Skip to main content

Advertisement

  • Research article
  • Open Access
  • Open Peer Review

Social factors in frequent callers: a description of isolation, poverty and quality of life in those calling emergency medical services frequently

BMC Public Health201919:684

https://doi.org/10.1186/s12889-019-6964-1

  • Received: 29 January 2019
  • Accepted: 13 May 2019
  • Published:
Open Peer Review reports

Abstract

Background

Frequent users of emergency medical services (EMS) comprise a disproportionate percentage of emergency department (ED) visits. EDs are becoming increasingly overwhelmed and a portion of use by frequent callers of EMS is potentially avoidable. Social factors contribute to frequent use however few studies have examined their prevalence. This study aims to describe social isolation/loneliness, poverty, and quality of life in a sample of frequent callers of EMS in the Hamilton region, a southern Ontario mid-sized Canadian city.

Study design

Cross-sectional quantitative study.

Methods

We surveyed people who called EMS five or more times within 12 months. A mailed self-administered survey with validated tools, and focused on four major measures: demographic information, social isolation, poverty, and quality of life.

Results

Sixty-seven frequent EMS callers revealed that 37–49% were lonely, 14% had gone hungry in the preceding month, and 43% had difficulties making ends meet at the end of the month. For quality of life, 78% had mobility problems, 55% had difficulty with self-care, 78% had difficulty with usual activities, 87% experienced pain/discomfort, and 67% had anxiety/depression. Overall quality adjusted life years value was 0.53 on a scale of 0 to 1. The response rate was 41.1%.

Conclusions

Loneliness in our participants was more common than Hamilton and Canadian rates. Frequent EMS callers had higher rates of poverty and food insecurity than average Ontario citizens, which may also act as a barrier to accessing preventative health services. Lower quality of life may indicate chronic illness, and users who cannot access ambulatory care services consistently may call EMS more frequently. Frequent callers of EMS had high rates of social loneliness and poverty, and low quality of life, indicating a need for health service optimization for this vulnerable population.

Keywords

  • Health services
  • Emergency medical services
  • Frequent callers
  • Social factors
  • Poverty
  • Quality of life
  • Social isolation

Background

In recent decades, emergency medical service (EMS) use has increased dramatically, straining emergency departments (ED) beyond their capacity and representing a significant cost in the healthcare budget. [1] Between 2012 and 2014 alone, Ontario ambulance use has increased by 8%, representing an increase of 100,000 dispatches and 17% in costs. Out of all calls, 58,000 patients (58%) are transported and 48,000 (48%) are not. [2] Some emergency service use among frequent callers is likely preventable, and may represent a discrepancy between physician and patient perceptions of medical emergencies. [37] In previous literature surveying emergency service use, one out of three ambulance dispatches have not been perceived as medical emergencies by health services researchers, [8] and frequent callers account for up to 40% of transports. [914] In specifically Canadian studies, frequent callers comprise 2.1–3.6% of overall ED users but account for 9.9–13.8% of visits. Frequent callers have been defined as people who call 4 to 5 or more times within 1 year, [15, 16] though definitions range from 3 to 10 times per year. [1620]

Existing literature from the United States of America (USA) characterizing frequent ED and EMS users (as opposed to callers) reveals that they are often vulnerable populations [15, 21] who tend to be of lower socioeconomic status, [22] have psychiatric and substance use disorders, [23] or have chronic medical conditions (often with multiple comorbidities). [4, 2428] Common chronic condition exacerbations were found to be in ambulatory care sensitive diseases such as asthma, [29, 30] chronic obstructive pulmonary disease, renal failure, and sickle cell anemia. [23] Consistent with this, frequent EMS users have been found to be high users of ambulatory care services (outpatient medical care that prevents or reduces hospitalizations). [31] Amongst non-specific presenting complaints, nausea and vomiting, chest pain, anxiety, pain, and shortness of breath are most common, which are not necessarily differing from non-frequent callers. [9, 31] Frequent EMS users also have poorer self-rated general health, [32] higher mortality rates post-ED, [33] hospital admissions, [34] and higher rates of ambulance usage. [34]

A growing body of literature studies potential psychosocial factors behind frequent ED usage. Some propose that frequent EMS users lack proper access to primary healthcare services and are forced to rely on emergency health services as their only source of regular medical care, thus presenting for non-urgent health issues. [3537] Ambulatory care-sensitive medical conditions such as asthma, diabetes, chronic obstructive pulmonary disease and congestive heart failure are one example where patients rely heavily on close monitoring in outpatient health services; without this, they are more likely than others to require ED visits and unscheduled hospitalization. [37] Social isolation and loneliness have also been identified as predictors of frequent ED usage (lacking close friends, living alone, unemployment, disability retirement, and subjective feelings of loneliness). [1, 30, 33, 3840] These patients may also have emotional, cognitive, and stress-related neuroendocrine, cardiovascular and immune changes that contribute to difficulty managing their health. [40, 41] The increasing proportion of elderly citizens who live alone is another potential reason for recent increases in ED visits amongst the elderly. [42] Lastly, frequent EMS users have higher rates of poverty, which is associated with a higher prevalence of chronic illnesses, as well as barriers to preventative and primary healthcare services. [43, 44] Additionally, increasing ED use has been associated with homelessness and unstable housing status, further emphasizing the vulnerability of this population. [21] However, the extent to which social factors actually determine ED and EMS usage has not yet been determined.

Existing literature has largely focused on the characteristics of frequent users of EDs, rather than callers to EMS, who are a different population. [5] Most research regarding frequent users has taken place in large American cities, and has used differing definitions of a frequent user, and tended to focus on psychiatric illness, failing to describe their actual characteristics. There are far fewer primary studies in mid-sized cities and in Canada, which have vastly different health service infrastructure than USA (i.e. universal health insurance). Given that a large proportion of frequent users of ED services arrive by ambulance (59.3% of frequent users vs. 12% of the general population), [5, 15, 17, 4549] studying this population of frequent callers to EMS will aid in continuing to find a solution to ED overcrowding. Investigating the profile of social factors will assist in planning primary and preventative health services development in these subpopulations of frequent EMS callers.

This study aims to describe social isolation/loneliness, poverty, and quality of life in a sample of frequent users of EMS in the Hamilton region, a southern Ontario mid-sized Canadian city.

Methods

Study design and sample

This cross-sectional quantitative study surveyed participants who had called 911 at least five times between April 1st 2015 and March 31, 2016. Participants were residents of the City of Hamilton 18 years or older, and were invited to participate by the Hamilton Paramedic Service, who had extracted their names from their database. The survey was distributed in two occurrences for ease of workload; initially commencing May 2016 and then a second sample commencing September 2017 each time using a modified Dillman’s Total Design. The surveys were mailed with an introductory letter with study objectives and explanation, instructions for return, a pre-stamped envelope, and a $5 gift card. A second mail-out included a reminder letter and was sent 1 week after initial mail-out to non-responding participants. A final mail-out 3–7 weeks later included a replacement introductory letter, instructions for returning the survey, the survey itself, and a pre-stamped envelope. When participants returned the survey, they were given an additional $5 gift card.

Measures

The survey questions focused on the following: (1) demographic information, (2) social isolation, (3) poverty, and (4) quality of life.

Demographic information collected included age, sex, body mass index (BMI) and employment status. To measure social isolation and loneliness, two well-validated scales were used since they measured different aspects of loneliness; the UCLA 3 Item Loneliness scale which could quantify loneliness, [50] and a portion of the De Jong Gierveld 6-Item Loneliness Scale which measured social loneliness. [51] To measure poverty, two highly sensitive and specific clinical screening questions were used – whether participants had trouble making ends meet at the end of the month, [52] and whether either they or their family members had gone hungry in the past month. [53] To measure quality of life, we used the EQ5D-3 L, a 5-item preference based instrument for 5 health states at 3 levels (mobility, self care, usual activities, pain/discomfort, anxiety/depression). [54] The scores were converted according to a Canadian preferences valuation to a score for quality adjusted life years (QALY). [54]

Ethical considerations

In order to adhere to high ethical standards, the survey was completely separate from any healthcare provided so that participants would not feel pressured or coerced to participate. Therefore, a group that already had difficulty accessing healthcare would not find this to be an additional barrier. The surveys were kept confidential and anonymous. Additionally compensation was provided for the time taken in filling out the survey. These ethical considerations passed Local Research Ethics Board Standards.

Data analysis

Descriptive statistics were calculated to describe social factors (poverty, loneliness, and quality of life). The mean, median, mode and 25th and 75th quartiles were calculated for QALY. Data was analyzed using SPSS statistical software, version 24. Missing data were excluded from the analyses and the final “valid percent” was taken.

Results

Demographics (Fig. 1)

253 eligible participants were identified. Of those, 81 were excluded as they had given an incomplete address and 5 were excluded as they were from a long-term care facility. 167 people in total were sent a mailed survey, and 67 completed the survey, yielding a response rate of 41.1%. Of the non-responders, 13 were found to be deceased, 21 declined the survey, and 66 did not respond even after reminders (Fig. 1).
Fig. 1
Fig. 1

Flow diagram for participants

Most of the respondents were older than 40 years of age (88.1%) (Table 1). With respect to employment status, 85.1% of the sample was unemployed. For BMI, 19.4% of participants had a normal BMI from 18.5–24.9, while 58.3% of the population was underweight, overweight or obese. Most individuals lived with someone (58.2%) but 38.8% of individuals lived alone.
Table 1

Demographic Data

Variable

Frequency (N = 67)

%

Age

18–24 yrs

1

1.5

25–40 yrs

7

10.4

41–64 yrs

27

40.3

65–74 yrs

15

22.4

75+ yrs

17

25.4

Sex

Male

33

49.3

Female

34

50.7

Employment Status

Employed

9

13.4

Not employed

57

85.1

Declined to answer

1

1.5

BMI

Underweight (< 18.5)

3

4.5

Normal Weight (18.5–24.9)

13

19.4

Overweight (25.0–29.9)

17

25.4

Obese Class I (30.0–34.9)

10

14.9

Obese Class II (35.0–39.9)

6

9

Obese Class III (> = 40.0)

3

4.5

Declined to answer

15

22.4

Living Arrangement

Lives by self

26

38.8

Live with one or more family members

32

47.8

Live with non-family member

7

10.4

Declined to answer

2

3

Non-responders had a similar age and sex distribution to responders. In terms of sex, 43.3% were female and 56.7% were male. In terms of age, the most represented categories were ages 41–64 (39.4%) and 74+ (31.7%), which are the same categories that were most represented among responders.

Social factors

On the UCLA 3 Item scale, 49.25% of participants achieved a “lonely” score of 6 to 9, while 47.76% of participants achieved a “not lonely” score of 3 to 5; 20.9% of participants felt that they lacked companionship often, and 40.3% felt that they lacked companionship some of the time. On the De Jong Social Loneliness questions, 37.3% were intensely lonely (Tables 2 and 3).
Table 2

UCLA Social Loneliness Score

Score summaries

Frequency

Percent

Lonely (Score = 6–9)

33

49.25

Not Lonely (Score = 3–5)

32

47.76

Declined to answer

2

2.99

Questionnaire responses:

Variables (score)

Frequency

Percent

There are enough people I feel close to

Yes, enough people to feel close to (1)

31

46.3

More or less people to feel close to (2)

21

31.3

No people to feel close to (0)

12

17.9

Declined to answer

3

4.5

How often feel left out

Hardly ever feel left out (0)

27

40.3

Some of the time feel left out (1)

27

40.3

Often feel left out (2)

11

16.4

Declined to answer

2

3

How often feel isolated

Hardly ever feel isolated (0)

27

40.3

Some of the time feel isolated (1)

24

35.8

Often feel isolated (2)

14

20.9

Declined to answer

2

3

Table 3

De Jong Social Loneliness Score

Score summaries:

Frequency

Percentage

0 (Not socially lonely)

19

28.4

1

7

10.4

2

12

17.9

3 (Intensely Socially lonely)

25

37.3

Declined to Answer

4

6

Questionnaire responses:

Variables (score)

Frequency

Percentage

Living Arrangement

Lives by self (0)

26

38.8

Live with one or more family members (1)

32

47.8

Live with non-family member (2)

7

10.4

Declined to answer

2

3

People to rely on

Yes there are people to rely on (1)

29

35.8

More or less, there are people to rely on (2)

24

35.8

No people to rely on (0)

13

19.4

Declined to answer

1

1.5

People to trust completely

Many people I can trust completely (yes −1)

27

40.3

More or less, people can trust completely (2)

18

26.9

No people I can trust completely (0)

20

29.9

Declined to answer

2

3

How often do you feel you lack companionship?

Lack companionship hardly ever (0)

26

38.8

Lack companionship some of the time (1)

27

40.3

Lack companionship often (2)

14

20.9

Declined to answer

0

0

Living Arrangement

Lives by self (0)

26

38.8

Live with one or more family members (1)

32

47.8

Nearly half of respondents (43.3%) reported not having enough money to make ends meet and 14.9% reported that they or a family member went hungry in the past month (Table 4).
Table 4

Poverty

Variable

 

N

%

In the past month, was there any day when you or anyone in your family went hungry because you did not have enough money for food?

Yes

10

14.9

No

55

82.1

Declined to Answer

2

3

Do you ever have trouble making ends meet at the end of the month?

Yes

29

43.3

No

37

55.2

Declined to Answer

1

1.5

Quality of life

A large percentage (74.6%) of participants experienced some problems walking; 11.9% were completely unable to wash and dress themselves; most had some problems performing usual activities (56.7%); most experienced pain and discomfort and a high proportion (67.1%) experienced moderate or extreme anxiety and depression (Table 5). When the EQ5D-3 L data were converted to QALYs, the mean was found to be 0.533 (out of a range of 0–1, where 1 described perfect quality of life). The 25th and 75th percentiles were 0.376 and 0.664 respectively.
Table 5

Quality of Life

Variable

 

N

%

Mobility

No problems walking

14

20.9

Some problems walking

50

74.6

Confined to bed

2

3

Declined to answer

1

1.5

Self care

No problems

30

44.8

Some problems (washing and dressing)

29

43.3

Unable to wash or dress self

8

11.9

Declined to answer

0

0

Usual activities

No problems performing usual activities

14

20.9

Some problems performing usual activities

38

56.7

Unable to perform usual activities

14

20.9

Declined to answer

1

1.5

Pain/Discomfort

None

8

11.9

Moderate

34

50.7

Extreme

24

35.8

Declined to answer

1

1.5

Anxiety/Depression

None

18

26.9

Moderate

35

52.2

Extreme

10

14.9

Declined to answer

4

6

Quality adjusted life years (QALY)

 Mean

0.53

 Median

0.56

 Mode

0.59

Discussion

We conducted a survey of 67 frequent users of EMS in a mid-sized Canadian city and found substantial social isolation, loneliness, income and food insecurity, as well as low quality of life. In the current body of literature, few studies of frequent users measure social isolation/loneliness and quality of life, and most of them survey ED users rather than EMS frequent users. [30, 39, 40] Therefore, our study represents a unique approach to emergency health service usage.

In this study, 37.3 to 49.3% of participants experienced significant degrees of loneliness. Comparatively, Canadian research from 2009 has cited that approximately 19–24% of Canadian seniors lack companionship or wish to participate in more social activities. [55] In Hamilton, in 2006, 15% of senior citizens were estimated to be isolated. [56] The high rates of loneliness found in our study are consistent with existing literature on frequent users of ED. People who live alone, lack friends, are divorced, or lack other social support have been shown to be more likely to be frequent users of ED. [17, 38, 57, 58] Accordingly, 38.8% of our participants live by themselves, a widely used indicator for social isolation, [59] compared to 28.2% Canadians (2016). [60] With respect to potential mechanisms, loneliness and frequent ED use have each been independently linked to increased morbidity, in which chronic illness, poor health behaviours, and poor mental health may result in increased mortality. [25, 39, 41, 6165] However, studies which show higher rates of loneliness in populations of frequent ED users have not found that rates of chronic illness differ between lonely and non-lonely individuals. [25, 39, 61]

Next, our results indicate that frequent callers to EMS have higher rates of poverty and food insecurity than average Ontario citizen, even those described in our population who are reachable and respond to survey; 14.9% of frequent callers were food insecure, compared to 8.2% of Ontario citizens in 2011. [66] Even more significantly, poverty rates were 43.3% in frequent callers, and 8.8% in Ontarians in 2014. [67] Frequent ED use has previously been associated with poverty in USA studies, where lack of medical insurance was a factor in the delay of seeking other primary and preventative healthcare. [3, 35] The presence of higher rates of poverty in our population is significant, as it is likely to suggest that factors other than lack of medical insurance contribute to frequent ED use behaviours. Besides insurance coverage, poverty can still represent a barrier to primary and preventative health services access in the form of lacking transportation to appointments, not being able to take time off work for appointments, or lack of money to pay for prescription drugs. [68]

Thirdly, participants in our study experienced a lower quality of life than Canadian population averages. In each of the 5 dimensions measured in the EQ5D-3 L, a significantly higher percentage experienced some or extreme problems: mobility (77.6% vs 22%), self care (55.2% vs. 4%), usual activities (77.6% vs. 23%), pain/discomfort (86.5% vs. 51%), and anxiety/depression (67.1% vs. 31%). [54] The most significant differences include difficulties in usual activities (54%), mobility (56%) and self care (51%), which may represent the most significant contributions toward EMS calls in frequent users. Previous studies have found high rates of mobility problems and functional decline in frequent users of ED, and that difficulty in activities of daily living are contributory to the decision to present to ED. [69, 70] Additionally, high rates of ambulatory care conditions have been reported in frequent users, the most common being pain-related conditions. [31, 37] This is consistent with the high prevalence of pain and discomfort found in our study.

Lastly, demographics of frequent EMS callers in our study are largely consistent with existing literature, which primarily studies frequent ED users. The majority of frequent users are younger than 65 years, [9, 61] and an equal number of males and females are frequent users of ED. [4, 14, 27, 71, 72] Other studies have described that younger users are more likely to be ED “superusers” (those with 15 or more annual ED visits), though unfortunately no studies have been conducted on similar statistics for EMS callers. [4, 9, 61] Our population’s unemployment rate was 85% – however, a limiting factor may be age, as 47.8% of participants were age 65+. After removing those participants, 37.3% of the population were unemployed, much higher than Ontario’s rate of 5.5%, suggesting unemployment to be a potential contributory factor toward frequent ED usage. [73] Unemployment could also contribute to and result from poverty and social isolation.

The combination of these numerous social factors represents a complex and multifactorial problem that may be an issue unable to be addressed by a purely biomedical approach traditionally used by emergency health services. We propose that a salutogenic approach to health service provision may be beneficial. Unlike traditional curative approaches, a salutogenic approach focuses on social factors which have been identified to create wellness. [74] Health is not viewed as being a dichotomous state of the presence or absence of disease, but rather is conceptualised along a health continuum between total health and death. [75] Salutogenic approaches to health are aware that total health may not be achieved in all instances, such as those with chronic illness, however, the overall wellness of the individual can be improved through addressing social factors related to the individual need, by linking the person to the appropriate resources for their situation. [76] Because paramedics have unique access to patients’ living environments, a salutogenic approach may be and has shown to be a promising option for paramedic and health service provision to effectively assess and address such social factors in patient populations. [77, 78]

Limitations of this study include the lack of a comparator group of non-frequent callers of EMS. However, given the difficulties in recruiting our population of frequent callers, it may also be difficult to recruit similar non-frequent callers of EMS. Another limitation is that participant recruitment was limited to the Hamilton region. However, this study is applicable to other mid-sized cities in both Canada and USA, and provides insight into healthcare systems with universal coverage, a gap in existing literature. Lastly, although the response rate was 41.1% which could be viewed as low, this rate is quite good for a mail-in survey, and at least the age and sex profile of non-responders matched our sample. [79] Additionally, 13 of the non-responders were found after to be deceased, and given the high mortality rate in this population, additional non-responders may have passed away without notifying the research team. However, this may mean that participants with the most significant and multiple comorbidities may not be represented in our study, as they are most likely to have been deceased.

Conclusion

Overall, our study describes high rates of social isolation and poverty, and a low quality of life in frequent callers of EMS compared to Canadian and USA averages, and that subpopulations within the frequent users group of EMS callers were largely similar to those in the frequent ED users group already characterized. Our results are consistent with many studies already conducted in USA, UK, Australia, and China, in both urban and suburban EDs. Due to Canada’s unique health service infrastructure, this study proposes a salutogenic approach to health service provision that is directly applicable to Southern Ontario and other mid-sized Canadian and American cities. Future research may be able to further characterize EMS frequent users, and trial preventative programs as well as social support programs by social workers in order to gain additional insight into interventions that may affect social loneliness, poverty and quality of life in frequent users of EMS and ED. [18, 80]

Abbreviations

BMI: 

Body mass index

ED: 

Emergency department

EMS: 

Emergency Medical Services

QALY: 

Quality adjusted life years

USA: 

United States of America

Declarations

Acknowledgements

We acknowledge Hamilton Paramedic Services for their cooperation and assistance.

Funding

None.

Availability of data and materials

The datasets used and/or analysed during the current study are not publicly available to protect participants’ identifying information, but are available from the corresponding author on reasonable request.

Authors’ contributions

All authors have approved the final article. GA: Coordinated and led all aspects of the study including conception and design, data collection, data analysis and manuscript writing. JL: Conducted data analysis and drafting and revising the manuscript. BM: Data collection. SM: Data collection. MH: Data collection. KC: Data collection. RA: Conception and design of study and data collection.

Ethics approval and consent to participate

This study was approved by the Hamilton Integrated Research Ethics Board. Written consent was obtained from all participants.

Consent for publication

No individual identifying information is published.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Family Medicine, McMaster University, David Braley Health Sciences Centre, 100 Main Street West, 6th Floor, Hamilton, ON, L8P 1H6, Canada
(2)
McMaster University, 100 Main Street West, 6th Floor, Hamilton, ON, L8P 1H6, Canada
(3)
Hamilton Paramedic Services, Hamilton, Canada
(4)
SickKids Centre for Global Child Health, 100 Main Street West, 6th Floor, Hamilton, ON, L8P 1H6, Canada
(5)
Department of Family Medicine, McMaster University, 100 Main Street West, 6th Floor, Hamilton, ON, L8P 1H6, Canada
(6)
Western Sydney University, School of Science and Health, Hamilton, Canada
(7)
University of Western Sydney, Locked Bag 1797, Penrith, NSW, 2751, Australia

References

  1. Lowthian JA, Curtis AJ, Cameron PA, Stoelwinder JU, Cooke MW, McNeil JJ. Systematic review of trends in emergency department attendances: an Australian perspective. Emerg Med J. 2011;28:373–7.View ArticleGoogle Scholar
  2. Office of the Auditor General of Ontario. Annual Report: Land Ambulance Services Section 404. http://www.auditor.on.ca/en/content/annualreports/arreports/en15/4.04en15.pdf.
  3. Hunt KA, Weber EJ, Showstack JA, Colby DC, Callaham ML. Characteristics of frequent users of emergency departments. Ann Emerg Med. 2006;48:1–8.View ArticleGoogle Scholar
  4. Hall MK, Raven MC, Hall J, Yeh C, Allen E, Rodriguez RM, et al. EMS-STARS: Emergency Medical Services “Superuser” Transport Associations: An Adult Retrospective Study. Prehosp Emerg Care. 2015;19:61–7.View ArticleGoogle Scholar
  5. Scott J, Strickland AP, Warner K, Dawson P. Frequent callers to and users of emergency medical systems: a systematic review. Emerg Med J. 2014;31:684–91.View ArticleGoogle Scholar
  6. Knowlton A, Weir BW, Hughes BS, Southerland RH, Schultz CW, Sarpatwari R, et al. Patient demographic and health factors associated with frequent use of emergency medical Services in a Midsized City. Acad Emerg Med. 2013;20:1101–11.View ArticleGoogle Scholar
  7. Oktay C, Cete Y, Eray O, Pekdemir M, Gunerli A. Appropriateness of emergency department visits in a Turkish university hospital. Croat Med J. 2003;44:585–91.PubMedGoogle Scholar
  8. Hjalte L, Suserud B-O, Herlitz J, Karlberg I. Initial emergency medical dispatching and prehospital needs assessment: a prospective study of the Swedish ambulance service. Eur J Emerg Med. 2007;14:134–41.View ArticleGoogle Scholar
  9. Moe J, Bailey AL, Oland R, Levesque L, Murray H. Defining, quantifying, and characterizing adult frequent users of a suburban Canadian emergency department. CJEM. 2013;15:214–26.View ArticleGoogle Scholar
  10. Chan BTB, Ovens HJ. Frequent users of emergency departments. Do they also use family physicians’ services? Can Fam Physician Med Fam Can. 2002;48:1654–60.Google Scholar
  11. Doupe MB, Palatnick W, Day S, Chateau D, Soodeen R-A, Burchill C, et al. Frequent users of emergency departments: developing standard definitions and defining prominent risk factors. Ann Emerg Med. 2012;60:24–32.View ArticleGoogle Scholar
  12. CIHI. Emergency department visits in 2014–2015. Canada: Canadian Institute for Health Information; 2015. https://secure.cihi.ca/free_products/NACRS_ED_QuickStats_Infosheet_2014-15_ENweb.pdf.
  13. South Carolina Public Health Institute. A report on frequent users of hospital emergency departments in South Carolina. South Carolina. USA: SCPHI; 2011.Google Scholar
  14. Weiss SJ, Ernst AA, Miller P, Russell S. Repeat EMS transports among elderly emergency department patients. Prehosp Emerg Care Off J Natl Assoc EMS Physicians Natl Assoc State EMS Dir. 2002;6:6–10.Google Scholar
  15. Jelinek GA, Jiwa M, Gibson NP, Lynch A-M. Frequent attenders at emergency departments: a linked-data population study of adult patients. Med J Aust. 2008;189:552–6.PubMedGoogle Scholar
  16. LaCalle E, Rabin E. Frequent users of emergency departments: the myths, the data, and the policy implications. Ann Emerg Med. 2010;56:42–8.View ArticleGoogle Scholar
  17. Markham D, Graudins A. Characteristics of frequent emergency department presenters to an Australian emergency medicine network. BMC Emerg Med. 2011;11:11–12. https://doi.org/10.1186/1471-227X-11-21.
  18. Skinner J, Carter L, Haxton C. Case management of patients who frequently present to a Scottish emergency department. Emerg Med J. 2009;26:103–5.View ArticleGoogle Scholar
  19. Cook LJ, Knight S, Junkins EP, Mann NC, Dean JM, Olson LM. Repeat patients to the emergency Department in a Statewide Database. Acad Emerg Med. 2004;11:256–63.View ArticleGoogle Scholar
  20. Matsumoto CL, O’Driscoll T, Madden S, Blakelock B, Lawrance J, Kelly L. Defining “high-frequency” emergency department use: Does one size fit all for urban and rural areas? Can Fam Physician Med Fam Can. 2017;63:e395–9.Google Scholar
  21. Doran KM, Raven MC, Rosenheck RA. What drives frequent emergency department use in an integrated health system? National Data from the Veterans Health Administration. Ann Emerg Med. 2013;62:151–9.View ArticleGoogle Scholar
  22. Ku BS, Scott KC, Kertesz SG, Pitts SR. Factors Associated with Use of Urban Emergency Departments by the U.S. Homeless Population. Public Health Rep. 2010;125:398–405.View ArticleGoogle Scholar
  23. Mandelberg JH, Kuhn RE, Kohn MA. Epidemiologic analysis of an urban, public emergency Department’s frequent users. Acad Emerg Med. 2000;7:637–46.View ArticleGoogle Scholar
  24. Langer S, Chew-Graham C, Hunter C, Guthrie EA, Salmon P. Why do patients with long-term conditions use unscheduled care? A qualitative literature review: long-term conditions and unscheduled care: a review. Health Soc Care Community. 2013;21:339–51.View ArticleGoogle Scholar
  25. Byrne M, Murphy AW, Plunkett PK, McGee HM, Murray A, Bury G. Frequent attenders to an emergency department: a study of primary health care use, medical profile, and psychosocial characteristics. Ann Emerg Med. 2003;41:309–18.View ArticleGoogle Scholar
  26. Chambers C, Chiu S, Katic M, Kiss A, Redelmeier DA, Levinson W, et al. High utilizers of emergency health Services in a Population-Based Cohort of homeless adults. Am J Public Health. 2013;103:S302–10.View ArticleGoogle Scholar
  27. Tangherlini N, Villar J, Brown J, Rodriguez RM, Yeh C, Friedman BT, et al. The HOME Team: Evaluating the Effect of an EMS-based Outreach Team to Decrease the Frequency of 911 Use Among High Utilizers of EMS. Prehosp Disaster Med. 2016;31:603–7.View ArticleGoogle Scholar
  28. Ford JG, Meyer IH, Sternfels P, Findley SE, McLean DE, Fagan JK, et al. Patterns and predictors of asthma-related emergency department use in Harlem. Chest. 2001;120:1129–35.View ArticleGoogle Scholar
  29. Griswold SK, Nordstrom CR, Clark S, Gaeta TJ, Price ML, Camargo CA. Asthma exacerbations in North American adults. Chest. 2005;127:1579–86.View ArticleGoogle Scholar
  30. Andrén KG, Rosenqvist U. Heavy users of an emergency department: psycho-social and medical characteristics, other health care contacts and the effect of a hospital social worker intervention. Soc Sci Med 1982. 1985;21:761–70.Google Scholar
  31. Blank FSJ, Li H, Henneman PL, Smithline HA, Santoro JS, Provost D, et al. A descriptive study of heavy emergency department users at an academic emergency department reveals heavy ED users have better access to care than average users. J Emerg Nurs. 2005;31:139–44.View ArticleGoogle Scholar
  32. Zuckerman S, Shen Y-C. Characteristics of occasional and frequent emergency department users: do Insurance coverage and access to care matter? Med Care. 2004;42:176–82.View ArticleGoogle Scholar
  33. Genell Andrén K, Rosenqvist U. Heavy users of an emergency department--a two year follow-up study. Soc Sci Med 1982. 1987;25:825–31.Google Scholar
  34. Lucas RH, Sanford SM. An analysis of frequent users of emergency Care at an Urban University Hospital. Ann Emerg Med. 1998;32:563–8.View ArticleGoogle Scholar
  35. Pane GA, Farner MC, Salness KA. Health care access problems of medically indigent emergency department walk-in patients. Ann Emerg Med. 1991;20:730–3.View ArticleGoogle Scholar
  36. Richardson LD, Hwang U. Access to care a review of the emergency medicine literature. Acad Emerg Med. 2001;8:1030–6.View ArticleGoogle Scholar
  37. Oster A, Bindman AB. Emergency department visits for ambulatory care sensitive conditions: insights into preventable hospitalizations. Med Care. 2003;41:198–207.PubMedGoogle Scholar
  38. Andrén KG. A study of the relationship between social network, perceived ill health and utilization of emergency care: A case-control study. Scand J Soc Med. 1988;16:87–93.View ArticleGoogle Scholar
  39. Geller J, Janson P, McGovern E, Valdini A. Loneliness as a predictor of hospital emergency department use. J Fam Pract. 1999;48:801–4.PubMedGoogle Scholar
  40. Molloy GJ, McGee HM, O’Neill D, Conroy RM. Loneliness and emergency and planned hospitalizations in a community sample of older adults: LONELINESS AND HEALTHCARE USE. J Am Geriatr Soc. 2010;58:1538–41.View ArticleGoogle Scholar
  41. Steptoe A, Owen N, Kunz-Ebrecht SR, Brydon L. Loneliness and neuroendocrine, cardiovascular, and inflammatory stress responses in middle-aged men and women. Psychoneuroendocrinology. 2004;29:593–611.View ArticleGoogle Scholar
  42. Lowthian JA, Jolley DJ, Curtis AJ, Currell A, Cameron PA, Stoelwinder JU, et al. The challenges of population ageing: accelerating demand for emergency ambulance services by older patients, 1995-2015. Med J Aust. 2011;194:574–8.PubMedGoogle Scholar
  43. Rust G. Practical barriers to timely primary care access: impact on adult use of emergency department services. Arch Intern Med. 2008;168:1705.View ArticleGoogle Scholar
  44. Kushel MB, Perry S, Bangsberg D, Clark R, Moss AR. Emergency department use among the homeless and marginally housed: results from a community-based study. Am J Public Health. 2002;92:778–84.View ArticleGoogle Scholar
  45. Locker TE, Baston S, Mason SM, Nicholl J. Defining frequent use of an urban emergency department. Emerg Med J. 2007;24:398–401.View ArticleGoogle Scholar
  46. Gibson NP, Jelinek GA, Jiwa M, Lynch A-M. Paediatric frequent attenders at emergency departments: a linked-data population study: Paediatric frequent attenders at emergency departments. J Paediatr Child Health. 2010;46:723–8.View ArticleGoogle Scholar
  47. Fuda KK, Immekus R. Frequent users of Massachusetts emergency departments: a statewide analysis. Ann Emerg Med. 2006;48:16.e1–8.View ArticleGoogle Scholar
  48. Geurts J, Palatnick W, Strome T, Sutherland KA, Weldon E. Frequent users of an inner-city emergency department. CJEM. 2012;14:306–13.View ArticleGoogle Scholar
  49. CIHI. Health Care in Canada, 2012: A focus on wait times. Canadian institute for health information. https://www.cihi.ca/en/hcic2012_ch2_en.pdf.Google Scholar
  50. Hughes ME, Waite LJ, Hawkley LC, Cacioppo JT. A Short Scale for Measuring Loneliness in Large Surveys: Results From Two Population-Based Studies. Res Aging. 2004;26:655–72.View ArticleGoogle Scholar
  51. Gierveld JDJ, Tilburg TV. A 6-item scale for overall, emotional, and social loneliness: confirmatory tests on survey data. Res Aging. 2006;28:582–98.View ArticleGoogle Scholar
  52. Brcic V, Eberdt C, Kaczorowski J. Development of a Tool to Identify Poverty in a Family Practice Setting: A Pilot Study. Int J Fam Med. 2011;2011:1–7.View ArticleGoogle Scholar
  53. Kleinman RE, Murphy JM, Wieneke KM, Desmond MS, Schiff A, Gapinski JA. Use of a single-question screening tool to detect hunger in families attending a neighborhood health center. Ambul Pediatr. 2007;7:278–84.View ArticleGoogle Scholar
  54. Bansback N, Tsuchiya A, Brazier J, Anis A. Canadian valuation of EQ-5D health states: preliminary value set and considerations for future valuation studies. PLoS One. 2012;7:e31115.View ArticleGoogle Scholar
  55. Statistics Canada. Canadian community health survey - healthy aging (CCHS). 2009. http://www23.statcan.gc.ca/imdb/p2SV.pl?Function=getSurvey&SDDS=5146.
  56. Hamilton seniors isolation impact plan (HSIIP). Project Overview. http://socialisolation.ca.
  57. Purdie FR, Honigman B, Rosen P. The chronic emergency department patient. Ann Emerg Med. 1981;10:298–301.View ArticleGoogle Scholar
  58. Padgett DK, Brodsky B. Psychosocial factors influencing non-urgent use of the emergency room: a review of the literature and recommendations for research and improved service delivery. Soc Sci Med 1982. 1992;35:1189–97.Google Scholar
  59. Cornwell EY, Waite LJ. Measuring social isolation among older adults using multiple indicators from the NSHAP study. J Gerontol B Psychol Sci Soc Sci. 2009;64B(Supplement 1):i38–46.View ArticleGoogle Scholar
  60. Statistics Canada. Families, households and marital status: key results from the 2016 census. 2016. http://www.statcan.gc.ca/daily-quotidien/170802/dq170802a-eng.htm?HPA=1.Google Scholar
  61. Carret ML, Fassa AG, Kawachi I. Demand for emergency health service: factors associated with inappropriate use. BMC Health Serv Res. 2007;7. https://doi.org/10.1186/1472-6963-7-131.
  62. Seguin J, Osmanlliu E, Zhang X, Clavel V, Eisman H, Rodrigues R, et al. Frequent users of the pediatric emergency department. CJEM. 2017;20(3):1–8.View ArticleGoogle Scholar
  63. Keefe J, Andrew M, Fancey P, Hall M. A profile of social isolation in Canada: final report. Mount saint Vincent University; 2006. https://www.health.gov.bc.ca/library/publications/year/2006/keefe_social_isolation_final_report_may_2006.pdf.Google Scholar
  64. Nicholson NR. A review of social isolation: an important but Underassessed condition in older adults. J Prim Prev. 2012;33:137–52.View ArticleGoogle Scholar
  65. Stewart M, Reutter L, Makwarimba E, Veenstra G, Love R, Raphael D. Left out: perspectives on social exclusion and inclusion across income groups. Health Sociol Rev. 2008;17:78–94.View ArticleGoogle Scholar
  66. Statistics Canada. Household food insecurity in Canada statistics and graphics (2011 to 2012). 2012. https://www.canada.ca/en/health-canada/services/nutrition-science-research/food-security/household-food-security-statistics-2011-2012.html.Google Scholar
  67. Statistics Canada. Towards a poverty reduction strategy - a backgrounder on poverty in Canada. 2016. https://www.canada.ca/en/employment-social-development/programs/poverty-reduction/backgrounder.html.Google Scholar
  68. Loignon C, Hudon C, Goulet É, Boyer S, De Laat M, Fournier N, et al. Perceived barriers to healthcare for persons living in poverty in Quebec, Canada: the EQUIhealThY project. Int J Equity Health. 2015;14:4.View ArticleGoogle Scholar
  69. McCusker J, Healey E, Bellavance F, Connolly B. Predictors of repeat emergency department visits by elders. Acad Emerg Med. 1997;4:581–8.View ArticleGoogle Scholar
  70. Salvi F, Morichi V, Grilli A, Giorgi R, De Tommaso G, Dessì-Fulgheri P. The elderly in the emergency department: a critical review of problems and solutions. Intern Emerg Med. 2007;2:292–301.View ArticleGoogle Scholar
  71. Brokaw J, Olson L, Fullerton L, Tandberg D, Sklar D. Repeated ambulance use by patients with acute alcohol intoxication, seizure disorder, and respiratory illness. Am J Emerg Med. 1998;16:141–4.View ArticleGoogle Scholar
  72. Chi CH, Lee HL, Wang SM, Tsai LM. Characteristics of repeated ambulance use in an urban emergency medical service system. J Formos Med Assoc Taiwan Yi Zhi. 2001;100:14–9.PubMedGoogle Scholar
  73. Statistics Canada. Labour force survey: labour market report, November 2017. 2017. https://www.ontario.ca/page/labour-market-report-november-2017.Google Scholar
  74. Lindstrom B. Salutogenesis. J Epidemiol Community Health. 2005;59:440–2.Google Scholar
  75. Antonovsky A. The salutogenic model as a theory to guide health promotion. Health Promot Int. 1996;11:11–8.View ArticleGoogle Scholar
  76. Antonovsky A. Unraveling the mystery of health: how people manage stress and stay well. 1st ed. San Francisco: Jossey-Bass; 1987.Google Scholar
  77. Cockrell KR. Exploring rural paramedics’ capacity for utilising a salutogenic approach to healthcare delivery; 2018.Google Scholar
  78. Cockrell KR. Exploration of rural paramedics’ capacity for utilising a salutogenic approach to health care delivery: a mixed methods study; 2017.Google Scholar
  79. Shih T-H, Fan X. Comparing response rates in e-mail and paper surveys: a meta-analysis. Educ Res Rev. 2009;4:26–40.View ArticleGoogle Scholar
  80. Brydges M, Denton M, Agarwal G. The CHAP-EMS health promotion program: a qualitative study on participants’ views of the role of paramedics. BMC Health Serv Res. 2016;16. https://doi.org/10.1186/s12913-016-1687-9.

Copyright

© The Author(s). 2019

Advertisement