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Abstract

  1. Top of page
  2. AbstractResumen
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. References
  9. Supporting Information

Objectives

Increases in regional emergency department (ED) efficiencies might be obtained by shifting patients to less crowded EDs. The authors sought to determine factors associated with a patient's decision to choose a specific regional ED. Based on prior focus group discussions with volunteers, the hypothesis was that distance to a specific ED and perceived ED wait times would be important.

Methods

A cross-sectional survey was developed using qualitative focus group methodology. The resulting survey was composed of 17 questions relating to patient decisions in choosing a specific ED and was administered in each of six EDs in a single urban Canadian health region at all hours of the day. Ambulatory patients with a Canadian Triage and Acuity Scale (CTAS) level 3 to 5 and aged ≥19 years were surveyed. The primary outcome was the proportion of patients whose main motivation for attending a specific ED was either distance traveled to reach the ED or perceived ED waiting time. Multivariable logistic regression was performed to assess factors influencing both of these reasons.

Results

A total of 757 patients were approached and 634 surveys (83.8%) were completed. Distance from the ED (named by 44.0% of respondents as their primary reason) and perceived ED wait times (9.3%) were the main motivations for patients to attend a specific ED. Multivariable analysis of factors associated with choosing distance revealed that ED distance < 10 km (adjusted odds ratio [OR] = 2.20, 95% confidence interval [CI] = 1.45 to 3.33; p = 0.001) and age ≥ 60 years (adjusted OR = 1.58, 95% CI = 1.12 to 2.26; p = 0.04) were significant in choosing a particular ED. Multivariable analysis of factors influencing wait times demonstrated that having a painful complaint (adjusted OR = 1.42, 95% CI = 1.05 to 1.98; p = 0.047) and age < 60 years (OR = 1.47, 95% CI = 1.02 to 2.14; p = 0.049) were significant in choosing a particular ED.

Conclusions

In a multicenter survey of patients from an urban health region, distance to a specific ED and perceived ED wait times were the most important reasons for choosing that ED. Younger patients and those with painful conditions appear to place greater priority on wait times.

Resumen

Encuesta Regional para Determinar los Factores que Influyen en un Paciente en la Elección de un Determinado Servicio de Urgencias

Objetivos

El incremento de la eficiencia en un servicio de urgencias (SU) regional puede alcanzarse mediante el desplazamiento de pacientes a SU menos saturados. El objetivo fue determinar los factores asociados con la decisión del paciente a la hora de elegir un determinado SU regional. En base a las opiniones previas de grupos de voluntarios, la hipótesis fue que podría ser importante la distancia a un SU específico y la percepción de los tiempos de espera del SU.

Método

Se desarrolló una encuesta transversal mediante una metodología cualitativa basada en grupo. La encuesta se componía de 17 preguntas relacionadas con las decisiones del paciente en la elección de un determinado SU y se administró a cualquier hora del día en cada uno de los seis SU de una única región sanitaria urbana en Canadá. Se realizó la encuesta a pacientes ambulatorios de 19 o más años con un nivel de gravedad de 3 a 5 según la escala de triaje canadiense. El resultado principal fue el porcentaje de pacientes cuya principal motivación para acudir a un determinado SU fue la distancia recorrida hasta el SU o la percepción del tiempo de espera en el SU. Se realizó un análisis multivariable mediante regresión logística para evaluar los factores que influían en estas razones.

Resultados

Se realizó la encuesta a 757 pacientes y 634 (83,8%) la completaron. Las principales motivaciones de los pacientes para acudir a un determinado SU fueron la distancia al SU (se enumeró como su razón principal por el 44% de los encuestados) y los tiempos de espera del SU percibidos (por el 9,3%). El análisis multivariable de los factores asociados con la elección de la distancia mostró que una distancia al SU < 10 km (OR ajustada 2,20, IC 95% = 1,45 a 3,33; p = 0,001) y una edad ≥ 60 años (OR ajustada 1,58, IC 95% = 1,12 a 2,26; p = 0,04) fueron significativas a la hora de elegir un determinado SU. El análisis multivariable de los factores que influyen en los tiempos de espera mostraron que tener dolor como motivo de consulta (OR ajustada 1,42, IC 95% = 1,05 a 1,98; p = 0,047) y una edad <60 años (OR 1,47, IC 95% = 1,02 a 2,14; p = 0,049) fueron significativos a la hora de elegir un determinado SU.

Conclusiones

En una encuesta multicéntrica de pacientes de una región sanitaria urbana, la distancia a un determinado SU y los tiempos de espera percibidos son las razones más importantes para la elección de dicho SU. Los pacientes jóvenes y aquéllos con procesos dolorosos parecen centrar la prioridad en los tiempos de espera.

Emergency department (ED) crowding has been associated with a variety of deleterious outcomes.[1-25] Although strategies such as overcapacity protocols,[26, 27] orders-at-triage for common complaints,[28, 29] and patient assessment in nontraditional areas[30] have been proposed to attenuate crowding, such solutions deal with patients who are already present in the ED. In addition, these strategies have typically been explored in single centers.

In larger urban centers, ambulatory patients often have a choice of more than one ED to attend. A Canadian survey demonstrated variability in crowding both among different EDs in a specific geographic areas[4] and at various times of the day.[31] “Smoothing” such system inefficiencies by directing patients to less busy EDs or to an ED at a less busy time of day could help alleviate crowding. Although asking “why” a patient went to an ED has been investigated,[32] the decisions ambulatory ED patients make in selecting a specific ED to attend—given a choice of centers—have not been explored. This may be relevant in understanding if the way patients use EDs is modifiable.

Through a patient survey, we sought to explore the choices that an ambulatory patient makes regarding the decisions to attend a specific ED when several EDs are available. Based on a pilot survey, our hypothesis was that the two most important factors influencing this choice were 1) distance to travel to an ED and 2) wait times to see a physician. We also wanted to explore the other reasons influencing both of these factors.

Methods

  1. Top of page
  2. AbstractResumen
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. References
  9. Supporting Information

Study Design and Population

This was a cross-sectional, face-to-face survey interviewing ambulatory patients who attended each of six EDs in the Vancouver Coastal Health Region (VCHR) from February 25 to April 29, 2010 (see Figure 1 for a map of the VCHR detailing hospital distribution; Data Supplement S1, available as supporting information in the online version of this paper, illustrates the characteristics of each institution). All hospitals are staffed exclusively by board-certified emergency physicians (EPs) and are affiliated with the University of British Columbia; approximately 800 medical students and residents are taught in the EDs annually. The research ethics board of the university and all constituent hospitals approved this study.

image

Figure 1. Map of the Vancouver Coastal Health Region detailing hospital distribution.

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Research assistants invited ambulatory patients aged 19 years or greater to participate via convenience sampling. Patients with a Canadian Triage and Acuity Scale (CTAS) level 3 through 5 were eligible (please see Data Supplement S2, available as supporting information in the online version of this paper, for an explanation of CTAS). Patients who were transported via emergency medical services (ground ambulance, helicopter, or fixed-wing transport), those who did not live or work within the health region, those unwilling or unable to provide informed consent, those who had debilitating communication difficulties, and those whose behavior might have threatened the safety of the interviewer were excluded from the survey. The latter two criteria included patients who were intoxicated or severely agitated.

Survey Content and Administration

Prior to survey development, a literature review was performed and no psychometrically tested questionnaires exploring the objectives of this study were identified. We used a qualitative focus group methodology to enhance the understanding of why a patient chooses a specific ED.[33] As part of a larger community survey to understand how and why patients use EDs, and how information about EDs could be distributed to patients, focus group participants were chosen based on their response to mail solicitation to participate after a recent regional ED visit within the preceding 3 months. Focus group recruitment, composition, and discussion themes can be seen in Data Supplement S3 (available as supporting information in the online version of this paper).

The 38 participants in the focus group were considered to have consented by accepting the invitation, and no financial compensation was provided. Patients identified several factors affecting their choice of ED. They considered patient distance to the ED (a quantifiable number; although “time traveled to ED” would be more accurate, this is variable based on conditions such as traffic, weather, and road construction) and perceived wait times to see a physician as the most important factors. For this study, “wait times” are considered the time from a patient's registration at the triage desk until the patient's formal assessment by a physician, medical student, or resident, which is denoted on the chart or on an electronic sign-in board, depending on the hospital. After this assessment, management decisions, including investigations and disposition, are commonly made. None of the centers has a “triage physician” who performs a cursory assessment of the patient, orders some investigations, and then passes the patient to a second physician who provides the formal assessment. Participants who self-identified as having chronic illness (15 of 38) felt that their previous experiences at the ED—defined as the perceived quality of clinical skill, staff courtesy, and morale—were important and did not rank wait times as highly. Other priorities included the perception of the hospital as appropriate to their specific health needs or having a specific specialist available.

Using the focus group information, specific wording for survey questions and appropriate measure tools were developed. The survey was tested on a pilot sample of 20 patients and questions were revised as necessary (see Data Supplement S4, available as supporting information in the online version of this paper, for the survey). The survey contained three broad groups of questions. The first section covered patient demographics and the distance traveled to come to the ED. The second section queried the factors influencing the choice of ED. Patients were asked to rank the factors that influence their usual choice of hospital ED from a list of 14 factors. The importance of wait times and distance were assessed on a five-point Likert scale. To test the influence of painful conditions on patient tolerance for wait times, the final section contained two hypothetical scenarios regarding abdominal pain and an ankle injury; patients were queried as to how long they would be willing to wait in an ED for treatment; this was assessed on a seven-point Likert scale.

Sample Size

We surveyed all sites and chose the survey sample size for each ED based on its annual patient volume. To allow for a 95% confidence interval (CI) with a precision of ±4% around a proportion of respondents who rate distance to ED and wait times as “extremely” or “very important” in their decisions to choose a specific ED, we required 625 surveys. For this total, we sought to obtain a minimum of 150 surveys each from the large centers, 110 surveys from the medium sites, and 50 surveys from the smaller sites.

Data Collection

Trained research assistants conducted the structured face-to-face interviews with patients. As the questionnaire had three pages including ten questions with single answers, and two questions with multiple possible answers, we felt that in-person interviews would maximize the number of completed survey; many of the important questions were toward the end of the questionnaire. CTAS level (triage level 3 through 5) and age (> 19 years) were identified from either an ED census board or the ED staff with access to patient information. Patients were surveyed after their initial triage assessments were complete, and while the patients were in the waiting room awaiting bed placement or to be seen by the physician. If there were no patients in the waiting room, those patients with the shortest length of stay were surveyed. Informed consent was implied if the patient agreed to participate in the survey. When available, and permission given, patient family or friends were used as translators if the patient was unable to communicate in English.

Respondents were retrospectively classified as having a painful condition based on their COT (Complaint Oriented Triage) electronic presenting complaint descriptor.[34] Two EPs (EG, RS), blinded to patient responses, classified each respondent's COT descriptor as potentially “painful” or “not painful”; 15% of patients were selected by a random number generator and both physicians independently classified patients to obtain a kappa value for interobserver reliability. All data were double entered into an Excel database (Microsoft Corp., Redmond, WA) for analysis.

The primary outcome was the proportion of patients choosing distance from an ED or perceived ED wait time as the most important factors in making a decision on which ED to attend. The secondary outcome was a multivariable logistic regression analysis of the factors contributing to patient beliefs regarding the importance of distance and perceived ED wait times.

Data Analysis

Descriptive statistics were calculated for each variable: proportions for dichotomous variables, means with standard deviations (SDs) for continuous variables that were assumed to be normally distributed, and medians with interquartile ranges (IQRs) for continuous variables that were nonnormally distributed. Although the importance of wait times and distance were assessed via a five-point Likert scale, these answers were dichotomized into “important” (if the patient felt that they were “extremely” or “very important”) and nonimportant (if the patient gave any other response) for both variables.

For each of the two outcomes of interest—distance and wait times—we compared the proportion of respondents rating these as very important by various predictor variables. For the dichotomous predictor variables we used chi-square with one degree of freedom. For predictor variables with more than two groups (CTAS level and hospital) we used Kruskal-Wallis analysis of variance. STATISTICA (Statsoft, Tulsa, OK) was used for these analyses.

Multivariate logistic regression was used to establish the relative contribution of each independent variable associated with importance of each outcome. Model development was based on a univariable p-value of each predictor of 0.2 or less with the outcome of interest. These variables were then assessed using a backward-stepwise procedure (p-to-remove > 0.15). EGRET software (Cytel Corp., Cambridge, MA) was used for these analyses. Specific two-way interactions between distance traveled to ED and age, and painful complaint and age, were investigated in separate multivariate logistic regression models. These interactions were investigated specifically, as we hypothesized that age or having a painful condition would modify patients' importance ratings for distance traveled to hospital. Adjusted odds ratios (ORs) and 95% CIs are reported for each variable, as it is associated with rating the outcome as extremely or very important. Fit of models was assessed by the Hosmer-Lemeshow goodness-of-fit statistic.

Results

  1. Top of page
  2. AbstractResumen
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. References
  9. Supporting Information

From July 1 to August 31, 2010, a total of 757 patients were approached. A total of 123 patients were ineligible to participate (35 arrived by ambulance, 40 were CTAS level 2), refused to participate (32), or did not complete the survey (16), leaving 634 surveys (83.8%) for analysis. Table 1 illustrates characteristics of survey participants. Patients ranked the most important factors in ED selection as follows: 279 (44.0%, 95% CI = 40.1% to 48.0%) indicated that distance to an ED was the most important factor affecting ED selection, 59 (9.3%, 95% CI = 7.2% to 11.9%) indicated that anticipated ED wait times were the most important factor, and 52 (8.2%, 95% CI = 6.2% to 10.6%) chose the location affiliated with their specialists as the most important factor. A total of 340 patients (53.6%) had painful complaints based on triage coding; the physician inter-rater reliability for distinguishing between “painful” or “nonpainful” complaint based on triage coding was κ = 0.81 (95% CI = 0.69 to 0.89).

Table 1. Characteristics of 634 ED Survey Respondents
CharacteristicsN (%) of patients
  1. CTAS = Canadian Triage and Acuity Scale; LGH = Lions Gate Hospital; MSJ = Mount St. Joseph's Hospital; RH = Richmond Hospital; SPH = St. Paul's Hospital; UBC = University of British Columbia Hospital; VGH = Vancouver General Hospital.

Sex
Female327 (51.6)
Male307 (48.4)
Age, yr
19–29157 (24.8)
30–39107 (16.9)
40–49122 (19.2)
50–5994 (14.8)
60–6981 (12.8)
70–7945 (7.1)
≥8028 (4.4)
Hospital
LGH92 (14.5)
MSJ56 (8.8)
RH100 (15.8)
VGH147 (23.2)
UBC53 (8.4)
SPH186 (29.3)
Mode of arrival
Car396 (62.4)
Taxi65 (10.3)
Walking106 (16.7)
Bus (public transport)67 (10.6)
Distance traveled to ED, km
<5346 (54.6)
5–10176 (27.8)
10–2076 (12.0)
20–3018 (2.8)
>3018 (2.8)
Complaint descriptor
Cardiovascular43 (6.8)
Gastrointestinal129 (20.3)
Neurologic 41 (6.5)
Orthopedic142 (22.4)
Skin77 (12.1)
Other202 (31.9)
CTAS level
3225 (35.5)
4346 (54.6)
563 (9.9)

Association of Various Factors With ED Wait Time

When patients were asked if wait times would influence their choice of ED if they had a choice between their typical ED and an ED with a shorter wait time, 366 respondents (57.8%, 95% CI = 53.2% to 61.2%) stated that wait time would influence their choice of ED. Patients were asked to rank the importance of wait times on a Likert scale, and 414 respondents (65.3%, 95% CI = 61.8% to 69.4%) felt that wait times were “extremely important” or “very important.” There were two hypothetical scenarios where patients were asked to choose a reasonable length of time to wait for care. For the abdominal pain/nausea (CTAS level 3) scenario, patients were willing to wait for care a median of 30 to 60 minutes (IQR = 0–30 minutes to 1–2 hours). For the ankle sprain (CTAS 4) scenario, median time was 1 to 2 hours (IQR = 0–30 minutes to 2–4 hours). In both cases, the 90th percentile for wait time tolerance was 6 to 8 hours.

Results from the univariable analysis are in Table 2; only age < 60 years (p = 0.02) was significantly associated with placing a high value on wait times. Other factors, including sex, having an orthopedic or pain-related complaint, being advised to go the ED, the specific hospital, the distance traveled, the CTAS level (each of levels 3 to 5), and the time elapsed prior to the survey were not significant predictors of the importance of ED wait times. Table 3 illustrates the multivariable analysis, in which both age < 60 years and having a painful presenting complaint were significant. Fit of this model was adequate (Hosmer-Lemeshow chi-square [df = 2] = 1.29; p = 0.55).

Table 2. Proportion of Survey Respondents in Select Variable Categories Who Chose “Extremely” or “Very” Important for Query on Wait Time Importance, Univariable Analysis
VariableTotal Nn (%)Statistic Valueap-value
  1. a

    Statistic = chi-square with 1 degree of freedom (df) for all dichotomous variables; Kruskal-Wallis H test for variables with > 2 groups (CTAS [df = 2] and hospital [df = 6]).

  2. CTAS = Canadian Triage and Acuity Scale; LGH = Lions Gate Hospital; MSJ = Mount St. Joseph's Hospital; RH = Richmond Hospital; SPH = St. Paul's Hospital; UBC = University of British Columbia Hospital; VGH = Vancouver General Hospital;

  3. b

    Downtown = VGH and SPH; not downtown = RH, LGH, MSJ, and UBC.

Sex
Female327218 (66.7)1.500.22
Male307191 (62.2)
Age, yr
<60480324 (67.5)5.280.022
≥6015489 (57.8)
Ortho complaint
Yes14288 (62.0)0.600.44
No492324 (65.9)
Pain complaint
Yes340233 (67.6)2.980.08
No294181 (61.6)
Location surveyed
Care space344216 (62.8)0.050.82
Waiting room290176 (60.7)
Advised to go to ED
Yes225148 (65.8)0.030.85
No409259 (63.3)
Hospital
LGH9262 (67.3)3.20.66
MSJ5635 (62.5)
RH10071 (71.0)
VGH14790 (61.3)
UBC5332 (60.3)
SPH186124 (66.7)
Distance traveled, km
<10522345 (66.1)0.820.37
≥1011269 (61.6)
Hospital location
Downtownb333214 (64.3)0.330.56
All others301200 (66.4)
CTAS level
3225145 (64.4)0.780.49
4346219 (63.3)
56333 (52.4)
Time elapsed prior to survey, hours
>1342217 (63.5)1.360.24
≤1292192 (65.7)
Table 3. Importance of Wait Times in Multivariable Analysis
Candidate VariablesAdjusted OR95% CIp-value
Pain (referent: no pain)1.421.05–1.980.047
Age (referent ≥ 60 yr)1.471.02–2.140.049
Sex: not in model   

Association of Various Factors With Distance

A total of 384 patients (60.6%, 95% CI = 57.2% to 64.8%) felt that distance from the ED was “extremely” or “very important.” Table 4 illustrates the univariable analysis of factors in patients who felt that distance was “important” in their decisions to attend specific EDs. Significant factors included traveling > 10 km and visiting a downtown hospital (as opposed to community/peripheral hospital).

Table 4. Proportion of Survey Respondents in Select Variable Categories Who Chose “Extremely” or “Very” Important for Query on Distance Importance, Univariable Analysis
Variable N n (%)Statistic Valueap-value
  1. a

    Statistic = chi-square with 1 degree of freedom (df) for all dichotomous variables; Kruskal-Wallis H test for variables with > 2 groups (CTAS [df = 2] and Hospital [df = 6]).

  2. CTAS = Canadian Triage and Acuity Scale; LGH = Lions Gate Hospital; MSJ = Mount St. Joseph's Hospital; RH = Richmond Hospital; SPH = St. Paul's Hospital; UBC = University of British Columbia Hospital; VGH = Vancouver General Hospital.

  3. b

    Downtown = VGH and SPH; not downtown = RH, LGH, MSJ, and UBC.

Sex
Female327200 (61.2)0.480.49
Male307180 (58.6)
Age, yr
<60480298 (62.1)3.580.058
≥6015483 (53.9)
Ortho complaint
Yes14278 (54.9)1.730.19
No492302 (61.4)
Pain complaint
Yes340199 (58.5)0.780.38
No294181 (61.5)
Location surveyed
Care space344202 (58.7)0.510.47
Waiting room290159 (54.8)
Advised to go to ED
Yes225125 (55.5)3.670.055
No409259 (63.3)
Hospital
LGH9262 (67.4)17.60.0035
MSJ5634 (60.7)
RH10069 (69.0)
VGH14769 (46.9)
UBC5331 (58.5)
SPH186119 (64.0)
Distance traveled, km
<10522334 (64.0)14.44<0.001
≥1011250 (44.6)
Hospital location
Downtownb333188 (56.4)4.960.03
All others301196 (65.1)
CTAS level
3225132 (58.7)0.560.72
4346199 (57.5)
56336 (57.1)
Time elapsed prior to survey, hours
>1342198 (57.9)1.190.28
≤1292182 (62.3)

In multivariable analysis, age < 60 years, traveling < 10 km, or traveling to a downtown hospital were positively associated in patients who thought that the distance to travel to the ED was important in deciding which ED to visit (Table 5). Two-way interactions between distance to ED and age, and having a painful complaint and age, were not significantly associated with placing a higher value on wait times (all p values > 0.2). Fit of this model was adequate (Hosmer-Lemeshow chi-square [df = 4] = 5.21; p = 0.29).

Table 5. Importance of Distance in the Multivariable Analysis
Candidate VariablesAdjusted OR95% CIp-value
  1. LGH = Lions Gate Hospital; MSJ = Mount St. Joseph's Hospital; RH = Richmond Hospital; SPH = St. Paul's Hospital; VGH = Vancouver General Hospital; UBC = University of British Columbia Hospital.

  2. a

    Downtown = VGH and SPH; not downtown = RH, LGH, MSJ, and UBC.

Downtown (peripheral)a0.650.46–0.910.011
Age (referent: ≥ 60 yr)1.581.12–2.260.041
Orthopedic complaint (referent: nonortho complaint)0.680.46–1.10.09
Distance traveled to ED (referent: ≥10 km)2.21.45–3.330.0011
Advised to go to ED (referent: not advised to go to ED)0.760.54–1.070.12

Discussion

  1. Top of page
  2. AbstractResumen
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. References
  9. Supporting Information

In our survey of 634 ambulatory patients across six EDs in a single urban Canadian health region, 44.0% stated that proximity to an ED was the main reason for choosing that ED, while 9.3% claimed that perceived wait times were the most important factor. Other issues, including quality of care, were cited by fewer than 10% of respondents as being the most important factor in their decision. This suggests that either patients value time to care more than quality of care or, alternatively, there is a perception of relative perceived parity in ED care provided across the region.

A significant number of patients were willing to wait more than 30 to 60 minutes in an ED for care of abdominal pain and more than 1 to 2 hours for care of an ankle sprain; 10% of patients were willing to wait 6 to 8 hours for care in both scenarios. This suggests that, in our setting, wait times are a relatively inelastic driver of patient behavior, and there would likely need to be significant differences in time to ED care between sites for patients to change their ED preferences.

Patients placed more value on distance traveled to the ED if they were surveyed at the four peripheral hospitals (which are widely scattered) and not at the two large downtown hospitals (which are in close proximity to each other). In our urban health region, this may indicate that attempts to shift patients between EDs may not be as effective for peripheral or isolated hospitals.

Older patients appear to have a greater tolerance for wait times. They may be less mobile or less willing to try an alternative ED, they may have chronic conditions treated by specialists at their particular EDs, or they may have had previous positive ED experiences. In the initial patient focus groups, previous hospital experience was considered a priority for ED choice. On the other hand, patients with painful presenting complaints appeared to value wait times more than patients whose did not have painful complaints, and this result was consistent across age.

Prior work has demonstrated that Canadian ED crowding is more likely to occur in EDs with >50,000 annual visits, those serving populations of at least 150,000, and university-affiliated hospitals or trauma centers. Furthermore, patient wait times varied not only by patient severity but also by the volume of patients in EDs at the time of the visit and by ED type—specifically, patients with less severe health conditions visiting lower volume EDs had shorter waiting times when compared with higher volume EDs.[4] This demonstrates that asymmetrical regional ED use does exist, leading to wait time variability between sites, and potential ED crowding. It is acknowledged that lack of inpatient care spaces—not ambulatory patients—is the primary cause of ED overcrowding.[13] However, “smoothing” the patient input variability by encouraging ambulatory patients to avoid already crowded EDs in favor of less crowded EDs might result in some overall improvement in regional ED wait times and efficiency.

With approximately 85% of ED patients not arriving by ambulance[35] (and therefore having a choice in which ED to attend), it may be appropriate to develop tools to help patients make informed decisions regarding the EDs they choose. While the distance an ambulatory patient travels to an ED is an inflexible variable, patient wait times appear to be variable, and conveying this information to a potential patient may influence him or her to choose another ED should the first choice have unacceptably long wait times.

Although a relatively novel concept, providing real-time ED wait times has been tried in some jurisdictions.*Patients may support this idea: Shaikh and coworkers[36] surveyed 375 nonurgent ED patients and found that 63% would prefer to have wait times displayed while in the ED; this study did not inquire whether patients would make use of an online or remote electronic wait time tool. In a two-ED community that provided ED wait times for each site online, the site with the shorter wait time had an increased probability of being chosen by nonurgent patients. However, there were only 18 to 39 website “hits” per day, indicating that few potential patients made use of this information.[37] Dissemination of this information to the emergency medical services system in the Calgary Health region was found to reduce the proportion of time each of the three hospitals spent in ambulance diversions.[38]

Limitations

  1. Top of page
  2. AbstractResumen
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. References
  9. Supporting Information

Only ambulatory patients from six regional EDs in a single urban Canadian health region were interviewed. While questions for the survey were developed from small focus groups where the median age was 65 years and there was a substantial burden of chronic illness, survey participants had a median age of 43 years, presumably with a lower rate of chronic illness, and this could affect responses related to wait time tolerance or specialist availability for chronic conditions. Although the questionnaires were conducted face-to-face to maximize completed surveys, patients self-reported data, and their answers may have been affected by recall or social desirability biases. A convenience sampling mechanism was used; ambulatory patients with mental health or substance misuse issues were likely underrepresented. The same caveat applies to higher-acuity (CTAS 1 or 2) or elderly patients, who tend to arrive more often by ambulance, and patients with communication barriers. Patients were more often interviewed during the busy daytime hours, and the motivations for patients attending a specific ED outside those hours may not have been adequately investigated. As Canada has single-payer universal health care coverage and patients have their choice of any ED, questions regarding finances and health insurance were not included, and these may substantially affect responses in other settings. For example, patients in other multi-ED regions might choose to attend a specific ED based on whether they were insured at that specific ED; this factor might reduce the importance of distance and wait times that we encountered in our setting. Patients in different environments might be less tolerant of longer wait times or distance to an ED. Finally, the development of the multivariate models was exploratory in nature, and this model may require validation in other settings.

Conclusions

  1. Top of page
  2. AbstractResumen
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. References
  9. Supporting Information

In a multicenter survey of patients from an urban health region, distance to a specific ED and perceived ED wait times are the most important reasons for choosing that ED. Younger patients and those with painful conditions appear to place greater priority on wait times.

  1. 1

    Editor's note: For example, patient load information (though not wait times in minutes) for all emergency departments in New South Wales, Australia, is available in real time on the internet: the number of patients triaged and waiting to be seen, the number of patients typically arriving in the current 2-hour block, and the number of available treatment spaces. The numbers of patients waiting at several other nearby EDs is also shown, and potential patients can click on these for full data (www.emergencywait.health.nsw.gov.au/hospitals/rted/index.asp).

References

  1. Top of page
  2. AbstractResumen
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. References
  9. Supporting Information
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Supporting Information

  1. Top of page
  2. AbstractResumen
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. References
  9. Supporting Information
FilenameFormatSizeDescription
acem12063-sup-0001-DataSupplementS1.pdfapplication/PDF28KData Supplement S1. Characteristics of the emergency departments and hospitals.
acem12063-sup-0002-DataSupplementS2.pdfapplication/PDF28KData Supplement S2. Canadian Triage and Acuity Scale.
acem12063-sup-0003-DataSupplementS3.pdfapplication/PDF29KData Supplement S3. Patient discussions for survey development.
acem12063-sup-0004-DataSupplementS4.pdfapplication/PDF90KData Supplement S4. Survey of factors influencing patient choices in selecting a particular emergency department.

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