article as: Katsomboon K, Sindhu S, Utriyaprasit, Viwatwongkasem C. Factors Associated with 24-Hour Clinical Outcome of Emer- gency Patients; a Cohort Study. Arch Acad Emerg Med. 2022; 10(1): e30. https://doi.org/10.22037/aaem.v10i1.1590. 1. Introduction Pre-hospital emergency medical events are often associated with adverse clinical outcomes such as death or cardiopul- monary arrest. In Bulgaria, overall mortality rate of emer- gency patients treated in emergency department (ED) was 2.4/ 100000 and 70.9% of deaths happened within 2.3 hour after arrival (1). In Switzerland, the incidence of death in the emergency department (ED) was 2.6/1,000 (2). Patient- related factors, health provider-related factors and health ∗Corresponding Author: Siriorn Sindhu; Faculty of Nursing, Mahidol Univer- sity, Bangkok, Thailand. No. 2 Wang Lang Road, Siriraj, Bangkoknoi, Bangkok, 10700, Thailand. Email: siriorn.sin@mahidol.edu, Tel/Fax: +668-1817-6060, Fax: +662-412-8415, ORCID: http://orcid.org/0000-0001-9326-757X . service-related factors have been reported to affect immedi- ate and intermediate outcomes of emergency services. Age is one of the patient-related factors that contributes to mortal- ity of emergency patients (1, 3). Other patient-related factors contributing to mortality among emergency patients include poverty and late arrival to the hospital (1). Emergency medical service (EMS) systems play a very impor- tant role in improving the survival rates. Pre-hospital trans- port time and distance has been found to influence emer- gency medical service outcomes (4-6). The roles of mode of transportation to ED on outcomes of emergency patients have been examined in previous studies. In France, no sig- nificant association between mode of transportation and all- cause 30-day mortality was noted (4, 7). International liter- ature reported conflicting results on effects of length of ED This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem K. Katsomboon et al. 2 stay (ED-LOS) on inpatient mortality (8-10). Patient condi- tions on ED discharge, length of intensive care unit (ICU) stay, and death were used as outcome indicators of emer- gency management in previous studies (8, 11). These out- comes may not fully reflect the quality of emergency medi- cal service, especially when considering the relationship be- tween pre-hospital emergency management, management in ED, and ongoing management in ICU or inpatient wards following ED discharge. This study aimed to determine fac- tors associated with 24-hour clinical outcome of emergency patients. 2. Methods 2.1. Study design and setting This prospective cohort study was conducted from January to November 2018 in 13 provincial hospitals in Thailand. Data from the National Institute of Emergency Medicine Ser- vice (NIEMS, 2017) (12) was used for hospital selection. The provincial hospitals were classified into high volume (i.e., treating > 10,000 critical emergency patients/year), medium volume (i.e., treating between 4,000- 10,000 critical emer- gency patients/year), and low volume (i.e., treating < 4,000 critical emergency patients/year). There were 13, 33, and 31 high-, medium- and low-volume provincial hospitals, re- spectively. Subsequent sampling by ratio yielded 3 high- volume hospitals, 5 medium-volume hospitals, and 5 low- volume hospitals. The hospital samples totaled 13. The In- stitutional Review Board, Faculty of Nursing, Mahidol Uni- versity (No: IRB -NS2017/23.0409) approved this study for its human research ethics. The patients agreed to participate in this study and provided their consent. To comply with local requirements, additional ethics approvals were also sought from the 13 provincial hospitals before the commencement of the study. 2.2. Participants The population included emergency patients who were man- aged in EDs of provincial hospitals across Thailand. The emergency patients in this study referred to those who were triaged as Level-1 and Level-2 based on Emergency Severity Index or ESI (Version 4) (13). Level-1 patients required immediate lifesaving interventions. Level-2 patients were in a high-risk situation, confused or in severe pain or distress. We decided to include patients trans- ported from community hospitals (i.e., inter-hospital trans- portation) because these patients experienced emergency episodes in their community, sought help in the ED of a nearby community hospital and were transported for defini- tive emergency care available at provincial hospitals. These patients were, therefore, considered emergency patients us- ing pre-hospital and in-hospital emergency services. Table 1: Baseline characteristics of study participants Variable Value (n=1,630) Age (year) Mean ± SD 59.9 ±17.3 Sex Male 933 (57.2) Female 697 (48.2) Chief complaint Respiratory 508 (31.2) Neurological 415 (25.5) Cardiovascular 310 (19.0) Cardiopulmonary arrest 142 (8.7) Trauma 116 (8.5) Other** 139 (7.1) Underlying disease Hypertension 547 (33.6) Coronary artery disease 309 (19.0) Diabetes mellitus 148 (9.1) Chronic obstructive pulmonary disease 121 (7.4) Epilepsy 28 (1.7) None 34 (2.1) Triage Level ESI level-1 546 (33.5) ESI level-2 1084 (66.5) Transportation distance (kilometers) Mean ± SD 28.2 ±31.0 (1-224) Mode of transportation Self-transportation 722 (44.3) Inter-hospital transfer 586 (35.9) EMS – ALS 189 (11.6) EMS-Non-ALS 133 (8.2) Severity of illness REMS on triage 6.9 ± 3.5 (0-24) REMS on Discharge 5.7 ± 3.2 (0-24) Length of stay in ED (minutes) Mean ± SD 119.36± 131.7 (10-1505) Ward Admission General ward 1395(85.5) Intensive care unit 164 (10.1) Semi-Intensive care unit 73 (4.4) Clinical outcome based on pre-arrest sign No sign of cardiac arrest 146 (9) Low risk of cardiac arrest 769 (47.2) Moderate risk of cardiac arrest 322 (19.8) High risk of cardiac arrest 342 (21.0) Severe risk of cardiac arrest 51 (3.1) Data are presented as mean ± standard deviation (SD) or frequency (%). ESI: emergency severity index; REMS: rapid emergency medicine score; EMS-ALS: Emergency medical service ambulance with advanced life support. To be included in the study, patients had to be at least 18 years old and classified as Level- 1 or Level-2 in ED triage This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem 3 Archives of Academic Emergency Medicine. 2022; 10(1): e30 Figure 1: Patient recruitment flowchart. EMS-ALS: Emergency medical service ambulance with advanced life support. Table 2: Univariate regression analysis of factors associated with 24-hour clinical outcome of patients admitted to emergency department (n=1,630) Variable Level of pre-arrest sign at 24 hours p No Low Moderate High Severe Age (year) Mean ± SD 56.88±18.18 59.82±17.43 59.29±17.06 62.11±16.84 60.43±16.38 0.0331 Sex Male 81 (8.7) 449 (48.1) 194 (20.8) 180 (19.3) 29 (3.1) 0.313 Female 65 (9.3) 320 (45.9) 128 (18.4) 162 (23.2) 22 (3.2) Underlying disease Hypertension 49 (9.0) 250 (45.7) 109 (19.9) 122 (22.3) 17 (3.1) Diabetes mellitus 9 (6.1) 75 (50.7) 32 (21.6) 31 (20.9) 1 (0.7) Coronary artery disease 2 (6.5) 17 (54.8) 4 (12.9) 7 (22.6) 1 (3.2) 0.0091 Epilepsy 8 (9.5) 44 (52.4) 13 (15.5) 16 (9.0) 3 (3.6) COPD 3 (12.5) 11 (45.8) 3 (12.5) 5 (20.8) 2 (8.3) None 22 (18.2) 52 (43.0) 21 (17.4) 25 (20.7) 1 (0.8) Severity of illness REMS at triage 5.64 ± 2.73 6.109 ± 3.13 7.37 ± 3.64 8.11 ± 3.55 10.61 ± 4.95 0.0001 REMS at discharge 4.02 ± 2.57 4.94 ± 2.77 6.27 ± 3.17 6.89 ± 3.11 9.96 ± 5.25 0.0001 Type of transportation Inter-hospital 2 (0.3) 230 (39.2) 150 (25.6) 178 (30.3) 27 (4.6) 0.0001 Self-transportation 109 (15.1) 375 (52.0) 113 (15.7) 116 (16.1) 8 (1.1) 0.0001 EMS-non-ALS 15 (11.0) 68 (50.0) 27 (19.9) 18 (13.2) 8 (5.9) 0.0001 EMS-ALS 20 (10.8) 96 (51.6) 32 (17.2) 30 (16.1) 8 (4.3) Transportation distance (Kilometers) Mean ± SD 9.79 ± 7.17 24.75± 28.64 32.39 ± 30.56 38.55 ± 37.07 35.47±4.86 0.0001 ED-LOS (hours) ≤ 2 23 (15.2) 74 (49.0) 15 (9.9) 33 (21.9) 6 (4.0) 0.0001 2-4 45 (12.9) 106 (30.3) 52 (14.9) 119 (34.0) 28 (8.0) 0.001 ≥ 4 31 (2.7) 374 (33.1) 197 (17.4) 417 (36.9) 110 (9.7) Data are presented as mean ± standard deviation (SD) or frequency (%). ESI: emergency severity index; REMS: rapid emergency medicine score. ED-LOS: emergency department length of stay; COPD: Chronic obstructive pulmonary disease; EMS-ALS: Emergency medical service ambulance with advanced life support. based on Emergency Severity Index (Version 4) (13). Patients who were directly admitted to inpatient wards (not through This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem K. Katsomboon et al. 4 Table 3: Ordinal logistic regression analysis of 24-hour clinical outcome-associated factors in patients admitted to emergency department (n=1,630) Factor Estimate Wald OR 95% CI p Lower Upper Age -0.035 0.004 0.965 0.958 0.973 <.001* Underlying disease Coronary artery disease 0.342 5.347 1.408 1.054 1.882 .021* None ref Severity of illness REMS at triage .093 15.072 1.097 1.047 1.150 <.001* REMS at Discharge .248 77.081 1.281 1.212 1.354 <.001* Transportation distance 0.007 8.224 1.007 1.002 1.011 0.004* Mode of transportation Inter-hospital transfer 0.577 7.148 1.781 1.167 2.718 0.008* Self-transportation -0.251 2.356 0.778 0.565 1.072 0.125 EMS-Non-ALS 0.085 0.147 1.089 0.705 1.681 0.701 EMS-ALS ref Length of stay in emergency department ≥ 4 hours -1.573 75.669 0.207 0.146 0.296 <.001* 2-4 hours -.521 18.515 0.594 0.468 0.753 <.001* ≤ 2 hours ref CI: confidence interval; OR: odds ratio; REMS: rapid emergency medicine score; EMS-ALS: Emergency medical service ambulance with advanced life support. ED), discharged home directly from ED, or transferred to an- other hospital were excluded. Patients who had been treated as inpatients in community hospitals and referred to EDs at provincial hospitals were also excluded. 2.3. Data gathering After the patients were stabilized in the ED, research assis- tants approached them and explained the research objec- tives and procedures to them. Patients received routine stan- dard care at ED and inpatient wards. Clinical data were docu- mented by nurses or attending physicians in paper and elec- tronic formats. Research assistants then collected these data after 24 hours of hospitalization. The research assistants un- derwent a 2-hour intensive training on data collection for this project. Patients’ sex and age, underlying disease, severity of illness, transportation distance, mode of transportation, and length of stay in ED were evaluated. Severity of illness was assessed using Rapid Emergency Medicine Score (REMS) (14). REMS is comprised of six phys- iological parameters of age, respiratory rate, oxygen satura- tion, body temperature, systolic blood pressure, pulse rate, and level of consciousness. The REMS score can be used in both trauma and non-trauma patients. Higher REMS is as- sociated with an OR of 1.51 for in-hospital mortality (95% CI 1.45-1.58) (14). Mode of transportation referred to how the patient was trans- ported for definitive treatment in the ED of the provincial hospital. In this study, modes of transportation included self- transportation (i.e., a patient was transported by self, family, or bystander), EMS ambulance with advanced life support (EMS-ALS), EMS ambulance with non-advanced life support (EMS-Non-ALS), and inter-hospital transportation. In the former three modes, a patient was directly transported to the ED of a provincial hospital. In the latter mode, a patient first presented to and was treated at a nearby community hospi- tal and thereafter transported to the ED of a provincial hos- pital. Transportation distance, in kilometer, was determined by the distance between the location where the emergency took place and the provincial hospital. ED-LOS, in minutes, was defined as the interval between the patient’s triage to ED discharge. 2.4. Outcome measurement The clinical outcome was measured using pre-arrest sign score, which was assessed and documented 24 hours after hospitalization by a nurse in intensive care unit (ICU) or gen- eral ward where the patient was treated following ED. The pre-arrest sign, a term widely used in Thailand, is in fact a tool originally known as an Activation Criteria for a Medical Emergency Team (15). The Activation Criteria for a Medical Emergency Team takes into account presenting symptoms, physiological conditions, and laboratory results, which indi- cate the risk of cardiopulmonary arrest, and hence pre-arrest signs as referred to by Thai clinicians. The score ranges from 0-11. High scores indicate high risk for cardiopulmonary ar- This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem 5 Archives of Academic Emergency Medicine. 2022; 10(1): e30 rest. In this study, the scores were classified into 5 levels: 8-11 points: Severe critical condition/very high risk of car- diac arrest 5-7 points: Critical condition and high risk of cardiac arrest 4 points: Moderate risk of cardiac arrest 2-3 points: Low risk of cardiac arrest 0-1 point: No sign of cardiac arrest 2.5. Statistical analysis The formula for survival studies (16) was used for sample size calculation. In the previous study, 17.7% of patients who were treated in ED were placed in intensive care units (17) and were, therefore, considered critically ill. For multi- stratified random sampling, the sample size of 1,630 was needed. To ensure that samples are adequate, 30 more pa- tients were added to the calculated sample size, resulting in the sample size of 1,660. The statistical package for the so- cial sciences for the MS Windows program (SPSS/FW ) (Ver- sion 21.0) was used for data analysis. Descriptive statistics, univariate regression analysis, and ordinal multivariate logis- tic regression analysis with a backward technique were per- formed. A p value cut-off of <0.05 and confidence interval of 95% were used. 3. Results 3.1. Baseline characteristics of patients A total of 1,630 patients were finally enrolled in the study (Figure 1). The majority were male (57.2%). The mean age was 59.95 + 17.3 (18-98) years. The majority suffered from critical illnesses involving respiratory system (31.2%) and were triaged as ESI Level 2 (66.5%). The most common modes of transportation were self-transportation (44.3%) and inter-hospital transportation (35.9%). Only 11.6% and 8.2% used EMS-ALS and EMS-Non-ALS, respectively. Mean REMS at triage was 6.9 ±3.5 (range 0 -24) points, while mean REMS at discharge from ED was 5.7 ± 3.24 (range 0 -24) points (Table 1). 3.2. Clinical outcome at 24 hours based on pre- arrest sign Based on pre-arrest sign scores, almost half (47.2 %) of the patients had a low level of critical condition after 24 hours of hospitalization. 21.0% and 19.8% had a high and moderate level of critical conditions, respectively. 3.1% were classified as severe (Table1). 3.3. Associated factors of 24-hour clinical out- come Univariate analysis revealed that age, having underlying dis- ease, severity of illness, mode of transportation, transporta- tion distance, and length of stay in ED were associated with pre-arrest sign 24 hours after hospitalization (Table 2). Sub- sequent ordinal logistic regression revealed that increasing age decreased a risk of developing pre-arrest sign or clinical deterioration 24 hours after hospitalization (OR: 0.965; 95% CI: 0.958-0.973). Patients who had coronary artery disease (CAD) were 1.41 times more likely to experience poor out- come (OR: 1.408; 95% CI: 1.054- 1.882). Every 1-point in- crease in REMS score at triage increased the risk of clinical deterioration by 1.09 times (OR: 1.097; 95% CI: 1.047-1.150). A 1-point increase in REMS scores at ED discharge, increased the risk of clinical deterioration by 1.28 times (OR: 1.281; 95% CI: 1.212 – 1.354). An increase of 1 kilometer of trans- portation distance increased the risk of poor outcome by 1.01 times (OR: 1.007; 95% CI: 1.002-1.011). Self-transportation and EMS-Non-ALS transportation produced similar clinical outcomes when compared to EMS-ALS transportation. Pa- tients transported by inter-hospital transfer were 1.78 times more likely to experience deteriorations compared to EMS- ALS (OR: 1.781; 95% CI: 1.167- 2.718). Patients who stayed in ED between 2-4 hours or over 4 hours were less likely to expe- rience clinical deteriorations compared to those who stayed less than 2 hours [(OR: 0.594; 95% CI: 0.468 - 0.753) and (OR: 0.207; 95% CI: 0.146-0.296), respectively]. 4. Discussion Having CAD, severity of illness, increased transport distance, and ED-LOS of less than 2 hours were found to negatively in- fluence 24-hour clinical outcome of emergency patients. In- creasing age was found to positively influence the outcome. Modes of transportation (i.e., self-transportation, EMS-ALS, and EMS-Non-ALS) did not influence the outcome. We had hypothesized that increasing age of the patient was a risk factor for poor outcome. To our surprise, our result was the opposite. In this study, the older the patients were, the less likely they were at risk of developing pre-arrest sign. The only possible explanation concerns past experience of older persons in relation to how they recognize and respond to warning signs of their underlying illnesses. Emergency medical events experienced by older persons in the past may help them and their family to recognize early changes in their signs and symptoms. In the present study, having CAD was a risk factor for poor outcome. CAD has been well-documented as a risk factor of cardiac arrest (18, 19). Patients with existing CAD are more likely to develop cardiopulmonary arrest than those with other pre-existing conditions (19). This finding has several implications for pre-hospital and in-hospital service management. Pre-hospital assessment of emergency patient should include a question about pre-existing CAD. Optimal pre-hospital service arrangements for CAD patients, includ- ing equipment and staff with competencies in CAD manage- This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem K. Katsomboon et al. 6 ment, should be considered. Severity of illness on ED triage and ED discharge, as deter- mined using REMS, was another predictor of poor clinical outcome. A recent study by Ala et al. (2020) (20) suggested that REMS correlated with mortality at 48 hours and 30 days. In line with emergency service, our finding suggested that REMS may have potential use in pre-hospital, ED, and han- dover of clinical information for continuous care following ED discharge to ICU or wards. Mode of transportation (self-transportation, EMS-Non-ALS, and EMS-ALS) did not make a difference in pre-arrest sign at 24 hours. In Thailand, families and bystanders are famil- iar with the latter two choices of emergency transportation. When encountering an emergency event, they are required to call the emergency dispatch center or 1669. However, a decision to call or not to call 1669 is influenced by a num- ber of factors such as perceived transport delay and sever- ity of the patients. The patients using self-transportation arrived at the hospital in a shorter time and had a lower level of severity compared to those using EMS transportation and pre-arrest sign was, therefore, not different between self- transportation, EMS-Non-ALS, and EMS-ALS in our study. Our findings are similar to those of a previous study by Sea- mon, et al. (21). In this study, inter-hospital transportation mode was likely to experience poorer clinical outcome com- pared to those transported by EMS-ALS. We understand that the increased risk of poor outcome may be related to trans- portation distance and time. Previous studies reported an increased risk of clinical deteriorations during inter-hospital transfer of critically ill and emergency patients (22). Transportation distance has shown to increase pre-arrest sign. In long-distance transportation, patients are more likely to experience delay in access to definitive care. These contribute to the increased risk of poor outcome among emergency patients requesting service from a long distance. The previous national quality standard indicator in Thailand required that ED-LOS is maintained less than 2 hours (23). Previous studies on the effects of ED-LOS on inpatient mor- tality reported conflicting results. Indian and American stud- ies (9, 24) concluded that ED-LOS had no effect on inpatient mortality rates, whereas an Indian study (9) revealed the ef- fect of longer ED-LOS on higher rate of inpatient death. Our findings, however, suggested that shorter stay (less than 2 hours) was associated with higher risk for developing pre- arrest signs. This can be explained by the fact that the ma- jority (85.5%) of the patients were admitted to general wards compared to only 14.5% admitted to ICU and semi-intensive care unit. Continuous management of emergency and crit- ically ill patients at general wards can be very challenging. These general units are often overworked and understaffed. Our study points out that more time at ED may be beneficial for the patients as it allows clinical conditions to be improved and sustained in the ED and makes it less complex to be man- aged in general wards. The Ministry of Public Health has very recently increased the ED target length of stay to 2-4 hours (25). The results of this study highlight two important processes in emergency medical services in Thailand: safe and early ar- rival of emergency patients at ED for definitive care and ad- equate management and stabilization of emergency patients in ED before inpatient admission. 5. Conclusion Having CAD, severity of illness, increased transport distance, and shorter ED-LOS of less than 2 hours were found to neg- atively influence 24-hour clinical outcome of emergency pa- tients. Increasing age was found to positively influence the outcome. Modes of transportation (i.e., self-transportation, EMS-ALS, and EMS-Non-ALS) did not influence the out- come. 6. Declarations 6.1. Acknowledgments We thank all the participants in this study as well as staff and health professionals for their facilitation during data collec- tion. 6.2. Authors’ contributions K.K. and S.S.; Contributed to conception, study design. K.K.; Contributed to data gathering and evaluation. 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This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem Introduction Methods Results Discussion Conclusion Declarations References