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Determinants of patient satisfaction in an Australian emergency department fast-track setting
  1. Michael M Dinh1,
  2. Nicholas Enright2,
  3. Andrew Walker1,
  4. Ahilan Parameswaran3,
  5. Matthew Chu4
  1. 1Emergency Department, Registrar Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia
  2. 2Sydney Medical School, Sydney University, Sydney, New South Wales, Australia
  3. 3Concord Hospital, New South Wales, Australia
  4. 4Emergency Department, Canterbury Hospital, Sydney, New South Wales, Australia
  1. Correspondence to Dr Michael M Dinh, Emergency Department, Royal Prince Alfred Hospital, Missenden Road, Camperdown, NSW 2050, Australia;{at}


Objectives To describe the relationship between waiting time and patient satisfaction, and to determine predictors of overall care rating in an emergency department (ED) fast-track setting.

Methods A convenience sample of patients triaged to a fast-track unit were surveyed. Patient satisfaction was scored using a validated survey instrument, as well as a single overall care rating (poor to excellent). Median satisfaction scores were compared between each incremental hour of waiting time. Bivariate analysis was conducted between those who waited 1 h or less, and those who waited longer. Ordered logistic regression was used to determine predictors of improved overall care rating.

Results 236 patients completed surveys (response rate of 74%). Of these, 84% rated their care as either very good or excellent. There was a linear decrease in median satisfaction scores for each incremental hour of waiting time associated with half the odds of higher overall care rating after adjusting for presenting problem type, triage category, and treating clinician type (OR 0.53 95% CI 0.37 to 0.75 p<0.001). English language (OR 2.43 95% CI 1.33 to 4.42 p=0.004) and initial consultation by a nurse practitioner (NP) (OR 1.81 95% CI 1.03 to 3.31 p=0.038) were also found to be significant predictors of improved overall care rating.

Conclusions Waiting time was found to be highly predictive of patient satisfaction in an emergency fast-track unit with English language and NPs also associated with improved overall care rating. Future measures to improve patient satisfaction in fast-track units should focus on these factors.

  • emergency care systems, primary care

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Emergency department (ED) ‘fast-track’ units were developed in Australia to address the needs of the increasing number of ED patients presenting with low-complexity problems.1 These are functionally distinct units within EDs that allow patients with low-complexity problems to be streamed from triage, and seen separately from more acute problems. This concept was underlined by the Garling Inquiry,2 into acute care at public hospitals in New South Wales, Australia, which recommended alternative models of care for ED waiting room patients.

Several studies have pointed to improved ED efficiency and patient waiting times after implementing fast-track units.1 ,3–6 To date, there are no studies evaluating patient-reported outcomes as a measure of quality of care in fast-track units.

The objective of the present study was to determine the predictors of improved patient satisfaction in a fast-track unit, and describe the relationship between waiting time and patient satisfaction. Such information is useful for departments seeking to improve quality of service delivery in fast-track units, and to ensure that changes in the way ED services are delivered in Australia are consistent with the needs of the community.


Study design

This was a secondary analysis of a prospective study of nurse practitioners (NP) in this fast-track unit. The prospective study was conducted between April 2010 and April 2011.

Study setting

The study was conducted in an ED of an inner city district-level teaching hospital in Sydney, New South Wales. The ED sees 30 000 patients annually with 43% of people from non-English speaking backgrounds.7 The fast-track unit was opened in 2008, and staffed by one NP and doctors ranging in experience from emergency physicians to resident medical officers. At the time of the study, this was one of only two fast-track units in New South Wales with a full-time nurse practitioner.

Study population

The population studied was a convenience sample of patients presenting between 08:00 and 22:30 h. Patients were only enrolled on days where the fast-track unit was staffed with both NP and emergency doctors (DR), and when study investigators were available to supervise the study. Inclusion criteria were age between 16 years and 70 years, triage category four or five, and meeting usual fast-track criteria (normal mental state and vital signs, no significant medical comorbidities, and presenting with low-complexity problems) for this ED. Exclusion criteria included significant cognitive impairment, inability to provide reliable history with no interpreter available for consultation, and those re-triaged as requiring more urgent medical attention. Patient eligibility was determined attriage, and written consent was obtained from the patient at triage by the triage nurse. Patients with incomplete satisfaction surveys were included in the analysis.

Study procedure

Patients who were enrolled by the triage nurse into the study were invited to complete a patient satisfaction survey instrument at the completion of fast-track consultation. As part of a concurrent study, patients were randomised with a sealed envelope preallocated into initial assessment and treatment by an emergency nurse practitioner (ENP), or initial assessment and treatment by any DR. The envelope with study group allocation was opened by the triage nurse and the patient informed of group allocation. The single ENP in this study was a qualified Australian NP with 7 years clinical experience who worked independently, assessing and managing patients within the fast-track unit, and was able to consult, where appropriate, with senior medical staff in the ED. ED doctors who worked in the fast-track unit ranged from resident medical officers (postgraduate years 2–4), emergency registrars, career medical officers and emergency physicians.

Demographic data, such as age, sex, nominated general practitioner, occupation and primary language spoken at home were collected at time of survey completion. Presenting problem details (musculoskeletal versus other presenting problems), time of consultation, and waiting times were collected using the ED patient tracking system (FirstNet, Cerner Kansas City USA). Waiting time was defined as the time in minutes from triage to the consultation time indicated on the patient tracking system. Patients were asked to complete the survey in private and submit it in one of two closed boxes located at the entrance to the ED and fast-track waiting rooms.

Study outcomes

The endpoints were patient satisfaction scores and overall care rating at the point of discharge. Patient satisfaction scores were measured on a self-administered satisfaction survey instrument completed prior to ED discharge. Total satisfaction score was a combined score of five domains (‘how would you rate the following aspects of your care today? Completeness of care, courtesy and politeness, explanation and advice, waiting time, understanding of discharge instructions), each rated on a five-point Likert scale (poor to excellent), giving a potential maximum total satisfaction score of 25. This was validated in a previous study of ED patient satisfaction and quality of care.8 ,9 A separate overall care rating (‘How would you rate your overall care in the ED today?’) was scored on a single five-point item (poor to excellent).

Statistical analysis

Descriptive statistics were used to compare demographic and other variables between those waiting for less than 60 min and those waiting longer than 60 min, based on current recommended Australasian Triage Scale (available at waiting time guidelines for triage category four patients (semiurgent). Given the skewed distribution of outcomes, these were expressed with medians and IQR. The hypothesis of this study was that increasing waiting time was associated with lower satisfaction scores and overall care ratings. Box whisker plots were used to describe the overall effect of each incremental 60 min waiting time intervals on satisfaction scores, with Kruskall–Wallis tests used to compare median satisfaction scores. To obtain adjusted odds of higher overall care ratings, an ordered logistic regression was used, assuming a constant relationship between each incremental increase in overall care rating. Cronbach's α was used to assess internal consistency of the satisfaction survey instrument with a threshold value of 0.70 used to define adequate internal consistency. All data was analysed on STATA 10 (Statacorp, College Station, Texas). We estimated that a sample size of 200 patients was required to detect a mean difference in satisfaction scores of three points with a SD of four points. This assumed a power of 0.80 and a two-tailed α of 0.05, and a loss to follow-up of 25%.


Ethics approval was sought and granted by the Sydney South West Area Health Service (RPAH zone) ethics review committee, Protocol No X09–0285 and HREC/09/RPAH/481.


Study population

Over 90 days during the study interval, 800 eligible patients were identified. Of these, 320 patients consented and enrolled into the study. Median patient age was 36 years (IQR 25–46 years). Sixty-one percent were male (195/320) and 72% (230/320) were treated for musculoskeletal problems. English was the primary language in 66% (211/320) of patients, and 78% (249/320) could identify a regular family doctor. The median waiting time to be seen by either doctor or NP was 53 min (IQR 33–87), and overall 64% of patients were seen within current Australasian Triage Scale waiting time benchmarks (60 min for triage category four and 120 min for triage category five).

Satisfaction surveys were submitted in 74% (236/320) of patients. The median satisfaction score was 22 out of 25 (IQR 19–24). With respect to overall care rating, 84% of patients rated overall care as either ‘very good’ or ‘excellent’, 13% indicated ‘good’, and only 3% rated their care as ‘fair’. No patients rated care as ‘poor’.

Effect of waiting time on patient satisfaction

There was no significant difference in patient demographics, presenting problem type, triage category, or treating clinician type when comparing patients who waited an hour or less with those who waited longer (see table 1). Patients waiting 1 h or less, more frequently rated their overall care as ‘excellent’, although this did not reach statistical significance (66% vs 53% p=0.063), and had higher median satisfaction scores compared with those who waited longer (score, IQR 23, 20–25 vs 21, 19–23 p<0.001). The relationship between waiting time categories and satisfaction scores is shown in figure 1, and demonstrates that each incremental hour of waiting time was associated with a roughly linear fall in median satisfaction scores (p<0.001). The relationship between actual waiting times and how patients rated their waiting time (‘poor’ to ‘excellent’) are compared in figure 2, and shows that median waiting times in patients who rated their wait as ‘excellent’ was 27 min (IQR 19.48) compared with 137 min (IQR 50–172) for patients who rated their waiting time as ‘poor’. The satisfaction survey instrument was internally consistent with a Cronbach's α of 0.82.

Table 1

comparing patient satisfaction and baseline characteristics for patients waiting 1 h or less, and patients waiting more than 1 h

Figure 1

Patient satisfaction scores by waiting time increments of 60 min. This figure is only reproduced in colour in the online version. Access the article online to view this figure in colour.

Figure 2

Actual waiting time by how the patient rated their waiting time (poor to excellent). Access the article online to view this figure in colour.

Predictors of improved overall care rating

When demographic and clinical characteristics were entered into a multivariable ordered regression model, each incremental hour of waiting time was associated with a significant reduction in odds of higher overall care rating (OR 0.53 95% CI 0.37 to 0.75 p<0.001). Other predictors of improved overall care rating were English (as primary language) and initial care by a NP. Adjusted odds ratios are summarised in table 2.

Table 2

Multivariable ordered logistic regression model for overall care rating (poor to excellent) as a function of patient demographic and clinical variables


This was a single-centre study that sought to determine the factors associated with patient satisfaction in an ED fast-track unit. Patient satisfaction remains an important measure of quality of healthcare delivery, and has been associated with improved patient outcomes in both medical and surgical literature.10–14 It has been postulated that patient satisfaction is associated with levels of engagement in health services and compliance with therapy.15 These measures are particularly relevant in the fast-track setting, as presentations are episodic, and often rely on adequate follow-up with a general practitioner to ensure full recovery.

Overall, patients were satisfied, with high satisfaction scores and 84% rating overall care as either very good or excellent. This compared favourably with previous ED studies using this satisfaction instrument.8 ,9 In these studies, only 60% of general ED patients rated care as either ‘excellent’ or ‘very good’ at the point of discharge. An ongoing population health survey in New South Wales also found that 60% of those who had visited any ED within the previous 12 months rated their overall care as excellent or very good.16

The main predictor of improved patient satisfaction in this study was waiting time, with an almost linear improvement in median satisfaction scores, and a doubling of the odds of improved overall care rating associated with each hour of reduction in waiting time. This is consistent with several studies that have examined the impact of waiting time and satisfaction in EDs.17 ,18 Although intuitively obvious, the impact of increasing waiting time on patient satisfaction and overall care rating has not been studied to date in the Australian emergency context. This study highlights the importance of waiting time and has implications for sustainable resourcing of EDs and efficient streaming of patients if they are to provide care that meets the needs and expectations of the community.

The finding that patients with non-English primary language were associated with poorer overall care rating warrants further exploration. It may be a reflection of selection bias with patients from non-English backgrounds less likely to enrol into the study, or a misclassification bias in patients who may not fully understand the survey forms. It is consistent with a previous ED study in the USA which found that non-English speakers were less likely to be satisfied with their care, and less willing to return for ongoing care.19 Patient expectations based on cultural backgrounds may play an important role in ED satisfaction, and efforts should be made to further understand those expectations, particularly in multicultural environments.20.

In this study, NPs were associated with improved patient satisfaction, and this is consistent with published trials of NP-based care evaluating patient satisfaction.21 A randomised trial conducted in the UK suggested greater satisfaction in a convenience sample of 199 patients presenting to a minor injuries unit.22 The present study differs from previous studies in that the setting was a fast-track unit designed to treat a variety of presenting problems, not just minor injuries. In this context, the results of the present study add to existing evidence that ENPs may be an acceptable alternative model of care for patients presenting with low-complexity problems to EDs.

There are several acknowledged limitations of this study, namely that this was a convenience sample with potential for selection bias based on the response rate. The sample generated in this study was felt to be representative of the general fast-track population, with the age, rate of musculoskeletal problems, and patients of non-English speaking backgrounds similar to the general population of patients in this area. However, it was likely that those who refused to participate were associated with poorer satisfaction, with reluctance to participate being symptomatic of their overall dissatisfaction at the time. Compliance with surveys could have been improved with face-to-face interviews after consultation, but this would have introduced observational bias. Factors like empathy, privacy, technical competence, and pain management, which have all been shown to determine satisfaction in EDs,23 ,24 were not explored in this study. We used a validated survey instrument that the authors felt covered the most important domains of satisfaction in an ED (completeness of care, courtesy and politeness, explanation and advice, waiting time, understanding of discharge instructions). The multivariable model used in this study assumed a linear relationship between each category of overall care rating. For instance, the conceptual difference between a rating of ‘good’ versus ‘very good’ was the same as the difference between ‘very good’ and ‘excellent’. This may not be the case as evidenced by the fact that most patients rated care between ‘good’ and ‘excellent’, and few patients rated care as ‘poor’. Finally, we did not evaluate other important domains of quality of care, namely effectiveness, and patient safety.


Satisfaction in this fast-track unit was primarily associated with waiting time, but was also positively associated with English as the primary language and initial consultation by aNP. Efforts to improve waiting time and access to ENPs and healthcare translators would improve the quality of care delivered in this fast-track unit.


We acknowledge Dr Macia Testa from Harvard School of Public Health for advice and biostatistical support in this study. We would also like to acknowledge and thank the medical and nursing staff of the Canterbury Hospital Emergency Department for their support in the study.



  • Contributions MMD: study design, data analysis and manuscript preparation. AW: study design, data collection, data analysis. NE: data collection, literature review, manuscript preparation. AP: data collection, literature review. MC: study design, manuscript review.

  • Competing interests None.

  • Provenance and peer review Not commissioned; internally peer reviewed.