• Vol. 51 No. 8, 483–492
  • 29 August 2022

Nationwide study of the characteristics of frequent attenders with multiple emergency department attendance patterns



Introduction: The burden of frequent attenders (FAs) of emergency departments (EDs) on healthcare resources is underestimated when single-centre analyses do not account for utilisation of multiple EDs by FAs. We aimed to quantify the extent of multiple ED use by FAs and to characterise FAs.

Methods: We reviewed nationwide ED attendance in Singapore data from 1 January 2006 to 31 December 2018 (13 years). FAs were defined as patients with ≥4 ED visits in any calendar year. Single ED FAs and multiple ED FAs were patients who attended a single ED exclusively and ≥2 distinct EDs within the year, respectively. Mixed ED FAs were patients who attended a mix of a single ED and multiple EDs in different calendar years. We compared the characteristics of FAs using multivariable logistic regression.

Results: We identified 200,130 (6.3%) FAs who contributed to1,865,704 visits (19.6%) and 2,959,935 (93.7%) non-FAs who contributed to 7,671,097 visits (80.4%). After missing data were excluded, the study population consisted of 199,283 unique FAs. Nationwide-linked data identified an additional 15.5% FAs and 29.7% FA visits, in addition to data from single centres. Multiple ED FAs and mixed ED FAs were associated with male sex, younger age, Malay or Indian ethnicity, multiple comorbidities, median triage class of higher severity, and a higher frequency of ED use.

Conclusion: A nationwide approach is needed to quantify the national FA burden. The multiple comorbidities and higher frequency of ED use associated with FAs who visited multiple EDs and mixed EDs, compared to those who visited a single ED, suggested a higher level of ED burden in these subgroups of patients. The distinct characteristics and needs of each FA subgroup should be considered in future healthcare interventions to reduce FA burden.

Emergency department (ED) overcrowding is a growing issue that threatens public health in various parts of the world,1 including the US,2 UK,3 Australia,4 Japan5 and Taiwan.6

Individuals who visit the ED repeatedly, known as frequent attenders (FAs), have been identified as a possible driver of ED overcrowding. While the definition of a FA varies in the literature, a commonly used threshold is ≥4 ED presentations within a year.7-10 FAs represent a small proportion of ED patients but contribute a disproportionate number of ED visits, exerting an excessive strain on ED resources9 as well as related medical services.11

FAs may exacerbate the problem of poor quality of care, prolonged waiting times, insufficient admission beds and delayed care,12 thereby leading to detrimental health outcomes. Moreover, studies have reported that FAs may not be using the ED appropriately.9,10,13-15

Most studies on repeated ED use by FAs have focused on single centres with limited multicentre assessment of ED use.7 In the US, limited statewide studies reported 58% FAs in Massachusetts16 and 62% FAs in Utah17 visiting multiple EDs (≥ 2 different EDs). To the best of our knowledge, few studies on FAs have been conducted on a national level.9,18-20 Without national data, the burden of FAs is likely to be underestimated when FAs visit multiple EDs within a country.20 Furthermore, use of multiple EDs is associated with problems such as over-treating,21 drug misuse,22,23 and discontinuity of care.24

Consistent with global trends, Singapore faces an increase in ED attendances over the years25,26 and ED overcrowding remains a chronic problem.27 Currently, there are 10 public hospitals in Singapore (8 general hospitals and 2 specialised hospitals) with 24-hour emergency services that are easily accessible.

In the present study, data of nationwide ED attendance over a 13-year period across all public hospitals in Singapore were analysed to quantify the degree to which FAs sought care at EDs. Single hospital analyses were compared with nationwide data. We sought to determine how characteristics associated with ED attendance behaviour differed in (1) FAs who visited a single ED only; (2) FAs who visited multiple EDs; and (3) FAs who attended a mix of a single ED and multiple EDs in different calendar years.


Study design and population

This was a retrospective review of ED attendance records from all public hospitals in Singapore from 1 January 2006 to 31 December 2018. The public healthcare system in Singapore comprises 3 integrated healthcare clusters—Singapore Health Services, National Healthcare Group, and National University Health System—with 8 public general hospitals under the clusters. In 2011, the National Electronic Health Record (NEHR) system, which consolidates all patients’ electronic medical records across public (mandatory data contribution) and private (voluntary data contribution) healthcare institutions on a single secure platform, was implemented. Medical records on NEHR were anonymised to form Ministry of Health, Singapore’s Omnibus database. In our study, we utilised nationwide ED de-identified electronic health data from Omnibus. Although patient identification was masked, repeated visits for the same patient could be tracked through a study identifier. Visits to specialised hospitals (a women’s and children’s hospital, and a psychiatric hospital) and visits with missing study identifiers were excluded from the analysis.

FAs were identified as patients with ≥4 ED visits in any calendar year, which was consistent with commonly reported definitions in FA studies.9,10 FAs of a single ED (single ED FAs) were identified as FAs who sought care from 1 ED in any calendar year exclusively throughout the study period. FAs of multiple EDs (multiple ED FAs) referred to FAs who sought care in ≥2 distinct EDs in any calendar year exclusively throughout the study period. FAs who attended a mix of a single ED and multiple EDs in different calendar years of the study period were referred to as mixed ED FAs in this study. Institutional review board exemption was obtained for the study.

Data variables

Patient demographics (age, sex and ethnicity), ED attendance characteristics, and variables that were found in the literature to be associated with frequent ED visits2,4-7,16,17,28 were included in our analysis. The age of patients at their first ED visit was categorised into 5 age groups (≤25, 26–45, 45–65, 66–85, >85 years old). Ethnicity was categorised into the 4 main ethnic groups in Singapore as Chinese, Malay, Indian and others. ED attendance characteristics included triage class (based on patient acuity category scale), number of comorbidities, admission rate, frequency of ED use, and final diagnosis that was based on World Health Organization International Classification of Diseases Ninth Revision (ICD-9), Tenth Revision (ICD-10) and Australian Modification (ICD-10-AM).

For each patient, we computed the median triage category over all ED visits and the proportion of ED visits that resulted in hospital admission. Highly frequent use of ED was taken to be >7 ED visits within a calendar year.29 The most common final diagnosis was identified for each patient and categorised into broad groups of conditions under each relevant ICD-9 chapter heading.30

Statistical analysis

We compared the demographics of FAs and their ED attendance characteristics using chi-square tests for categorical data and Mann-Whitney U test for continuous variables.

Multivariable logistic regression modelling, with unique individuals as the unit of analysis, was performed to determine characteristics associated with multiple and mixed ED use in FAs. Factors found significant in univariable analyses were included in the multivariable logistic regression model. A two-tailed P value of <0.05 was considered statistically significant. Odds ratios (OR) and corresponding 95% confidence intervals (CI) were reported as applicable. All data analyses were performed using STATA version 15.1 (StataCorp, College Station, US).


From 1 January 2006 to 31 December 2018, a total of 11,641,406 ED visits were recorded. We excluded 17.5% of visits to specialised hospitals and 0.51% visits with missing study identifiers (Fig. 1). We identified 200,130 (6.3%) patients as FAs who contributed to 1,865,704 ED visits (19.6%), and 2,959,935 (93.7%) non-FAs who contributed to 7,671,097 (80.4%) ED visits. After excluding missing data, the final study population consisted of 199,283 unique FAs.


Fig. 1. Study population flowchart
ED: emergency department; FA: frequent attender; ID: identifier
a Institute of Mental Health, KK Women’s and Children’s Hospital, Singapore



Fig. 2. Number of emergency department patients and emergency department visits at all public general hospitals in Singapore by calendar year from 2006 to 2018.
ED: emergency department; FA: frequent attender

Fig. 2 shows the yearly trend of the total number of ED patients and corresponding ED visits. We observed an increase in the number of ED patients and ED visits by 39.7% and 34.8%, respectively, from 2006 to 2018. Consistent with this increasing trend, the number of FAs and their corresponding ED visits were also found to have increased over the study period by 24.9% and 16.4%, respectively.

Compared to 173,329 FAs identified from aggregating the numbers from all individual hospitals, nationwide linked data identified 200,130 FAs, which was an additional 15.5% of FAs identified (Table 1). Table 2 shows the demographics and ED attendance characteristics of the FA population.

Table 1.  Frequent attenders in Singapore and their attributable ED visits nationwide and at individual hospitals, 2006–2018

HospitalNo. of FAsTotal patientsProportion of total patients (%)No. of ED visits by FAsTotal ED visitsProportion of total ED visits (%)
Hospital A28,662821,0173.49237,4831,764,08213.46
Hospital B36,834759,4584.85328,7651,905,64517.25
Hospital C37,554900,7734.17315,0712,056,40215.32
Hospital D22,751506,4104.49196,3031,124,89917.45
Hospital E30,703813,5693.77231,3441,777,14213.02
Hospital F11,341279,9434.0592,648563,52116.44
Hospital Gb5,352199,8452.6836,108317,74011.36
Hospital Hb13223,8550.5568427,3702.50

ED: emergency department; FA: frequent attender
a Nationwide linked data identified 200,130 FAs, which was an additional 15.5% of FAs when compared to 173,329 FAs identified if the numbers from all individual hospitals were aggregated
b Limited data available as operations of these hospitals commenced officially in 2015 (G) and 2018 (H)

Table 2.  Characteristics of frequent attenders in Singapore who visited a single emergency department versus multiple emergency departments versus mix of single and multiple emergency departments, 2006–2018


no. (%)


FAs of single ED, no. (%)


FAs of multiple EDs, no. (%)


FAs of single and multiple EDs (mixed EDs), no. (%)


P value
Demographic characteristics
Age, median (IQR), years44 (22–69)52 (23–73)33 (21–62)47 (22–67)<0.001
Age groups, years
≤2567,923 (34.1)27,459 (28.5)32,361 (41.7)8,103 (32.2)<0.001
26–4533,988 (17.1)16,086 (16.7)13,755 (17.7)4,147 (16.5)
46–6540,500 (20.3)19,392 (20.1)14,812 (19.1)6,296 (25.0)
66–8546,751 (23.5)26,876 (27.8)14,020 (18.1)5,855 (23.3)
>8510,121 (5.1)6,710 (7.0)2,625 (3.4)786 (3.1)
Male133,593 (67.0)60,466 (62.6)56,193 (72.4)16,934 (67.2)<0.001
Chinese113,617 (57.0)57,418 (59.5)43,522 (56.1)12,677 (50.3)<0.001
Malay31,749 (15.9)14,149 (14.7)12,803 (16.5)4,922 (19.5)
Indian27,405 (13.8)11,125 (11.5)11,358 (14.6)4,797 (19.1)
Others26,512 (13.3)13,831 (14.3)9,890 (12.8)2,791 (11.1)
Attendance characteristics
Median triage class
P18,231 (4.1)4,852 (5.0)2,529 (3.3)850 (3.4)<0.001
P285,453 (42.9)43,152 (44.7)29,455 (38.0)12,846 (51.0)
P3/P4105,599 (53.0)48,519 (50.3)45,589 (58.8)11,491 (45.6)
No. of comorbidities
08,332 (4.2)4,620 (4.8)3,302 (4.3)410 (1.6)<0.001
1134,812 (67.7)67,191 (69.6)52,626 (67.8)14,995 (59.5)
≥256,139 (28.2)24,712 (25.6)21,645 (27.9)9,782 (38.8)
Admission rate
<0.5118,189 (59.3)52,869 (54.8)50,883 (65.6)14,437 (57.3)<0.001
≥0.581,094 (40.7)43,654 (45.2)26,690 (34.4)10,750 (42.7)
Frequency of ED use
4–7 visits per year169,116 (84.9)90,056 (93.3)65,277 (84.2)17,244 (68.5)<0.001
>7 visits per year30,167 (15.1)6,467 (6.7)12,296 (15.9)7,943 (31.5)
Most common final diagnosis related to
Infectious diseases19,261 (9.7)10,736 (11.1)7,195 (9.3)1,330 (5.3)<0.001
Neoplasms3,513 (1.8)1,890 (2.0)1,531 (2.0)92 (0.4)
Endocrine, nutritional and related diseases8,295 (4.2)4,260 (4.4)2,791 (3.6)1,244 (4.9)
Mental disorders2,846 (1.4)1,093 (1.1)1,399 (1.8)354 (1.4)
Nervous system and sense organs7,528 (3.8)3,297 (3.4)3,604 (4.7)627 (2.5)
Circulatory system14,032 (7.0)7,300 (7.6)4,880 (6.3)1,852 (7.4)
Respiratory system44,640 (22.4)21,592 (22.4)16,440 (21.2)6,608 (26.2)
Digestive system13,884 (7.0)7,103 (7.4)5,322 (6.9)1,459 (5.8)
Genitourinary system7,161 (3.6)4,112 (4.3)2,185 (2.8)864 (3.4)
Skin and subcutaneous tissue6,220 (3.6)3,275 (3.4)2,189 (2.8)756 (3.0)
Musculoskeletal system and connective tissue9,134 (3.1)4,212 (4.4)3,828 (4.9)1,094 (4.3)
Symptoms, signs and ill-defined conditions40,635 (20.4)18,490 (19.2)15,696 (20.2)6,449 (25.6)
Injury and poisoning20,287 (10.2)8,101 (8.4)9,893 (12.8)2,293 (9.1)
Others1,846 (0.9)1,062 (1.1)620 (0.8)164 (0.7)

FAs of multiple EDs and mixed EDs were characterised by younger age, with a median age of 33 years (IQR [interquartile range] 21–62) and 47 years (IQR 22–67), respectively, compared to 52 years (IQR 23–73) for FAs of a single ED. A higher proportion of FAs who visited multiple EDs (72.4%) were males compared to those who visited single EDs (62.6%) and mixed EDs (67.2%). FAs of Chinese (59.5%) and other (14.3%) ethnicities tended to visit a single ED, while FAs of Malay (19.5%) and Indian (19.1%) ethnicities showed mixed ED attendance behaviour.

The majority of all FAs (59.5–69.6%) had 1 comorbid condition, with a higher proportion of mixed ED FAs (38.8%) having ≥2 comorbidities compared to FAs who visited single (25.6%) and multiple EDs (27.9%). The majority of FAs who visited multiple EDs had a median triage class of lowest severity, i.e. P3/P4 (58.8%), while the majority of mixed ED FAs had a median triage class of higher severity, i.e. P2 (51.0%). A higher proportion of mixed ED FAs (25.6%) had symptoms, signs and ill-defined conditions as the final diagnoses compared to FAs who visited a single ED (19.2%) and multiple EDs (20.2%).

Multivariable analysis showed that FAs who visited multiple EDs and mixed EDs were associated with male sex, younger age, Malay or Indian ethnicities, multiple comorbid conditions, median triage class of higher severity, and a higher frequency of ED use (Table 3).

Table 3.  Univariable and multivariable analysis of factors associated with frequent attenders in Singapore who visited multiple emergency departments and a mix of single and multiple emergency departments (versus a single emergency department)

ParametersUnivariable, OR (95% CI)Multivariable adjusted, OR (95% CI)a
 FAs of multiple EDs FAs of single and multiple EDs (mixed EDs)FAs of multiple EDsFAs of single and multiple EDs (mixed EDs)
Age groups, years
  ≤25 (reference)
  26–450.73 (0.71–0.75)0.87 (0.84–0.91)0.76 (0.74–0.79)0.94 (0.90–0.99)
  46–650.65 (0.63–0.67)1.10 (1.06–1.14)0.60 (0.58–0.62)0.92 (0.88–0.97)
  66–850.44 (0.43–0.45)0.74 (0.71–0.77)0.42 (0.40–0.43)0.64 (0.60–0.67)
  >850.33 (0.32–0.35)0.40 (0.32–0.35)0.33 (0.31–0.35)0.36 (0.33–0.39)
  Female (reference)
  Male1.57 (1.54–1.60)1.22 (1.19–1.26)1.25 (1.22–1.28)1.04 (1.01–1.07)
  Chinese (reference)
  Malay1.19 (1.16–1.23)1.54 (1.48–1.60)1.06 (1.03–1.09)1.40 (1.34–1.45)
  Indian1.35 (1.31–1.39)2.00 (1.93–2.08)1.17 (1.13–1.20)1.74 (1.67–1.82)
  Others0.94 (0.92–0.97)0.91 (0.87–0.96)0.78 (0.76–0.81)0.91 (0.87–0.96)
Median triage class
  P1 (reference)
  P21.31 (1.25–1.38)1.70 (1.58–1.83)1.15 (1.09–1.21)1.62 (1.50–1.76)
  P3/P41.80 (1.72–1.89)1.35 (1.25–1.46)0.93 (0.88–0.99)0.87 (0.80–0.95)
No. of comorbidities
  None (reference)
  11.10 (1.05–1.15)2.51 (2.27–2.79)1.05 (1.00–1.10)2.24 (2.02–2.48)
  ≥21.23 (1.17–1.29)4.46 (4.02–4.95)1.07 (1.02–1.13)3.39 (3.05–3.76)
Admission rate
  <0.5 (reference)
  ≥0.50.64 (0.62–0.65)0.90 (0.88–0.93)1.00 (0.97–1.03)1.04 (0.99–1.09)
Frequency of ED use
  4–7 visits per year (reference)
  >7 visits per year2.54 (2.47–2.62)5.17 (4.99–5.35)2.15 (2. 09–2.22)4.61 (4.45–4.79)
Most common final diagnosis related to
  Infectious diseases (reference)
  Neoplasms1.21 (1.12–1.30)0.39 (0.31–0.49)1.55 (1.44–1.68)0.36 (0.29–0.45)
  Endocrine, nutritional and related diseases0.98 (0.92–1.03)2.36 (2.17–2.57)1.30 (1.22–1.38)2.14 (1.96–2.34)
  Mental disorders1.91 (1.76–2.08)2.61 (2.28–2.99)1.87 (1.71–2.04)1.93 (1.68–2.22)
  Nervous system and sense organs1.63 (1.54–1.72)1.54 (1.39–1.70)1.50 (1.41–1.58)1.47 (1.32–1.63)
  Circulatory system1.00 (0.95–1.05)2.05 (1.90–2.21)1.33 (1.27–1.40)1.89 (1.74–2.05)
  Respiratory system1.14 (1.10–1.18)2.47 (2.32–2.63)0.95 (0.92–0.99)2.06 (1.93–2.20)
  Digestive system1.11 (1.07–1.17)1.66 (1.53–1.80)1.17 (1.12–1.23)1.53 (1.40–1.66)
  Genitourinary system0.79 (0.75–0.84)1.70 (1.55–1.86)0.96 (0.91–1.02)1.58 (1.44–1.74)
  Skin and subcutaneous tissue1.00 (0.94–1.06)1.86 (1.69–2.05)1.07 (1.01–1.14)1.86 (1.68–2.06)
  Musculoskeletal system and connective tissue1.36 (1.29–1.43)2.10 (1.92–2.29)1.29 (1.22–1.37)1.96 (1.79–2.14)
  Symptoms, signs and ill-defined conditions1.27 (1.22–1.31)2.82 (2.64–3.00)1.39 (1.33–1.44)2.37 (2.22–2.53)
  Injury and poisoning1.82 (1.75–1.90)2.28 (2.12–2.46)1.61 (1.54–1.68)2.11 (1.96–2.28)
  Others0.87 (0.79–0.97)1.25 (1.05–1.48)1.00 (0.90–1.11)1.19 (1.00–1.42)

CI: confidence interval; FA: frequent attender; OR: odds ratio
a Using stepwise logistic regression controlling for age, sex, ethnicity, median triage class, number of comorbidities, proportion of admissions, frequency of ED use and most common final diagnosis

Compared to FAs who were ≤25 years of age, the adjusted odds of multiple ED and mixed ED use were 0.33 time (95% CI 0.31–0.35) and 0.36 time (95% CI 0.33–0.39) lower, respectively, in FAs >85 years old. The odds of multiple ED and mixed ED use were 1.25 (95% CI 1.22–1.28) and 1.04 (95% CI 1.01–1.07) times higher, respectively, in male FAs compared to female FAs. FAs of Malay or Indian ethnicity had 1.06 (95% CI 1.03–1.09) and 1.17 times (95% CI 1.13–1.20) increased odds of visiting multiple EDs, respectively, compared to FAs who were Chinese. Similarly, FAs of Malay or Indian ethnicity had 1.40 (95% CI 1.34–1.45) and 1.74 times (95% CI 1.67–1.82) increased odds of visiting mixed EDs than FAs who were Chinese.

A highly frequent ED use of >7 visits per year was found to be most strongly associated with multiple ED (OR 2.15, 95% CI 2.09–2.22) and mixed ED (OR 4.61, 95% CI 4.45–4.79) use in FAs. The odds of multiple ED (OR 0.93, 95% CI 0.88–0.99) and mixed ED (OR 0.87, 95% CI 0.80–0.95) use were lower for FAs with a median triage class of P3/P4 (lowest severity), when compared to FAs with median triage class of P1 (highest severity), while the association between admission rate and multiple ED (P=0.92) and mixed ED (P=0.08) use in FAs became attenuated.

FAs who had ≥2 comorbidities had 1.07 times (95% CI 1.02–1.13) and 3.39 times (95% CI 3.05–3.76) increased odds of visiting multiple EDs and mixed EDs, respectively, than FAs without any comorbidities. Compared with infectious diseases as the reference category, the top 3 most common final diagnoses associated with FAs of multiple EDs were mental disorders (OR 1.87, 95% CI 1.71–2.04); injuries and poisoning (OR 1.61, 95% CI 1.54–1.68); and neoplasms (OR 1.55, 95% CI 1.44–1.68). For mixed FAs, they were symptoms, signs and ill-defined conditions (OR 2.37, 95% CI 2.22–2.53); endocrine, nutritional and related diseases (OR 2.14, 95% CI 1.96–2.34); and injury and poisoning (OR 2.11, 95% CI 1.96–2.28).


Our study provided a comprehensive perspective on FAs using nationwide, longitudinal ED attendance data and highlighted the heterogeneity among FAs with different ED attendance patterns. It affirmed single-centre studies9,18,19 that FAs account for a disproportionately large share of ED attendances and the magnitude was previously underestimated when comparing nationwide data and data aggregated from individual hospitals. Addition of the number of FAs from the ED of each hospital underestimated the actual FA use of EDs.

FAs who visited multiple EDs and mixed EDs were not captured in hospital-specific data but could be accounted for using nationwide linked data. Although majority of FAs (48.4%) visited a single ED, half of the FAs (51.6%) visited multiple EDs or had mixed ED attendance behaviour. These findings signified that a substantial number of FAs would not be accounted for if only data at a single hospital were analysed. As such, integrated datasets that include all EDs in a given region or country is important to realise the full extent of the FA burden.

A failure to consider the overlapping pattern of ED use has various implications. The costs of multiple ED utilisation by FAs are higher compared to aggregate costs from a single ED.29 Multiple ED use poses a challenge in settings where ED physicians need to make rapid decisions under stressful conditions despite insufficient knowledge with regards to previous care at EDs. This may result in duplicative, unnecessary or suboptimal patient care.31

Our findings showed that younger age (≤25 years old) and male sex were associated with FAs who visited multiple EDs and mixed EDs. In contrast, studies based on single-centre assessments of ED use reported FAs as being older adults and >65 years old.9,18,19 This suggested that single ED analyses failed to capture a whole FA population, particularly younger aged FAs who may have greater mobility and may visit EDs at multiple locations.32 Our findings corroborated with Chan et al. who observed higher rates of frequent attendance in younger males (16–25 years old) in Singapore.18 The authors postulated that this was likely due to the prevalence of conscripted soldiers seeking treatment at the ED. Similarly, a study in 1 tertiary hospital reported that 7% of their annual ED workload was contributed by conscripted soldiers.19 In Singapore, all males aged ≥18 years are required to serve 2 years of mandatory military service. These military personnel can access ED services without fees, which may explain the higher consumption of ED services by this group of FAs.33

FAs with 2 or more comorbidities tended to visit multiple EDs or mixed EDs (>3 times increased odds) compared to those with no comorbidities, suggesting that these groups of FAs were characterised by more complex medical profiles. Interestingly, only 30–40% FAs of multiple ED and mixed ED attendance had an admission rate of >0.5, i.e., they were less likely to be admitted as inpatients for further management and this may be related to their younger age. Further research may be needed to determine if these FAs could be better managed in the community.

FAs of multiple EDs and mixed EDs were highly frequent users of EDs compared to FAs of a single ED, with 16% of multiple ED FAs and one third of mixed ED FAs having >7 visits per year. This observation was consistent with existing literature on multiple ED use.32 This tendency could in part be attributed to an increase in random chance of visiting more than 1 ED as the frequency of ED use was increased.29

Importantly, our findings showed a strong association between mental disorders (including alcohol/substance abuse) and the use of multiple EDs by FAs, a finding that was aligned with prior literature on multiple ED use.31,32 This suggested that EDs in Singapore could be facing the effects of unavailable or insufficient treatment opportunities for mental disorders. FAs who presented with such diagnoses were likely sent to the ED during times of crisis, and often by third parties (e.g. law enforcement or ambulance). These patients would then be conveyed to the nearest ED, increasing the likelihood of visiting different EDs.32 Stronger infrastructure to address issues of mental health and substance use may be critical to mitigate the use of multiple EDs.32

For mixed ED FAs, a strong association was found for the final diagnoses of general symptoms/ill-defined conditions (including syncope, nausea and chest pain), which may be related to the higher proportion of individuals with multiple comorbidities seen in this group. Our observation that mixed ED FAs were the heaviest users of EDs with a significant proportion of them visiting the ED >7 times in a year, corroborated previous studies which demonstrated an increased ED/acute care utilisation with increased number of comorbidities.34,35 Further studies are needed to elucidate the reasons for ED care seeking instead of primary care for this group of patients.

The FA population was found to be not demographically or clinically homogeneous, with each of the 3 groups of FAs having distinct characteristics and needs.16 This is an important consideration that should guide the development of future health interventions to reduce FA numbers, improve patient outcomes and encourage the use of finite ED resources more efficiently, especially when ED visits continue to rise. The magnitude of the FA population overlap among EDs suggests that coordination of care across multiple institutions is warranted to address the FA burden.

Future research

The scope for future research includes investigating the persistence of multiple and mixed ED use over time and conducting qualitative studies to explore reasons for ED use in terms of the healthcare system (e.g. ambulance transport policies, accessibility and quality of primary care services) and personal preference factors, so as to better assess the extent to which FA behaviour may be problematic, inappropriate or preventable.29 Future research should also seek to understand and evaluate the impact of multiple and mixed ED use on patient care utilisation and outcomes.31

Study limitations

There were several methodological limitations in our study. Firstly, there was a lack of critical variables that may influence ED-seeking behaviour, such as education level, socioeconomic status, employment status, social history and mode of arrival to the ED. Social circumstances such as homelessness or isolation may specifically increase the risk of multiple ED use but these were unavailable in the dataset.

Secondly, the study was subjected to the common limitations of using existing datasets collected for clinical and administrative purposes. These included missing data and a potential misclassification of information, especially when data could be collected under stress conditions at the ED.

Lastly, our findings may not be generalisable to other settings as health-seeking behaviour of FAs are intricately related to factors such as healthcare funding and delivery models, which differ across regions or countries.


To our knowledge, this is the first study in Singapore to compare factors associated with FAs who visited single EDs, multiple EDs and mixed EDs. The use of nationwide data provided a comprehensive perspective on FAs. A nationwide approach is needed to quantify the national FA burden, as single hospital studies may greatly underestimate the problem.

The multiple comorbidities and higher frequency of ED use associated with FAs who visited multiple EDs and mixed EDs, compared to those who visited a single ED, suggested a higher level of ED burden in these subgroups of patients. The distinct characteristics and needs of these patients should be considered in future healthcare interventions to reduce FA of EDs.



  1. Di Somma S, Paladino L, Vaughan L, et al. Overcrowding in emergency department: an international issue. Intern Emerg Med 2015;10:171-5.
  2. Vinton DT, Capp R, Rooks SP, et al. Frequent users of US emergency departments: Characteristics and opportunities for intervention. Emerg Med J 2014;31:526-32.
  3. Dent A, Hunter G, Webster AP. The impact of frequent attenders on a UK emergency department. Eur J Emerg Med 2010;17:332-6.
  4. Markham D, Graudins A. Characteristics of frequent emergency department presenters to an Australian emergency medicine network. BMC Emerg Med 2011;11:21.
  5. Takeuchi S, Funakoshi H, Nakashima Y, et al. Unique characteristics of frequent presenters to the emergency department in a Japanese population: a retrospective analysis. Acute Med Surg 2019;6:145-51.
  6. Hsu CM, Liang LL, Chang Y Te, et al. Emergency department overcrowding: Quality improvement in a Taiwan Medical Center. J Formos Med Assoc 2019;118:186-93.
  7. Pines JM, Asplin BR, Kaji AH, et al. Frequent users of emergency department services: Gaps in knowledge and a proposed research agenda. Acad Emerg Med 2011;18:e64-9.
  8. Chiu Y, Racine-Hemmings F, Dufour I, et al. Statistical tools used for analyses of frequent users of emergency department: A scoping review. BMJ Open 2019;9:e027750.
  9. Boh C, Li H, Finkelstein E, et al. Factors Contributing to Inappropriate Visits of Frequent Attenders and Their Economic Effects at an Emergency Department in Singapore. Acad Emerg Med 2015;22:1025-33.
  10. Oh HC, Chow WL, Gao Y, et al. Factors associated with inappropriate attendances at the emergency department of a tertiary hospital in Singapore. Singapore Med J 2020;61:75-80.
  11. Kuek BJW, Li H, Yap S, et al. Characteristics of Frequent Users of Emergency Medical Services in Singapore. Prehospital Emerg Care 2019;23:215-24.
  12. Dunn R. Reduced access block causes shorter emergency department waiting times: An historical control observational study. Emerg Med 2003;15:232-8.
  13. McHale P, Wood S, Hughes K, et al. Who uses emergency departments inappropriately and when – a national cross-sectional study using a monitoring data system. BMC Med 2013;11:258.
  14. Miyazawa A, Maeno T, Shaku F, et al. Inappropriate use of the emergency department for nonurgent conditions: Patient characteristics and associated factors at a Japanese hospital. J Gen Fam Med 2019;20:146-53.
  15. Cheng L, Ng WM, Lin Z, et al. Factors reducing inappropriate attendances to emergency departments before and during the COVID-19 pandemic: A multicentre study. Ann Acad Med Singap 2021;50:818-26.
  16. Fuda KK, Immekus R. Frequent Users of Massachusetts Emergency Departments: A Statewide Analysis. Ann Emerg Med 2006;48:9-16.
  17. Cook LJ, Knight S, Junkins EP, et al. Repeat Patients to the Emergency Department in a Statewide Database. Acad Emerg Med 2004;11:256-63.
  18. Chan JS, Tin AS, Chow WL, et al. Frequent attenders at the emergency department: an analysis of characteristics and utilisation trends. Proc Singapore Healthc 2018;27:12-9.
  19. Paul P, Heng BH, Seow E, et al. Predictors of frequent attenders of emergency department at an acute general hospital in Singapore. Emerg Med J 2010;27:843-8.
  20. Shen Y, Teo EWK, Liu N, et al. Data-driven approach to defining the emergency department frequent attender using a cohort of 10 years. J Acute Med 2018;8:6-16.
  21. Sansone RA, Sansone LA. Doctor shopping: a phenomenon of many themes. Innov Clin Neurosci 2012;9:42-6.
  22. Paulozzi LJ, Strickler GK, Kreiner PW, et al.; Centers for Disease Control and Prevention (CDC). Controlled Substance Prescribing Patterns – Prescription Behavior Surveillance System, Eight States, 2013. MMWR Surveill Summ 2015;64:1-14.
  23. Hall AJ, Logan JE, Toblin RL, et al. Patterns of Abuse Among Unintentional Pharmaceutical Overdose Fatalities. JAMA 2008;300:2613-20.
  24. Biernikiewicz M, Taieb V, Toumi M. Characteristics of doctor-shoppers: a systematic literature review. J Mark Access Heal Policy 2019;7:1595953.
  25. Data.gov.sg. Attendances at Accident & Emergency Departments, Specialist Outpatient Clinics, Polyclinics and Public Sector Dental Clinics, 31 May 2021. Available at: https://data.gov.sg/dataset/attendances-at-accident-emergency-departments-specialist-outpatient-clinics-and-polyclinics. Accessed on 27 April 2021.
  26. Tang XR, Pek PP, Siddiqui FJ, et al. Determinants of emergency department utilisation by older adults in Singapore: A systematic review. Ann Acad Med Singap 2022;51:170-9.
  27. Schoenenberger LK, Bayer S, Ansah JP, et al. Emergency department crowding in Singapore: Insights from a systems thinking approach. SAGE Open Med 2016;4:205031211667195.
  28. Uí Bhroin S, Kinahan J, Murphy A. Profiling frequent attenders at an inner city emergency department. Ir J Med Sci 2019;188:1013-9.
  29. Fertel BS, Hart KW, Lindsell CJ, et al. Patients who use multiple EDs: Quantifying the degree of overlap between ED populations. West J Emerg Med 2015;16:229-33.
  30. World Health Organization. International classification of diseases: [‎9th]‎ ninth revision, basic tabulation list with alphabetic index. Available at: https://apps.who.int/iris/handle/10665/39473. Accessed on 31 March 2022.
  31. Lyons TW, Olson KL, Palmer NP, et al. Patients Visiting Multiple Emergency Departments: Patterns, Costs, and Risk Factors. Acad Emerg Med 2017;24:1349-57.
  32. Giannouchos TV, Washburn DJ, Kum HC, et al. Predictors of Multiple Emergency Department Utilization among Frequent Emergency Department Users in 3 States. Med Care 2020;58:137-45.
  33. Oktay C, Cete Y, Eray O, et al. Appropriateness of emergency department visits in a Turkish university hospital. Croat Med J 2003;44:585-91.
  34. Gruneir A, Griffith LE, Fisher K, et al. Increasing comorbidity and health services utilization in older adults with prior stroke. Neurology 2016;87:2091-8.
  35. Griffith LE, Gruneir A, Fisher K, et al. Insights on multimorbidity and associated health service use and costs from three population-based studies of older adults in Ontario with diabetes, dementia and stroke. BMC Health Serv Res 2019;19:313.