Lee, Khang, and Lim: Impact of the 2015 Middle East Respiratory Syndrome Outbreak on Emergency Care Utilization and Mortality in South Korea

### Purpose

In May 2015, South Korea experienced an epidemic of Middle East respiratory syndrome (MERS). This study investigated the impacts of MERS epidemic on emergency care utilization and mortality in South Korea.

### Materials and Methods

A natural experimental study was conducted using healthcare utilization and mortality data of the entire Korean population. The number of monthly emergency room (ER) visits was investigated to identify changes in emergency care utilization during the MERS epidemic; these trends were also examined according to patients' demographic factors, disease severity, and region. Deaths within 7 days after visiting an ER were analyzed to evaluate the impact of the reduction in ER visits on mortality.

### Results

The number of ER visits during the peak of the MERS epidemic (June 2015) decreased by 33.1% compared to the average figures from June 2014 and June 2016. The decrease was observed in all age, sex, and income groups, and was more pronounced for low-acuity diseases (acute otitis media: 53.0%; upper respiratory infections: 45.2%) than for high-acuity diseases (myocardial infarctions: 14.0%; ischemic stroke: 16.6%). No substantial changes were detected for the highest-acuity diseases, with increases of 3.5% for cardiac arrest and 2.4% for hemorrhagic stroke. The number of deaths within 7 days of an ER visit did not change significantly.

### Conclusion

During the MERS epidemic, the number of ER visits decreased in all age, sex, and socioeconomic groups, and decreased most sharply for low-acuity diseases. Nonetheless, there was no significant change in deaths after emergency care.

### INTRODUCTION

The patterns of healthcare utilization change in infectious disease outbreaks. Identifying the patterns of change is important for future preparedness and response. The effects on healthcare utilization of infectious disease epidemic depend on the characteristics of an infection. In the 2003 severe acute respiratory syndrome (SARS) epidemic in Taiwan, medical service utilization decreased due to fear of nosocomial transmission.12 However, in the 2009 pandemic of H1N1 influenza, which is highly infectious but has a low case-fatality rate, emergency care utilization increased.34
In 2015, South Korea (hereafter “Korea”) experienced an epidemic of Middle East respiratory syndrome (MERS). In a vulnerable healthcare delivery system in which the gatekeeper function of primary clinics was weak, the first patient wandered through several different hospitals before being diagnosed, thereby spreading the infection.5 The 14th patient, a super-spreader, stayed in an overcrowded emergency room (ER) in a tertiary-care hospital for 3 days and spread the infection to 78 patients.6 An healthcare-associated MERS epidemic then started and the fear of MERS spread nationwide.678 A 14-day self-isolation quarantine program was applied to contacts of infected patients, while there was no restriction on the public's access to medical care.89 However, Korean citizens were afraid to visit healthcare facilities due to fears regarding the potential nosocomial transmission of this unfamiliar contagious disease. Such fears affected the entire society, and all healthcare utilization reportedly decreased.
In order to effectively respond to emerging infectious disease outbreaks, it is important to predict changes in healthcare utilization and understand the different patterns of changes in diverse population groups. Previous studies have analyzed the impacts of SARS and influenza epidemics.2341011 However, although few small studies have investigated changes in healthcare utilization during the MERS epidemic in Korea,1213 no study has systematically evaluated the impact of the MERS epidemic on nationwide healthcare utilization. Furthermore, the impact of the reduction in emergency care utilization on health outcomes has not been explored.
The hypothesis of this study was that the use of emergency care during the MERS epidemic decreased regardless of age, sex, and socioeconomic position (SEP), but with a less prominent impact for severe diseases, meaning that the final health outcomes of emergency care showed minimal changes. We aimed to investigate the changes in emergency care utilization during the 2015 MERS epidemic according to patient characteristics, disease severity, and region, and evaluate its impact on mortality.

### Study setting and databases

The population of Korea is approximately 50 million people, spread over an area of 99000 km2. The administrative units of Korea include eight metropolitan cities and nine provinces that are divided into cities and counties. Korea implemented National Health Insurance (NHI) in 1989, covering the entire population. The Korean government runs NHI as a single insurer, compulsorily covering inpatient, outpatient, and emergency services.1415 While NHI service ensures high accessibility to medical care, the gatekeeper function of primary clinics is weak, meaning that people can visit tertiary-care hospitals freely, with low out-of-pocket costs. Korea has a total of 420 registered ERs, which are open to all beneficiaries without restriction, and overcrowding of ER is a serious problem in tertiarycare hospitals.1617
The National Health Information Database (NHID) from NHI Service was analyzed.1518 The eligibility database (DB), healthcare utilization DB, and death information DB contained within NHID were used for this study. The eligibility DB (patients' demographic information) included age, sex, and insurance premium as an indicator of SEP.19 The healthcare utilization DB contained insurance service fee codes and diagnostic codes. The total number of diagnostic codes was five, including one principal code, one secondary code, and three additional diagnostic codes, based on the International Classification of Diseases, 10th edition. All healthcare use covered by NHI was included in the NHID, but cases involving traffic accidents covered by auto insurance (accounting for approximately 2.6% of total healthcare use) and cases involving foreigners not covered by the Korean NHI were excluded.141820 We individually linked the eligibility DB and healthcare utilization DB with the death information DB, including date of death, to investigate the mortality after ER visits.

### MERS outbreak in Korea and study population

On May 20, 2015, the first MERS case in Korea was identified in a traveler from the Middle East. From May 20, when the first patient was diagnosed, to July 5, when the last patient was diagnosed, a total of 186 patients were confirmed, with a 20% mortality rate.2122 Although some hospitals were closed temporarily for quarantine purposes, there was no restriction on the use of medical services. However, activities in all sectors of society, including health service utilization, decreased. Social cost of the MERS epidemic was estimated to be 8.3 billion USD.23
All patient visits to ER between January 2014 and December 2016 were examined. Cases for which data regarding the age and sex of the insured and insurance premium were not confirmed were minimal (0.097% of total visits), and such cases were excluded from the analysis. The official end date of the MERS epidemic, according to the criteria of World Health Organization, was December 23, which came 80 days after the last death. However, the period of the 2015 MERS epidemic was defined as June to July 2015, corresponding to the period when new patients were diagnosed and the fear of MERS was prevalent. The peak was June 2015, when most number of new patients were diagnosed.

### Measurement of variables

Patients were divided into three age groups: children (0–19 years), adults (20–59 years), and the elderly (over 60). SEP was classified into quintile groups using an insurance premium.19
Based on the first two diagnostic codes (principal and secondary codes), we selected several major diseases in ER and classified them to high-acuity and low-acuity diseases, based on whether their treatment could be initiated at the primary care settings rather than ER.24 High-acuity diseases included cardiac arrest (I46), myocardial infarction (MI; I21–22), hemorrhagic stroke (I60–62), and ischemic stroke (I63–64).25 Low-acuity diseases included acute gastroenteritis (AGE; A08–09), acute pharyngotonsillitis (APT; J00), acute otitis media (AOM; H65–67), and upper respiratory infection (URI; J00–06).124
The regions where the MERS outbreak mainly occurred (i.e., Seoul metropolitan city and Gyeonggi Province) were defined as risk areas and were compared with other regions. In Gyeonggi Province, Suwon, where the infection control hospital is located, and Pyeongtaek, where the first patient was diagnosed, were defined as high-risk areas, while Anyang and Seongnam, which are similar to Suwon and Pyongtaek in terms of population size and number of ER visits, were defined as comparison areas.
The first outcome was the monthly number of ER visits. To assess the degree of reduction in ER visits, the ratio of ER visits in 2015 to the averaged visits from the same month in 2014 and 2016 was calculated as follows and presented as a percentage (%):
$Ratio of ER visits in 2015 (%)=Number of ER visits in 2015Average number of ER visits in 2014 and 2016×100.$
The second outcome was the monthly number of deaths within 7 days of an ER visit, which was calculated as follows and presented as a percentage (%): ratio of deaths in 2015 to averaged deaths of the corresponding months in 2014 and 2016.

### Statistical analyses

The MERS epidemic can be considered as a natural experiment. The periods of the MERS epidemic were considered as the intervention group, and other months were considered as the comparison group. In addition to the investigation of monthly trends from 2014 to 2016, the monthly numbers of ER visits in 2015 were compared with the average visits of the corresponding months in 2014 and 2016 (ratio of ER visits in 2015, %). The monthly number of deaths within 7 days of an ER visit was analyzed in the same manner. This analytical choice was based on the assumption that the monthly statistical figures in 2015 would have been similar to the averages from 2014 and 2016 in the absence of important events or policies affecting monthly visits and associated mortality.
In addition, age-standardized prevalence and their 95% confidence intervals (CIs) per 100000 population were calculated for the ER visits and deaths within 7 days of an ER visit in 2015. The number of health insurance subscribers was used as the denominator,26 and mid-year population in 2016 was used as the standard population.27 Prevalence ratios and their 95% CIs were also calculated using the averaged value from the same month in 2014 and 2016 as reference.
Changes in emergency care utilization patterns were compared by age, sex, and SEP [quintile of insurance premium: Q1 (lowest) to Q5 (highest)]. The reductions in ER visits for high-acuity and low-acuity diseases were presented as percentages (%) comparing risk areas with comparison areas. The ratios of monthly ER visits in 2015 to the averaged visits from the same month in 2014 and 2016 were compared according to disease severity, and we performed chi-square test to assess whether the differences of monthly ER visits between 2015 and 2014/2016 were statistically significant. All other results were graphically displayed to identify monthly trends throughout the year, and we considered the values during the MERS epidemic to be meaningful if they were outside the range of values for the other months.
Data management and statistical analyses were conducted using SAS software version 9.4 (SAS Institute Inc., Cary, NC, USA).

### Ethics statement

The protocol of this study was reviewed and approved by the Institutional Review Board of Seoul National University Hospital (No. C-1804-041-934). Data use of this study was also approved by the National Health Insurance Service of Korea (Study No. NHIS-2018-1-153). No personal identifiers were provided in the data; instead, only anonymized aggregate data were used for the final analysis.

### Overall emergency room visits according to the MERS epidemic

ER visits rose from 2014 to 2016, as shown graphically in Fig. 1. At the peak of the MERS epidemic in June 2015, the number of ER visits sharply declined by 28.0%, reaching 72.0% of the average visits in 2014 and 2016 (Fig. 1, Supplementary Table 1, only online). Except for June and July, the ratio of ER visits in 2015 ranged from 87.3% to 100.8%. The MERS epidemic resulted in a marked reduction in ER visits regardless of age, sex, and SEP, especially in pediatric patients (39.6%, 21.9%, and 24.9% decreased in children, adults, and the elderly, respectively) (Supplementary Table 2, Supplementary Fig. 1, only online).
The age-standardized prevalence ratios for ER visits per 100000 population in June 2015 was 0.72, which was lower compared to the rest of the year (0.85 to 1.01) (Table 1).

### Emergency care utilization according to disease severity

At the peak of the MERS epidemic, the ratio of ER visits due to low-acuity diseases decreased more sharply than that of ER visits due to high-acuity diseases (33.8%, 39.9%, 53.0%, and 45.2% decreased in AGE, APT, AOM, and URI, respectively versus a 14.0% decreased for MI and a 16.6% decreased for ischemic stroke). ER visits due to the highest-acuity diseases, cardiac arrest and hemorrhagic stroke, did not decrease during the MERS outbreak (with ratios of 103.5% for cardiac arrest and 102.4% for hemorrhagic stroke) and showed similar trends throughout the year (Table 2, Supplementary Table 3, Supplementary Figs. 2 and 3, only online).

### Emergency care utilization by region

At the peak of the MERS epidemic, the reduction in emergency care use was more prominent in the risk areas than in other metropolitan cities and provinces (66.9% in Seoul and 66.7% in Gyeonggi Province versus 76.7% in other metropolitan cities and 75.0% in other provinces). In Gyeonggi Province, the reduction was more prominent in high-risk areas than in comparison areas (58.1% in Suwon and 56.8% in Pyeongtaek versus 71.0% in Anyang and 71% in Seongnam) (Fig. 2, Supplementary Table 4, only online).

### Effect of reduction in emergency care utilization on short-term mortality

No substantial changes were detected in the number of deaths within 7 days after an ER visit throughout the year (December: 94.5% to March: 110.1%), including the MERS epidemic period (June: 99.2% and July: 99.5%) (Fig. 3, Supplementary Table 5, only online). The death trends within 7 days of an ER visit in 2015 were similar throughout the year, regardless of sex and SEP. Due to the unstable numbers of monthly childhood deaths (ranging from 42 to 85 in 2014–2016), a large variation in children was noted, from 54.4% in February to 133.3% in August, while the corresponding values during the months of the MERS epidemic were 114.6% (June) and 78.0% (July) (Supplementary Table 2, Supplementary Fig. 4, only online).

### DISCUSSION

This study evaluated changes in the utilization of emergency care throughout the 2015 MERS epidemic in Korea by using NHID, which covered the entire Korean population. Emergency care utilization decreased regardless of age, sex, and SEP at the peak of the MERS epidemic, especially in pediatric patients. The reduction was more prominent in low-acuity diseases than in high-acuity diseases, and in the MERS epidemic areas than in other areas. Although ER visits decreased markedly during the epidemic period, the number of deaths within 7 days of an ER visit did not change.
Patterns of medical service use in infectious disease outbreak may vary according to the characteristics of an infection, such as infectivity and lethality of the disease. Both SARS and H1N1 influenza were epidemics that caused global panic, but the pattern of healthcare utilization changed in the opposite direction. Healthcare utilization decreased in the 2003 SARS epidemic due to fear of nosocomial infection, whereas it explosively increased in the 2009 H1N1 influenza pandemic due to fear of influenza itself.23410 In the case of MERS, since the main transmission route was nosocomial transmission and the mortality rate was high, healthcare utilization decreased during the epidemic.1213 This effect was dramatic in the ER rather than other departments in hospitals, as most of the nosocomial infections occurred in a crowded ER.6 When we analyzed the monthly number of ER visits by type of ER using the National Emergency Department Information System (NEDIS) data, the number of ER visits decreased in all three types of ER (regional emergency medical center, local emergency medical center, and local emergency medical institution) in MERS epidemic, regardless of the type of ER.16 Since only 186 patients were diagnosed with MERS during the epidemic in Korea, the explanation for the impact of MERS on ER use was fear, not the MERS disease itself. The effects of fear impacted everyone in the society regardless of age, sex, and SEP groups.7 The greater reduction in the epidemic areas than in other comparison areas also corroborates the explanation that the fear of MERS infection caused the reduced utilization of healthcare.
As in previous studies examining changes in healthcare utilization according to disease severity, the results of this study showed that the reduction in emergency care utilization was most prominent for low-acuity diseases.11213 The reduction in visits for high-acuity diseases was relatively small, and the most severe diseases did not show a decrease even in June 2015, when the epidemic was at its peak. Patients decide to use medical care based on their consideration of risks and benefits. During an infectious disease epidemic, patients use medical care when they feel that the benefits of healthcare utilization are greater than the risk of infection.1 When there were concerns about nosocomial infections, those with low-acuity diseases, which are considered to have little benefits from emergency service use, were less likely to visit the ER. In Korea, due to the absence of limitations on healthcare utilization and the weak gatekeeping role of healthcare delivery system, unnecessary hospital utilization of low-acuity patients is prevalent.2829 As a result, overcrowding in a tertiary-care hospital ER caused the MERS epidemic, and low-acuity patients decreased most when the risk of infection overwhelmed the benefit of emergency service use. A study of the SARS epidemic showed that restriction of non-urgent hospital utilization during the epidemic did not increase mortality and complication rates.30 The authors of that study concluded that restriction of non-urgent visits is a safe public health strategy to control nosocomial infections and to maintain hospital surge capacity. Examining the scale of ER visits for low-acuity diseases with little benefit from service use is important, not only for preparing appropriate emergency surge capacity but also for providing evidence to redesign emergency service to decrease healthcarerelated infectious disease outbreak.
Another noteworthy finding of this study was that, although the total number of ER visits decreased, the number of deaths within 7 days of an ER visit did not meaningfully change during the epidemic. This implies that the number of patients with serious conditions visiting the ER did not change, even though overall emergency care utilization decreased. As shown for cardiac arrest and hemorrhagic stroke in this study, the reduction in ER use for high-acuity diseases is expected to be minimal in infectious disease outbreak. When fear of an epidemic spreads and ER visits decrease, preparations for serious conditions need to be focused, and patients with severe diseases should not face barriers to emergency care use.
This study had some limitations. First, our analysis was based on the assumption that no meaningful changes in factors affecting ER visits, except for the MERS epidemic, occurred during the study period, which might not have been completely true. For example, the ratio of ER visits in December 2015 was relatively low compared to the ratio in other comparison months (87.3%; Supplementary Table 1, only online). This may have been due to the influenza epidemic in December 2016, which occurred a month earlier than usual (influenza epidemic alarm was announced by the Korea Centers for Disease Control and Prevention on January 2, 2014; January 22, 2015; January 14, 2016; and December 8, 2016). However, our analysis on the utilization by region (MERS risk area versus comparison area) corroborated our explanation. Second, the scope of this study only included patients who visited the ER. The health outcomes of those who did not use emergency services were not investigated. Although ER visits for the most severe conditions did not decrease, the reduction in emergency care utilization for MI and ischemic stroke, where acute care is important, might have led to complications other than short-term mortality.3132 Supplementary Fig. 5 (only online) employing mortality data among the entire Korean population from Statistics Korea shows no apparent changes in overall mortality according to the MERS epidemic. However, further study is needed to investigate the long-term outcomes of reduced emergency care utilization. Third, ER visits due to traffic accidents, which account for a considerable proportion of injured patients, were not included in this study, as these cases were covered by auto insurance in Korea and not by the NHI. However, based on the estimates from NEDIS database in Korea, 5.1% of ER visits were covered by auto insurance.33 Changes in the ER visits covered by auto insurance would not critically change the findings.
This study also had several strengths. First, to the best of our knowledge, this is the first study to investigate the impact of MERS outbreak at the national level. In the era of emerging infectious diseases, understanding the impact of epidemic is an important first step to being prepared. Second, this study was a natural experiment, in which major confounding factors, such as social and economic factors, might well be independent of the MERS epidemic in the causal association with ER visits and mortality. Third, we employed total NHI data covering the entire Korean population, which enabled us to present stable overall- and subgroup-specific numbers of ER visits and mortality.
In conclusion, during the 2015 MERS epidemic in Korea, the utilization of emergency care decreased regardless of age, sex, and SEP. A greater reduction was observed in epidemic areas than in other comparison areas, and the reduction was greater for low-acuity diseases than for high-acuity diseases. Although the number of ER visits decreased, the number of deaths within 7 days of an ER visit did not change.

### ACKNOWLEDGEMENTS

Hee-Yeon Kang and Yeon-Yong Kim provided helpful comments on the earlier analysis of this paper.

### Notes

The authors have no potential conflicts of interest to disclose.

AUTHOR CONTRIBUTIONS:

• Conceptualization: Sun Young Lee and Young-Ho Khang.

• Data curation: Sun Young Lee and Young-Ho Khang.

• Methodology: Sun Young Lee, Young-Ho Khang, and Hwa-Kyung Lim.

• Formal analysis: Sun Young Lee and Hwa-Kyung Lim.

• Software: Sun Young Lee.

• Validation: Sun Young Lee and Young-Ho Khang.

• Investigation: Sun Young Lee, Young-Ho Khang, and Hwa-Kyung Lim.

• Writing—original draft: Sun Young Lee.

• Writing—review & editing: Sun Young Lee, Young-Ho Khang, and Hwa-Kyung Lim.

• Approval of final manuscript: All authors.

### References

1. Lu TH, Chou YJ, Liou CS. Impact of SARS on healthcare utilization by disease categories: implications for delivery of healthcare services. Health Policy. 2007; 83:375–381. PMID: 17445942.
2. Chang HJ, Huang N, Lee CH, Hsu YJ, Hsieh CJ, Chou YJ. The impact of the SARS epidemic on the utilization of medical services: SARS and the fear of SARS. Am J Public Health. 2004; 94:562–564. PMID: 15054005.
3. Fagbuyi DB, Brown KM, Mathison DJ, Kingsnorth J, Morrison S, Saidinejad M, et al. A rapid medical screening process improves emergency department patient flow during surge associated with novel H1N1 influenza virus. Ann Emerg Med. 2011; 57:52–59. PMID: 20947207.
4. Costello BE, Simon HK, Massey R, Hirsh DA. Pandemic H1N1 influenza in the pediatric emergency department: a comparison with previous seasonal influenza outbreaks. Ann Emerg Med. 2010; 56:643–648. PMID: 20363533.
5. Cowling BJ, Park M, Fang VJ, Wu P, Leung GM, Wu JT. Preliminary epidemiological assessment of MERS-CoV outbreak in South Korea, May to June 2015. Euro Surveill. 2015; 20:7–13. PMID: 26132767.
6. Cho SY, Kang JM, Ha YE, Park GE, Lee JY, Ko JH, et al. MERS-CoV outbreak following a single patient exposure in an emergency room in South Korea: an epidemiological outbreak study. Lancet. 2016; 388:994–1001. PMID: 27402381.
7. Ro JS, Lee JS, Kang SC, Jung HM. Worry experienced during the 2015 Middle East Respiratory Syndrome (MERS) pandemic in Korea. PLoS One. 2017; 12:e0173234. PMID: 28273131.
8. Park GE, Ko JH, Peck KR, Lee JY, Lee JY, Cho SY, et al. Control of an outbreak of Middle East respiratory syndrome in a tertiary hospital in Korea. Ann Intern Med. 2016; 165:87–93. PMID: 27272273.
9. Kim EY, Liao Q, Yu ES, Kim JH, Yoon SW, Lam WW, et al. Middle East respiratory syndrome in South Korea during 2015: risk-related perceptions and quarantine attitudes. Am J Infect Control. 2016; 44:1414–1416. PMID: 27130900.
10. Chen TA, Lai KH, Chang HT. Impact of a severe acute respiratory syndrome outbreak in the emergency department: an experience in Taiwan. Emerg Med J. 2004; 21:660–662. PMID: 15496687.
11. Heiber M, Lou WY. Effect of the SARS outbreak on visits to a community hospital emergency department. CJEM. 2006; 8:323–328. PMID: 17338843.
12. Paek SH, Kim DK, Lee JH, Kwak YH. The impact of Middle East respiratory syndrome outbreak on trends in emergency department utilization patterns. J Korean Med Sci. 2017; 32:1576–1580. PMID: 28875599.
13. Jeong H, Jeong S, Oh J, Woo SH, So BH, Wee JH, et al. Impact of Middle East respiratory syndrome outbreak on the use of emergency medical resources in febrile patients. Clin Exp Emerg Med. 2017; 4:94–101. PMID: 28717779.
14. Song SO, Jung CH, Song YD, Park CY, Kwon HS, Cha BS, et al. Background and data configuration process of a nationwide population-based study using the Korean National Health Insurance system. Diabetes Metab J. 2014; 38:395–403. PMID: 25349827.
15. Park CS, Choi EK, Han KD, Lee HJ, Rhee TM, Lee SR, et al. Association between adult height, myocardial infarction, heart failure, stroke and death: a Korean nationwide population-based study. Int J Epidemiol. 2018; 47:289–298. PMID: 29025084.
16. National Emergency Medical Center. Statistical yearbook of emergency medical service [Internet]. Seoul: National Emergency Medical Center;c2015. accessed on 2019 March 19. Available at: https://www.e-gen.or.kr/nemc/statistics_annual_report.do.
17. Lee YJ, Shin SD, Lee EJ, Cho JS, Cha WC. Emergency department overcrowding and ambulance turnaround time. PLoS One. 2015; 10:e0130758. PMID: 26115183.
18. Seong SC, Kim YY, Khang YH, Park JH, Kang HJ, Lee H, et al. Data resource profile: the National Health Information Database of the National Health Insurance Service in South Korea. Int J Epidemiol. 2017; 46:799–800. PMID: 27794523.
19. Khang YH, Yang S, Cho HJ, Jung-Choi K, Yun SC. Decomposition of socio-economic differences in life expectancy at birth by age and cause of death among 4 million South Korean public servants and their dependents. Int J Epidemiol. 2010; 39:1656–1666. PMID: 20647268.
20. Health Insurance Review and Assessment Service. Statistics of the healthcare fee [Internet]. Wonju: Health Insurance Review and Assessment Service;c2015. accessed on 2019 March 19. Available at: https://www.hira.or.kr/bbsDummy.do?pgmid=HIRAA020045030000&brdScnBltNo=4&brdBltNo=2376&pageIndex=2#none.
21. Kang CK, Song KH, Choe PG, Park WB, Bang JH, Kim ES, et al. Clinical and epidemiologic characteristics of spreaders of Middle East respiratory syndrome coronavirus during the 2015 outbreak in Korea. J Korean Med Sci. 2017; 32:744–749. PMID: 28378546.
22. Kim KH, Tandi TE, Choi JW, Moon JM, Kim MS. Middle East respiratory syndrome coronavirus (MERS-CoV) outbreak in South Korea, 2015: epidemiology, characteristics and public health implications. J Hosp Infect. 2017; 95:207–213. PMID: 28153558.
23. Cho KY, Yoo JS. Estimate of economic loss of MERS epidemic [Internet]. Seoul: Korea Economic Research Institute;c2015. accessed on 2019 March 19. Available at: https://www.keri.org/web/www/research_0201?p_p_id=EXT_BBS&p_p_lifecycle=0&p_p_state=normal&p_p_mode=view&_EXT_BBS_struts_action=%2Fext%2Fbbs%2Fview_message&_EXT_BBS_messageId=350282.
24. Kellermann AL, Weinick RM. Emergency departments, Medicaid costs, and access to primary care--understanding the link. N Engl J Med. 2012; 366:2141–2143. PMID: 22591255.
25. Writing Group Members. Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, et al. Heart disease and stroke statistics-2016 update: a report from the American Heart Association. Circulation. 2016; 133:e38–e360. PMID: 26673558.
26. Korean Statistical Information Service (KOSIS). Health insurance statistics: monthly population [Internet]. Daejeon: KOSIS;c2018. accessed on 2019 March 19. Available at: http://kosis.kr/statHtml/statHtml.do?orgId=350&tblId=TX_35001_A007&vw_cd=MT_ZTITLE&list_id=350_35001_B&seqNo=&lang_mode=ko&language=kor&obj_var_id=&itm_id=&conn_path=MT_ZTITLE.
27. Korean Statistical Information Service (KOSIS). The estimated population [Internet]. Daejeon: KOSIS;c2019. accessed on 2019 March 19. Available at: http://kosis.kr/statHtml/statHtml.do?orgId=101&tblId=DT_1BPA001&vw_cd=MT_ZTITLE&list_id=A41_10&seqNo=&lang_mode=ko&language=kor&obj_var_id=&itm_id=&conn_path=MT_ZTITLE.
28. Jung H, Do YK, Kim Y, Ro J. The impact of an emergency fee increase on the composition of patients visiting emergency departments. J Prev Med Public Health. 2014; 47:309–316. PMID: 25475198.
29. Lee JY, Jo MW, Yoo WS, Kim HJ, Eun SJ. Evidence of a broken healthcare delivery system in Korea: unnecessary hospital outpatient utilization among patients with a single chronic disease without complications. J Korean Med Sci. 2014; 29:1590–1596. PMID: 25469056.
30. Stukel TA, Schull MJ, Guttmann A, Alter DA, Li P, Vermeulen MJ, et al. Health impact of hospital restrictions on seriously ill hospitalized patients: lessons from the Toronto SARS outbreak. Med Care. 2008; 46:991–997. PMID: 18725855.
31. Levine GN, Bates ER, Blankenship JC, Bailey SR, Bittl JA, Cercek B, et al. 2015 ACC/AHA/SCAI focused update on primary percutaneous coronary intervention for patients with ST-elevation myocardial infarction: an update of the 2011 ACCF/AHA/SCAI Guideline for percutaneous coronary intervention and the 2013 ACCF/AHA Guideline for the management of ST-elevation myocardial infarction: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Society for Cardiovascular Angiography and Interventions. Circulation. 2016; 133:1135–1147. PMID: 26490017.
32. Furie KL, Jayaraman MV. 2018 Guidelines for the early management of patients with acute ischemic stroke. Stroke. 2018; 49:509–510. PMID: 29367335.
33. National Emergency Medical Center. Statistical yearbook of National Emergency Department Information System (NEDIS) [Internet]. Seoul: National Emergency Medical Center;c2015. accessed on 2019 March 19. Available at: https://www.e-gen.or.kr/nemc/statistics_annual_report.do?brdclscd=02.

### SUPPLEMENTARY MATERIALS

#### Supplementary Fig. 1

Trends in emergency room visits between 2014 and 2016 according to the age, sex, and socioeconomic position.
ymj-60-796-s001.pdf

#### Supplementary Fig. 2.

Trends in emergency room visits and deaths within 7 days between 2014 and 2016 according to the diseases.
ymj-60-796-s002.pdf

#### Supplementary Fig. 3

The ratio of emergency room visits in 2015 compared with averages of 2014 and 2016 by disease severity.
ymj-60-796-s003.pdf

#### Supplementary Fig. 4

Trends in deaths within 7 days of an emergency room visit between 2014 and 2016 according to the age, sex, and socioeconomic position.
ymj-60-796-s004.pdf

#### Supplementary Fig. 5

Trends in overall mortality between 2014 and 2016 (data from Korea mortality statistics, http://kostat.go.kr/portal/korea/index.action).
ymj-60-796-s005.pdf

#### Supplementary Table 1

Monthly Number of Emergency Room Visits between 2014 and 2016
ymj-60-796-s006.pdf

#### Supplementary Table 2

Trends in Emergency Room Visits and Deaths within 7 Days between 2014 and 2016 according to the Age, Sex, and Socioeconomic Position
ymj-60-796-s007.pdf

#### Supplementary Table 3

Trends in Emergency Room Visits and Deaths within 7 Days between 2014 and 2016 according to the Diseases
ymj-60-796-s008.pdf

#### Supplementary Table 4

Monthly Number of Emergency Room Visits between 2014 and 2016 by Region
ymj-60-796-s009.pdf

#### Supplementary Table 5

Monthly Number of Deaths within 7 Days of an Emergency Room Visit between 2014 and 2016
ymj-60-796-s010.pdf

### The Age-Standardized Prevalence (per 100000) and Prevalence Ratio of Monthly Emergency Room Visits and Deaths within 7 Days of Emergency Room Visits

Month ER visits Deaths within 7 days of ER visits
Prevalence* (95% CI) Prevalence ratio (95% CI) Prevalence* (95% CI) Prevalence ratio (95% CI)
January 885.47 (882.86–888.08) 1.00 (1.00–1.00) 12.69 (12.36–13.01) 1.02 (0.99–1.05)
February 949.72 (947.02–952.42) 0.97 (0.97–0.98) 12.78 (12.45–13.10) 0.97 (0.94–1.00)
March 919.44 (916.77–922.10) 1.01 (1.01–1.01) 13.99 (13.65–14.33) 1.11 (1.08–1.14)
April 882.06 (879.45–884.66) 0.98 (0.98–0.98) 12.25 (11.93–12.56) 1.05 (1.02–1.08)
May 1031.75 (1028.94–1034.57) 1.00 (1.00–1.00) 12.04 (11.73–12.35) 1.00 (0.97–1.03)
June 708.48 (706.15–710.82) 0.72 (0.72–0.72) 10.82 (10.52–11.11) 0.99 (0.96–1.03)
July 853.01 (850.45–855.57) 0.85 (0.84–0.85) 10.89 (10.59–11.19) 1.00 (0.97–1.03)
August 1007.88 (1005.10–1010.66) 0.97 (0.97–0.97) 10.80 (10.50–11.09) 0.96 (0.93–0.99)
September 985.56 (982.81–988.31) 0.95 (0.94–0.95) 11.34 (11.04–11.65) 0.98 (0.95–1.02)
October 876.61 (874.01–879.21) 0.95 (0.95–0.96) 11.70 (11.39–12.01) 0.96 (0.93–0.99)
November 804.15 (801.66–806.64) 0.93 (0.93–0.93) 11.73 (11.42–12.04) 0.97 (0.94–1.00)
December 871.86 (869.27–874.45) 0.87 (0.87–0.88) 12.48 (12.16–12.80) 0.95 (0.92–0.98)

ER, emergency room; CI, confidence intervals.

*Age-standardized prevalence per 100000 in 2015; Average age-standardized prevalence for the corresponding months in 2014 and 2016 were referent in calculating prevalence ratios; Values during the Middle East respiratory syndrome epidemic period (June to July).

### The Ratios of Monthly Emergency Room Visits in 2005 to the Average Visits of Corresponding Months in 2014 and 2016 according to Disease Severity (%)

Month High-acuity disease Low-acuity disease
Myocardial infarction Cardiac arrest Ischemic stroke Hemorrhagic stroke AGE APT AOM URI
% p value* % p value* % p value* % p value* % p value* % p value* % p value* % p value*
May 98.2 0.463 100.2 0.992 96.2 0.019 101.1 0.732 99.7 0.411 92.0 <0.001 90.8 <0.001 95.7 <0.001
June 86.0 <0.001 103.5 0.401 83.4 <0.001 102.4 0.443 66.2 <0.001 60.1 <0.001 47.0 <0.001 54.8 <0.001
July 94.6 0.050 99.2 0.802 95.7 0.011 101.0 0.786 83.3 <0.001 60.5 <0.001 67.2 <0.001 60.4 <0.001
August 96.9 0.267 95.4 0.209 98.3 0.309 98.3 0.553 99.1 0.097 101.4 0.606 101.2 0.728 100.9 0.290

AGE, acute gastroenteritis; APT, acute pharyngotonsillitis; AOM, acute otitis media; URI, upper respiratory infection.

*p value from chi-square test; Values during Middle East respiratory syndrome epidemic period (June to July).

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