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The disconfirmation paradigm: Throughput times and emergency department patient satisfaction
The Journal of Emergency Medicine, Vol. 32, No. 1, pp. 7–13, 2007 Copyright © 2007 Elsevier Inc. Printed in the USA. All rights reserved 0736-4679/07 $–see front matter
doi:10.1016/j.jemermed.2006.05.028
Original Contributions
THE DISCONFIRMATION PARADIGM: THROUGHPUT TIMES AND EMERGENCY DEPARTMENT PATIENT SATISFACTION Tara N. Cassidy-Smith,
MD,
Brigitte M. Baumann,
MD,
and Edwin D. Boudreaux,
PHD
Department of Emergency Medicine, Cooper University Hospital and University of Medicine and Dentistry of New Jersey—Robert Wood Johnson Medical School at Camden, New Jersey Reprint Address: Tara N. Cassidy-Smith, MD, Department of Emergency Medicine, Cooper University Hospital, One Cooper Plaza, Camden, NJ 08103
e Abstract—This study examined the relationship between throughput times, expectations, and patient satisfaction using the Disconfirmation Paradigm (DP), which proposes that dissatisfaction arises when service expectations are not met. Before discharge or admission, adult emergency department (ED) patients estimated how long they waited for three intervals (Perceived Times): triage to patient care area, patient care area placement to physician evaluation, and physician evaluation to disposition. Acceptable waiting times and satisfaction for the same intervals were then provided by the subject (Acceptable Times and Throughput Time Satisfaction, respectively). Perceived Times were subtracted from Acceptable Times to yield an index of Expectancy Disconfirmation. There were 1118 (72%) of 1550 eligible patients interviewed. Throughput Time Satisfaction predicted overall satisfaction (r ⴝ 0.56 to 0.62, p < 0.001). In turn, Expectancy Disconfirmation predicted Wait Time Satisfaction (r ⴝ 0.42 to 0.64, p < 0.001). Consistent with the DP, when throughput times exceeded expectations, dissatisfaction with those throughput times arose, leading to general dissatisfaction with the ED visit. © 2007 Elsevier Inc.
INTRODUCTION The relevance of patient satisfaction to Emergency Medicine is increasingly important as emergency department (ED) overcrowding continues to rise. EDs are encountering patient loads that often exceed their capacities, presumably leading to increased waiting times and decreased patient satisfaction. Both physicians and hospital administrators have become increasingly concerned with meeting patient expectations of expeditious, quality care under these demanding conditions. A number of studies have attempted to elucidate factors associated with ED patient satisfaction. Several studies have suggested that patients’ perceptions of throughput times are strongly correlated with satisfaction, wheras actual throughput times play a lesser role (1– 4). Perhaps most important in determining a patient’s satisfaction with an ED visit is how the throughput times compare to the patient’s expectations. Consistent with this idea, the Disconfirmation Paradigm proposes that dissatisfaction arises when service expectations are not met (3,4). According to the Disconfirmation Paradigm, perceptions of a service encounter are characterized by either confirmation or disconfirmation of expectancies. Confirmation is when a service is performed as expected. When there is a difference between performance and expectations, disconfirmation results. Negative disconfirmation occurs when the service is perceived as worse
e Keywords—patient satisfaction; emergency department; throughput times; Disconfirmation Paradigm
This abstract was presented (poster presentation) at the Society for Academic Emergency Medicine annual meeting, Orlando, FL, May 2004.
RECEIVED: 11 July 2005; FINAL ACCEPTED: 17 May 2006
SUBMISSION RECEIVED:
4 April 2006; 7
8
T. N. Cassidy-Smith et al.
than expected and positive disconfirmation occurs when the service is perceived as better than expected. Greatest satisfaction is achieved when the patient experiences positive disconfirmation. In practical terms, if Mr. Jones’ wait to be treated is consistent with his expectation, but Ms. Smith’s wait is much longer than expected, Mr. Jones is more likely to be satisfied with his ED visit— even if both patients actually waited the same length of time. We conducted a prospective surveillance study to examine the relations between actual throughput times, patient’s perceptions, patient’s expectations related to those throughput times, and ED patient satisfaction. Specifically, we used the Disconfirmation Paradigm, as well as previous research on throughput times and satisfaction, to guide our study design and hypotheses. We predicted three specific outcomes. First, patients’ actual throughput times will correlate weakly with overall satisfaction (1– 4). Second, the difference between a patient’s perceived throughput time and his acceptable throughput time (i.e., expectancy disconfirmation) will correlate strongly with throughput time satisfaction. Third, throughput time satisfaction, rather than actual throughput times or expectancy disconfirmation, will demonstrate the strongest correlation with overall satisfaction.
METHODS Study Design, Participant Selection This study used a prospective, cross-sectional design. Adult patients being treated in an urban, academic ED between 8:00 a.m. and 12:00 a.m., February 2nd through March 21st, 2003 were approached for inclusion just before discharge or after being told they were going to be admitted. Verbal consent was obtained from all participants. During the consent process, patients were assured that the study would not delay their discharge or admission. This was done to minimize refusal rates and to avoid introducing a selection bias wherein more dissatisfied patients would refuse to participate because they did not want to experience any further delays. Patients were excluded if they were too ill (e.g., vomiting, severe distress), cognitively debilitated (e.g., intoxicated, demented, obtunded), or otherwise unable to respond to questions. Hospital-provided, Spanish-speaking interpreters assisted with Hispanic patients. All patients were managed at the discretion of the treating physician. All disposition decisions were made by the attending physician caring for the patient, regardless of whether a resident or nurse practitioner was also involved in the patient care. The study was pre-approved by the institutional review board (IRB) of the hospital.
Setting The Department of Emergency Medicine at our institution is an academic, Level 1 trauma center serving a population of two million persons. The annual census is approximately 47,000 visits per year, 25% of which are pediatric patients. The ED population is composed of 35% whites, 43% blacks, 20% Hispanics, and 2% other. Approximately 30% are commercially insured, 40% are government insured, and 30% are self-pay/no insurance. At the time of our study we were still using a three-level triage system, in which approximately 29% were triaged as emergent, 49% as urgent, and 23% as routine. The adult admit rate was approximately 25%. Our total walkout rates (left before being seen and left against medical advice) ranged from 8% to 10%.
Measurement A research assistant (RA) interviewed each patient using a survey that assessed patient demographics, patient estimates of the length of various throughput intervals, expectations regarding throughput times, and satisfaction indices. Chart review by trained research assistants was used to abstract demographics, visit characteristics, and actual throughput time. Patient demographics. We assessed age, sex, race/ ethnicity (black, white, Hispanic, other), and insurance status (commercial, Medicaid, Medicare, none/self-pay). Expectancy disconfirmation. Immediately before exiting the ED, discharged patients estimated how long they had waited during three time intervals (Perceived Throughput Times): time from initial entry into the ED to being placed in a treatment area (patient care area placement), wait for physician evaluation once in a treatment area (MD evaluation), and wait from physician evaluation to when the patient was told they were going to be discharged or admitted (disposition notification). Admitted patients often stayed in the ED for hours after they were informed they were to be admitted. Therefore, admitted patients’ evaluations of their satisfaction may have changed significantly after the RA interview, and this change in satisfaction was not captured by our data collection method. However, attempting to survey admitted patients immediately before transfer to the medical/ surgical floor proved to be too difficult, requiring considerable coordination between shift changes in research assistants to track patients during their ED stay. Therefore, for the sake of consistency between ratings of intervals for both discharged and admitted patients, and to help ensure the completeness of data, we elected to use
Satisfaction and Throughput Times
the interval between when the patient was evaluated by a physician and when the patient was informed of the decision to admit, even though patients often remained in the ED for a considerable amount of time after this point. Patients provided estimates of the amount of time that they believed to be “acceptable” to wait for the same three time intervals referenced above (Acceptable Throughput Times). Perceived Throughput Times were subtracted from Acceptable Throughput Times to yield an index of Expectancy Disconfirmation. A positive number represented “better than acceptable” waits (positive disconfirmation), a negative number “worse than acceptable” waits (negative disconfirmation), and 0 a wait exactly consistent with expectations (confirmation). Patient satisfaction. The patient satisfaction survey used in this study was developed using recommended practices for survey development (5). In keeping with recommendations made by Trout et al. (2), we used a skewed response scale (greater number of options for positive responses) to help avoid a ceiling effect: Poor, Fair, Good, Very Good, and Excellent. We chose to create our own survey because existing market surveys (e.g., Press-Ganey) are long and cumbersome to use. Because our ED treats a high volume of patients in a limited space, bed-turnover is extremely important. By keeping the questionnaire focused, potential delays in bed-turnover were minimized and allowed even very ill patients to complete it, thus maximizing the response rate and making the sample more generalizable. We conducted reliability analyses on the satisfaction items (described later) using the data collected for this study. Patients rated their satisfaction with each of the three time intervals (Throughput Time Satisfaction) and the overall visit. Patients also indicated whether they would return to the ED in the future (Yes or No). Visit characteristics. We abstracted information from the written medical chart on method of arrival (ambulance, car, medical transportation, other), initial acuity level as assigned by trained triage nurses (emergent, urgent, routine), and disposition (discharge, admit). We calculated three Actual Throughput Time intervals that were consistent with our survey question intervals: from triage to patient care area placement (pt care area placement), from patient care area placement to physician evaluation time (MD eval), and from physician evaluation to discharge or, among admitted patients, floor notification (disposition notification).
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Data Analysis To establish the reliability of the three items assessing throughput time satisfaction, we computed Cronbach’s alpha. This is as an indicator of internal consistency reliability and is based on the average correlation of the items (5). It represents the degree to which the three items measure a similar entity, i.e., throughput time satisfaction. We validated the overall satisfaction question by comparing responses based on whether patients reported they would return for future emergencies. If the overall satisfaction index is valid, one would expect that patients who report being willing to return would have much greater satisfaction (1,6). To test the primary hypotheses, we calculated Spearman correlation coefficients between Expectancy Disconfirmation Indices, Throughput Time Satisfaction, Actual Throughput Times, and Overall Satisfaction. We predicted three specific outcomes. First, patients’ Actual Throughput Times would correlate weakly (r ⬍ .20) with Overall Satisfaction. Second, the Expectancy Disconfirmation Indices would correlate moderately to strongly (r ⬎ .40) with Throughput Time Satisfaction. Third, of all the indicators of throughput time measured, Throughput Time Satisfaction would demonstrate the strongest correlation with overall satisfaction. All data analyses were computed with SPSS 11.5 (SPSS Inc., Chicago, IL).
RESULTS There were 1118 (72%) of 1550 eligible patients interviewed. Table 1 summarizes the descriptive statistics. We collected the actual throughput times from the written medical charts. The capture rates from the chart review of the specific time intervals were as follows: wait time for patient care area placement, 83%, wait for MD evaluation, 79%, and wait for disposition, 80%. The Cronbach’s alpha for the three Throughput Time Satisfaction items was .82, suggesting good internal consistency and reliability. Patients reporting that they would return to the ED for future care reported markedly greater Overall Satisfaction (Yes return: 4.0 vs. No return: 2.5, p ⬍ 0.001), indicating good construct validity of the Overall Satisfaction item. These patterns of results and methods of expectation and satisfaction are consistent with previous work in this area (2,6,7). Patterns among the Spearman correlation coefficients supported the three hypotheses (Tables 2, 3). First, Actual Throughput Times correlated weakly with Overall Satisfaction (r ⫽ .00 to ⫺0.22). Second, the Expectancy Disconfirmation Indices correlated moderately to strongly with their respective Throughput Time Satisfaction (r ⫽ .42 to .64). Third, of all the variables assessed, Through-
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T. N. Cassidy-Smith et al. Table 1. Subject Characteristics Summary Statistic Mean (SD), Percentage (%), or Median (IQR)
Variable Age Sex Male Female Race/ethnicity White Black Hispanic Other Missing data Insurance status HMO/PPO Medicare Medicaid Self-pay Other Method of arrival Ambulance Car Other Acuity level Emergent Urgent Routine Missing data Disposition Discharged Admitted Actual throughput times Triage to patient care area Patient care area to MD evaluation MD evaluation to disposition Perceived throughput times Triage to patient care area Patient care area to MD evaluation MD evaluation to disposition Acceptable throughput times Triage to patient care area Patient care area to MD evaluation MD evaluation to disposition Expectancy disconfirmation Triage to patient care area Patient care area to MD evaluation MD evaluation to disposition Throughput time satisfaction* Triage to patient care area Patient care area to MD evaluation MD evaluation to disposition Overall satisfaction* Likelihood of returning for future care Yes No Unsure
45 (SD ⫽ 19) 43% 57% 40% 26% 21% 2% 11% 22% 15% 24% 8% 9% 27% 54% 19% 32% 43% 17% 8% 70% 30% 00:35 min (IQR ⫽ 00:15 to 01:05) 00:25 min (IQR ⫽ 00:10 to 00:50) 01:25 min (IQR ⫽ 00:45 to 2:40) 00:20 min (IQR ⫽ 00:05 to 01:00) 00:12 min (IQR ⫽ 00:05 to 00:30) 00:30 min (IQR ⫽ 00:10 to 01:04) 00:30 min (IQR ⫽ 00:10 to 01:00) 00:15 min (IQR ⫽ 00:07 to 00:30) 00:30 min (IQR ⫽ 00:10 to 01:00) 00:00 (IQR ⫽ ⫺00:30 to 00:07) 00:00 (IQR ⫽ ⫺00:05 to 00:15) 00:00 (IQR ⫽ ⫺00:30 to 00:09) 3.5 3.7 3.6 3.8
(SD (SD (SD (SD
⫽ ⫽ ⫽ ⫽
1.3) 1.2) 1.2) 1.2)
4.0 4.0 4.0 4.0
(IQR (IQR (IQR (IQR
⫽ ⫽ ⫽ ⫽
3.0 3.0 3.0 3.0
to to to to
5.0) 5.0) 5.0) 5.0)
92% 6% 2%
* Both mean (SD) and median (IQR) were reported for satisfaction indices, because reporting practices vary in the literature. n ⫽ 1118. Actual throughput times ⫽ calculated using times recorded on medical chart; Perceived throughput times ⫽ patient’s estimates of how long they waited for each interval; Acceptable throughput times ⫽ patient’s opinions regarding how long a wait would be acceptable for each interval; Expectancy disconfirmation ⫽ Perceived throughput times ⫺ acceptable throughput times ⫽ expectancy disconfirmation (0 ⫽ confirmation, “⫺” value ⫽ waited less time than found acceptable, and “⫹” value ⫽ waited more time than found acceptable). Throughput time satisfaction: rated on 5-point Likert-type scale 1 ⫽ Poor, 2 ⫽ Fair, 3 ⫽ Good, 4 ⫽ Very Good, 5 ⫽ Excellent.
Satisfaction and Throughput Times
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Table 2. Spearman Correlation Coefficients Between Actual Throughput Times, Expectancy Disconfirmation, and Throughput Time Satisfaction
Method of Assessment Actual Expectancy disconfirmation
Interval Wait Wait Wait Wait Wait Wait
for for for for for for
patient care area placement MD evaluation disposition patient care area placement MD evaluation disposition
Satisfaction with Wait for Patient Care Area Placement
Satisfaction with Wait for MD
Satisfaction with Wait for Disposition
⫺0.44* ⫺0.06 0.04 0.64** 0.26** 0.18**
⫺0.22* ⫺0.12* ⫺0.02 0.40** 0.45** 0.23**
⫺0.18* ⫺0.07 ⫺0.12** 0.36** 0.42** 0.42**
** p ⬍ 0.001; * p ⬍ 0.01.
put Time Satisfaction indices demonstrated the strongest associations with Overall Satisfaction (r ⫽ .56 to .62). DISCUSSION We prospectively examined the relations between actual throughput times, expectancy disconfirmation, and ED patient satisfaction. Consistent with our first hypothesis and the findings of others, actual throughput times were weakly related to overall satisfaction (1– 4,8). Rather, the Disconfirmation Paradigm, by appealing to how actual throughput times interact with patients’ expectations, allows us to better understand how throughput time affects satisfaction. Specifically, when throughput times exceeded the length of time patients perceived as acceptable, dissatisfaction with those throughput times arose, which was associated with a much greater likelihood of being dissatisfied with the ED visit in general. A patient may enter the ED and wait 60 min to be placed in a patient treatment area, but his satisfaction with the visit will differ based on his expectations. If 60 min is longer
Table 3. Spearman Correlation Coefficients Between Actual Throughput Times, Expectancy Disconfirmation, Throughput Time Satisfaction, and Overall Satisfaction Method of Assessment Actual
Expectancy disconfirmation Satisfaction with
** p ⬍ 0.001.
Interval Wait for patient care area placement Wait for MD evaluation Wait for disposition Wait for patient care area placement Wait for MD evaluation Wait for disposition Wait for patient care area placement Wait for MD evaluation Wait for disposition
Overall Satisfaction ⫺0.22** ⫺0.05 0.00 0.42** 0.28** 0.24** 0.56** 0.59** 0.62**
than he finds acceptable, then he will likely be dissatisfied. The opposite is also true: if it is shorter than he finds acceptable, then he will be satisfied. By prospectively examining patients’ expectations of their throughput times and correlating them with their satisfaction, we were able to validate the Disconfirmation Paradigm in the ED setting. This article confirms earlier work by Thompson et al. (3,9,10). They found that actual waiting times were of marginal importance in predicting ED patient satisfaction; rather, ratings of whether throughput times were greater than, equal to, or less than patient’s expectations were important. Hedges and colleagues also performed a prospective, cross-sectional study to evaluate the effect of actual and perceived wait intervals upon patient satisfaction (4). They, too, were able to demonstrate that overall satisfaction was more strongly associated with the perception that the wait interval was shorter than expected, rather than actual waiting times. An additional factor that may influence patient satisfaction is level of acuity. Boudreaux et al. (7) determined that emergent patients had greater satisfaction when compared with urgent and routine patients. The greatest association with satisfaction was with perceived throughput times, with the urgent patients less satisfied than routine patients, despite similar wait times. These findings support the Disconfirmation Paradigm, where the urgent, more acutely ill patients would have a greater expectation to be seen expeditiously than the routine, less acutely ill patients. Appropriately, dissatisfaction arises when the acute patients’ service expectations fail to be met. There are several clinical implications associated with validation of the Disconfirmation Paradigm. Primarily, our results suggest that targeting perceived wait times and expectations, rather than actual wait times, might offer promise for improving ED patient satisfaction. Considering the amount of money and resources that are often devoted toward improving actual throughput times, such as adding staff, expanding the physical plant, and adding fast-tracks,
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targeting expectations might represent a more cost-effective option. For this reason, efforts aimed at changing the patient’s expectations, rather than actually shortening the time it takes to process the patient, has intuitive appeal. At the very least, it should be viewed as a complementary approach to other process improvement efforts designed to reduce actual throughput times. For systems with severe constraints on space or financial resources that do not allow expansion, either in terms of physical layout or in terms of staffing, strategies that target patients’ expectations may be one of the few options available to affect satisfaction with throughput times. Changing patients’ expectations may not be as easy as one might think, however. Although two studies have found that minimal education interventions designed to change patients’ expectations of their ED care can improve patient satisfaction, others have not (8,11–13). Krishell and Baraff created a brochure that explained ED processes, such as the triage process and how it affects the order of being seen (11). Using a randomized, controlled trial, they were able to conclude that patients receiving the brochure rated satisfaction higher across several domains, including overall satisfaction. One hypothesized mechanism for why such an intervention can be effective is that it helps to change patients’ expectations to be more in line with the reality of how an ED prioritizes patient care and manages throughput. A patient who has a more thorough understanding of why he is waiting and how long typical patients wait may actually modify his own expectations. Put in the vocabulary of the Disconfirmation Paradigm, greater congruence between patient expectations and reality is likely to result in confirmation (or positive disconfirmation) and, ultimately, greater satisfaction with the visit. Others, however, have failed to show an impact using simple interventions on overall patient satisfaction. Mowen et al. predicted that patients given an estimated waiting time at triage would be significantly more satisfied that those who were not (8). They randomized ED patients with “minor” complaints to receive either an estimated waiting
T. N. Cassidy-Smith et al.
time or no information at all. They did not find any differences in satisfaction between the groups, finding that patients in the intervention group did not even remember being told the estimate. In addition, Sun et al. recently published an intervention study that examined the effects of printed information distributed to patients about what to expect in the ED (13). Similar to the Krishell and Baraff (11) study, Sun found no differences in satisfaction between the treatment and control conditions. The ambiguity in these results demonstrates that simple manipulations in modifying expectations may not necessarily improve patient satisfaction with throughput times or satisfaction with their overall visit. More intensive or novel interventions designed to modify patients’ expectations should be the focus of future research. Our study had several limitations. First, we did not collect data during low census hours (12:00 a.m.– 8:00 a.m.), allowing for the possibility that patients seen during these periods have different expectations and actual wait times. In addition, we excluded severely ill patients, who were likely to have faster throughput times based on acuity, thereby excluding patients with wait times that were likely better than expected. Thirdly, we were unable to account for additional factors that may relate to satisfaction or perceived delays, such as extent of workup received, including what tests were performed, or if any consultants were involved in patient care, both of which would increase overall wait times. Finally, admitted patients often waited for hours for an inpatient bed to become available. Because subject enrollment in this investigation was completed shortly after a patient disposition was made, it is likely that we neglected to capture changes in admitted patients’ satisfaction before transfer to the floor. Administration of the survey just before floor transfer of boarded patients proved too difficult and would have resulted in a significant amount of lost data. Furthermore, differentiating between dissatisfaction with ED boarding wait time and ED disposition time would have been impossible. It is also plausible that long term boarders (⬎6 h) would have had greater wait
Figure 1. Hypothetical role of disconfirmation in how throughput times affect satisfaction.
Satisfaction and Throughput Times
time dissatisfaction than brief ED boarders, with the prolonged ED stay negatively affecting wait time satisfaction at all levels. The immediate enrollment of subjects after the disposition decision attempted to address this potential confounder. In conclusion, although it has become clear that patient expectation disconfirmation is most important in determining patient satisfaction, innovative ways to change these expectations that are supported by research are lacking. Our results provide further support for the model outlined in Figure 1 and suggest that reducing throughput times alone will probably not result in marked changes in patient satisfaction. The data support that a viable alternative or complement to reducing actual throughput times is to focus our efforts on developing novel interventions to modify patients’ expectations. Acknowledgments—We thank the following individuals for their help in data collection and study design: Daryl SpruillGraham, Christopher Lawler, and Ramon Perez.
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REFERENCES 1. Boudreaux ED, O’Hea EL. Patient satisfaction in the emergency department: a review of the literature and implications for practice. J Emerg Med 2004;26:13–26. 2. Trout A, Magnusson AR, Hedges JR. Patient satisfaction investi-
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gations and the emergency department: what does the literature say? Acad Emerg Med 2000;7:695–709. Thompson DA, Yarnold PR. Relating patient satisfaction to waiting times perceptions and expectations: the disconfirmation paradigm. Acad Emerg Med 1995;2:1057– 62. Hedges JR, Trout A, Magnusson AR. Satisfied Patients Exiting the Emergency Department (SPEED) Study. Acad Emerg Med 2002; 9:15–21. Pedhazur EJ, Schmelkin LP. Measurement, design, and analysis: an integrated approach. Hillsdale, NJ: Lawrence Erlbaum Associates; 1991. Hall MF, Press I. Keys to patient satisfaction in the emergency department: results of a multiple facility study. Hosp Health Serv Adm 1996;41:515–32. Boudreaux ED, Friedman J, Chansky ME, Baumann BM. Emergency department patient satisfaction: examining the role of acuity. Acad Emerg Med 2004;11:162– 8. Mowen JC, Licata JW, McPhail J. Waiting in the emergency room: how to improve patient satisfaction. J Health Care Mark 1993;13: 26 –33. Thompson DA, Yarnold PR, Williams DR, Adams SL. Effects of actual waiting time, perceived waiting time, information delivery, and expressive quality on patient satisfaction in the emergency department. Ann Emerg Med 1996;28:657– 65. Thompson DA, Yarnold PR, Adams SL, Spacone AB. How accurate are waiting time perceptions of patients in the emergency department? Ann Emerg Med 1996;28:652–56. Krishel S, Baraff LJ. Effect of emergency department information on patient satisfaction. Ann Emerg Med 1993;22:568 –72. Corbett SW, White PD, Wittlake WA. Benefits of an informational videotape for emergency department patients. Am J Emerg Med 2000;18:67–71. Sun BC, Brinkley M, Morrissey J, Rice P, Stair T. A patient education intervention does not improve satisfaction with emergency care. Ann Emerg Med 2004;44:378 – 83.
doi:10.1016/j.jemermed.2006.05.028
Original Contributions
THE DISCONFIRMATION PARADIGM: THROUGHPUT TIMES AND EMERGENCY DEPARTMENT PATIENT SATISFACTION Tara N. Cassidy-Smith,
MD,
Brigitte M. Baumann,
MD,
and Edwin D. Boudreaux,
PHD
Department of Emergency Medicine, Cooper University Hospital and University of Medicine and Dentistry of New Jersey—Robert Wood Johnson Medical School at Camden, New Jersey Reprint Address: Tara N. Cassidy-Smith, MD, Department of Emergency Medicine, Cooper University Hospital, One Cooper Plaza, Camden, NJ 08103
e Abstract—This study examined the relationship between throughput times, expectations, and patient satisfaction using the Disconfirmation Paradigm (DP), which proposes that dissatisfaction arises when service expectations are not met. Before discharge or admission, adult emergency department (ED) patients estimated how long they waited for three intervals (Perceived Times): triage to patient care area, patient care area placement to physician evaluation, and physician evaluation to disposition. Acceptable waiting times and satisfaction for the same intervals were then provided by the subject (Acceptable Times and Throughput Time Satisfaction, respectively). Perceived Times were subtracted from Acceptable Times to yield an index of Expectancy Disconfirmation. There were 1118 (72%) of 1550 eligible patients interviewed. Throughput Time Satisfaction predicted overall satisfaction (r ⴝ 0.56 to 0.62, p < 0.001). In turn, Expectancy Disconfirmation predicted Wait Time Satisfaction (r ⴝ 0.42 to 0.64, p < 0.001). Consistent with the DP, when throughput times exceeded expectations, dissatisfaction with those throughput times arose, leading to general dissatisfaction with the ED visit. © 2007 Elsevier Inc.
INTRODUCTION The relevance of patient satisfaction to Emergency Medicine is increasingly important as emergency department (ED) overcrowding continues to rise. EDs are encountering patient loads that often exceed their capacities, presumably leading to increased waiting times and decreased patient satisfaction. Both physicians and hospital administrators have become increasingly concerned with meeting patient expectations of expeditious, quality care under these demanding conditions. A number of studies have attempted to elucidate factors associated with ED patient satisfaction. Several studies have suggested that patients’ perceptions of throughput times are strongly correlated with satisfaction, wheras actual throughput times play a lesser role (1– 4). Perhaps most important in determining a patient’s satisfaction with an ED visit is how the throughput times compare to the patient’s expectations. Consistent with this idea, the Disconfirmation Paradigm proposes that dissatisfaction arises when service expectations are not met (3,4). According to the Disconfirmation Paradigm, perceptions of a service encounter are characterized by either confirmation or disconfirmation of expectancies. Confirmation is when a service is performed as expected. When there is a difference between performance and expectations, disconfirmation results. Negative disconfirmation occurs when the service is perceived as worse
e Keywords—patient satisfaction; emergency department; throughput times; Disconfirmation Paradigm
This abstract was presented (poster presentation) at the Society for Academic Emergency Medicine annual meeting, Orlando, FL, May 2004.
RECEIVED: 11 July 2005; FINAL ACCEPTED: 17 May 2006
SUBMISSION RECEIVED:
4 April 2006; 7
8
T. N. Cassidy-Smith et al.
than expected and positive disconfirmation occurs when the service is perceived as better than expected. Greatest satisfaction is achieved when the patient experiences positive disconfirmation. In practical terms, if Mr. Jones’ wait to be treated is consistent with his expectation, but Ms. Smith’s wait is much longer than expected, Mr. Jones is more likely to be satisfied with his ED visit— even if both patients actually waited the same length of time. We conducted a prospective surveillance study to examine the relations between actual throughput times, patient’s perceptions, patient’s expectations related to those throughput times, and ED patient satisfaction. Specifically, we used the Disconfirmation Paradigm, as well as previous research on throughput times and satisfaction, to guide our study design and hypotheses. We predicted three specific outcomes. First, patients’ actual throughput times will correlate weakly with overall satisfaction (1– 4). Second, the difference between a patient’s perceived throughput time and his acceptable throughput time (i.e., expectancy disconfirmation) will correlate strongly with throughput time satisfaction. Third, throughput time satisfaction, rather than actual throughput times or expectancy disconfirmation, will demonstrate the strongest correlation with overall satisfaction.
METHODS Study Design, Participant Selection This study used a prospective, cross-sectional design. Adult patients being treated in an urban, academic ED between 8:00 a.m. and 12:00 a.m., February 2nd through March 21st, 2003 were approached for inclusion just before discharge or after being told they were going to be admitted. Verbal consent was obtained from all participants. During the consent process, patients were assured that the study would not delay their discharge or admission. This was done to minimize refusal rates and to avoid introducing a selection bias wherein more dissatisfied patients would refuse to participate because they did not want to experience any further delays. Patients were excluded if they were too ill (e.g., vomiting, severe distress), cognitively debilitated (e.g., intoxicated, demented, obtunded), or otherwise unable to respond to questions. Hospital-provided, Spanish-speaking interpreters assisted with Hispanic patients. All patients were managed at the discretion of the treating physician. All disposition decisions were made by the attending physician caring for the patient, regardless of whether a resident or nurse practitioner was also involved in the patient care. The study was pre-approved by the institutional review board (IRB) of the hospital.
Setting The Department of Emergency Medicine at our institution is an academic, Level 1 trauma center serving a population of two million persons. The annual census is approximately 47,000 visits per year, 25% of which are pediatric patients. The ED population is composed of 35% whites, 43% blacks, 20% Hispanics, and 2% other. Approximately 30% are commercially insured, 40% are government insured, and 30% are self-pay/no insurance. At the time of our study we were still using a three-level triage system, in which approximately 29% were triaged as emergent, 49% as urgent, and 23% as routine. The adult admit rate was approximately 25%. Our total walkout rates (left before being seen and left against medical advice) ranged from 8% to 10%.
Measurement A research assistant (RA) interviewed each patient using a survey that assessed patient demographics, patient estimates of the length of various throughput intervals, expectations regarding throughput times, and satisfaction indices. Chart review by trained research assistants was used to abstract demographics, visit characteristics, and actual throughput time. Patient demographics. We assessed age, sex, race/ ethnicity (black, white, Hispanic, other), and insurance status (commercial, Medicaid, Medicare, none/self-pay). Expectancy disconfirmation. Immediately before exiting the ED, discharged patients estimated how long they had waited during three time intervals (Perceived Throughput Times): time from initial entry into the ED to being placed in a treatment area (patient care area placement), wait for physician evaluation once in a treatment area (MD evaluation), and wait from physician evaluation to when the patient was told they were going to be discharged or admitted (disposition notification). Admitted patients often stayed in the ED for hours after they were informed they were to be admitted. Therefore, admitted patients’ evaluations of their satisfaction may have changed significantly after the RA interview, and this change in satisfaction was not captured by our data collection method. However, attempting to survey admitted patients immediately before transfer to the medical/ surgical floor proved to be too difficult, requiring considerable coordination between shift changes in research assistants to track patients during their ED stay. Therefore, for the sake of consistency between ratings of intervals for both discharged and admitted patients, and to help ensure the completeness of data, we elected to use
Satisfaction and Throughput Times
the interval between when the patient was evaluated by a physician and when the patient was informed of the decision to admit, even though patients often remained in the ED for a considerable amount of time after this point. Patients provided estimates of the amount of time that they believed to be “acceptable” to wait for the same three time intervals referenced above (Acceptable Throughput Times). Perceived Throughput Times were subtracted from Acceptable Throughput Times to yield an index of Expectancy Disconfirmation. A positive number represented “better than acceptable” waits (positive disconfirmation), a negative number “worse than acceptable” waits (negative disconfirmation), and 0 a wait exactly consistent with expectations (confirmation). Patient satisfaction. The patient satisfaction survey used in this study was developed using recommended practices for survey development (5). In keeping with recommendations made by Trout et al. (2), we used a skewed response scale (greater number of options for positive responses) to help avoid a ceiling effect: Poor, Fair, Good, Very Good, and Excellent. We chose to create our own survey because existing market surveys (e.g., Press-Ganey) are long and cumbersome to use. Because our ED treats a high volume of patients in a limited space, bed-turnover is extremely important. By keeping the questionnaire focused, potential delays in bed-turnover were minimized and allowed even very ill patients to complete it, thus maximizing the response rate and making the sample more generalizable. We conducted reliability analyses on the satisfaction items (described later) using the data collected for this study. Patients rated their satisfaction with each of the three time intervals (Throughput Time Satisfaction) and the overall visit. Patients also indicated whether they would return to the ED in the future (Yes or No). Visit characteristics. We abstracted information from the written medical chart on method of arrival (ambulance, car, medical transportation, other), initial acuity level as assigned by trained triage nurses (emergent, urgent, routine), and disposition (discharge, admit). We calculated three Actual Throughput Time intervals that were consistent with our survey question intervals: from triage to patient care area placement (pt care area placement), from patient care area placement to physician evaluation time (MD eval), and from physician evaluation to discharge or, among admitted patients, floor notification (disposition notification).
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Data Analysis To establish the reliability of the three items assessing throughput time satisfaction, we computed Cronbach’s alpha. This is as an indicator of internal consistency reliability and is based on the average correlation of the items (5). It represents the degree to which the three items measure a similar entity, i.e., throughput time satisfaction. We validated the overall satisfaction question by comparing responses based on whether patients reported they would return for future emergencies. If the overall satisfaction index is valid, one would expect that patients who report being willing to return would have much greater satisfaction (1,6). To test the primary hypotheses, we calculated Spearman correlation coefficients between Expectancy Disconfirmation Indices, Throughput Time Satisfaction, Actual Throughput Times, and Overall Satisfaction. We predicted three specific outcomes. First, patients’ Actual Throughput Times would correlate weakly (r ⬍ .20) with Overall Satisfaction. Second, the Expectancy Disconfirmation Indices would correlate moderately to strongly (r ⬎ .40) with Throughput Time Satisfaction. Third, of all the indicators of throughput time measured, Throughput Time Satisfaction would demonstrate the strongest correlation with overall satisfaction. All data analyses were computed with SPSS 11.5 (SPSS Inc., Chicago, IL).
RESULTS There were 1118 (72%) of 1550 eligible patients interviewed. Table 1 summarizes the descriptive statistics. We collected the actual throughput times from the written medical charts. The capture rates from the chart review of the specific time intervals were as follows: wait time for patient care area placement, 83%, wait for MD evaluation, 79%, and wait for disposition, 80%. The Cronbach’s alpha for the three Throughput Time Satisfaction items was .82, suggesting good internal consistency and reliability. Patients reporting that they would return to the ED for future care reported markedly greater Overall Satisfaction (Yes return: 4.0 vs. No return: 2.5, p ⬍ 0.001), indicating good construct validity of the Overall Satisfaction item. These patterns of results and methods of expectation and satisfaction are consistent with previous work in this area (2,6,7). Patterns among the Spearman correlation coefficients supported the three hypotheses (Tables 2, 3). First, Actual Throughput Times correlated weakly with Overall Satisfaction (r ⫽ .00 to ⫺0.22). Second, the Expectancy Disconfirmation Indices correlated moderately to strongly with their respective Throughput Time Satisfaction (r ⫽ .42 to .64). Third, of all the variables assessed, Through-
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T. N. Cassidy-Smith et al. Table 1. Subject Characteristics Summary Statistic Mean (SD), Percentage (%), or Median (IQR)
Variable Age Sex Male Female Race/ethnicity White Black Hispanic Other Missing data Insurance status HMO/PPO Medicare Medicaid Self-pay Other Method of arrival Ambulance Car Other Acuity level Emergent Urgent Routine Missing data Disposition Discharged Admitted Actual throughput times Triage to patient care area Patient care area to MD evaluation MD evaluation to disposition Perceived throughput times Triage to patient care area Patient care area to MD evaluation MD evaluation to disposition Acceptable throughput times Triage to patient care area Patient care area to MD evaluation MD evaluation to disposition Expectancy disconfirmation Triage to patient care area Patient care area to MD evaluation MD evaluation to disposition Throughput time satisfaction* Triage to patient care area Patient care area to MD evaluation MD evaluation to disposition Overall satisfaction* Likelihood of returning for future care Yes No Unsure
45 (SD ⫽ 19) 43% 57% 40% 26% 21% 2% 11% 22% 15% 24% 8% 9% 27% 54% 19% 32% 43% 17% 8% 70% 30% 00:35 min (IQR ⫽ 00:15 to 01:05) 00:25 min (IQR ⫽ 00:10 to 00:50) 01:25 min (IQR ⫽ 00:45 to 2:40) 00:20 min (IQR ⫽ 00:05 to 01:00) 00:12 min (IQR ⫽ 00:05 to 00:30) 00:30 min (IQR ⫽ 00:10 to 01:04) 00:30 min (IQR ⫽ 00:10 to 01:00) 00:15 min (IQR ⫽ 00:07 to 00:30) 00:30 min (IQR ⫽ 00:10 to 01:00) 00:00 (IQR ⫽ ⫺00:30 to 00:07) 00:00 (IQR ⫽ ⫺00:05 to 00:15) 00:00 (IQR ⫽ ⫺00:30 to 00:09) 3.5 3.7 3.6 3.8
(SD (SD (SD (SD
⫽ ⫽ ⫽ ⫽
1.3) 1.2) 1.2) 1.2)
4.0 4.0 4.0 4.0
(IQR (IQR (IQR (IQR
⫽ ⫽ ⫽ ⫽
3.0 3.0 3.0 3.0
to to to to
5.0) 5.0) 5.0) 5.0)
92% 6% 2%
* Both mean (SD) and median (IQR) were reported for satisfaction indices, because reporting practices vary in the literature. n ⫽ 1118. Actual throughput times ⫽ calculated using times recorded on medical chart; Perceived throughput times ⫽ patient’s estimates of how long they waited for each interval; Acceptable throughput times ⫽ patient’s opinions regarding how long a wait would be acceptable for each interval; Expectancy disconfirmation ⫽ Perceived throughput times ⫺ acceptable throughput times ⫽ expectancy disconfirmation (0 ⫽ confirmation, “⫺” value ⫽ waited less time than found acceptable, and “⫹” value ⫽ waited more time than found acceptable). Throughput time satisfaction: rated on 5-point Likert-type scale 1 ⫽ Poor, 2 ⫽ Fair, 3 ⫽ Good, 4 ⫽ Very Good, 5 ⫽ Excellent.
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Table 2. Spearman Correlation Coefficients Between Actual Throughput Times, Expectancy Disconfirmation, and Throughput Time Satisfaction
Method of Assessment Actual Expectancy disconfirmation
Interval Wait Wait Wait Wait Wait Wait
for for for for for for
patient care area placement MD evaluation disposition patient care area placement MD evaluation disposition
Satisfaction with Wait for Patient Care Area Placement
Satisfaction with Wait for MD
Satisfaction with Wait for Disposition
⫺0.44* ⫺0.06 0.04 0.64** 0.26** 0.18**
⫺0.22* ⫺0.12* ⫺0.02 0.40** 0.45** 0.23**
⫺0.18* ⫺0.07 ⫺0.12** 0.36** 0.42** 0.42**
** p ⬍ 0.001; * p ⬍ 0.01.
put Time Satisfaction indices demonstrated the strongest associations with Overall Satisfaction (r ⫽ .56 to .62). DISCUSSION We prospectively examined the relations between actual throughput times, expectancy disconfirmation, and ED patient satisfaction. Consistent with our first hypothesis and the findings of others, actual throughput times were weakly related to overall satisfaction (1– 4,8). Rather, the Disconfirmation Paradigm, by appealing to how actual throughput times interact with patients’ expectations, allows us to better understand how throughput time affects satisfaction. Specifically, when throughput times exceeded the length of time patients perceived as acceptable, dissatisfaction with those throughput times arose, which was associated with a much greater likelihood of being dissatisfied with the ED visit in general. A patient may enter the ED and wait 60 min to be placed in a patient treatment area, but his satisfaction with the visit will differ based on his expectations. If 60 min is longer
Table 3. Spearman Correlation Coefficients Between Actual Throughput Times, Expectancy Disconfirmation, Throughput Time Satisfaction, and Overall Satisfaction Method of Assessment Actual
Expectancy disconfirmation Satisfaction with
** p ⬍ 0.001.
Interval Wait for patient care area placement Wait for MD evaluation Wait for disposition Wait for patient care area placement Wait for MD evaluation Wait for disposition Wait for patient care area placement Wait for MD evaluation Wait for disposition
Overall Satisfaction ⫺0.22** ⫺0.05 0.00 0.42** 0.28** 0.24** 0.56** 0.59** 0.62**
than he finds acceptable, then he will likely be dissatisfied. The opposite is also true: if it is shorter than he finds acceptable, then he will be satisfied. By prospectively examining patients’ expectations of their throughput times and correlating them with their satisfaction, we were able to validate the Disconfirmation Paradigm in the ED setting. This article confirms earlier work by Thompson et al. (3,9,10). They found that actual waiting times were of marginal importance in predicting ED patient satisfaction; rather, ratings of whether throughput times were greater than, equal to, or less than patient’s expectations were important. Hedges and colleagues also performed a prospective, cross-sectional study to evaluate the effect of actual and perceived wait intervals upon patient satisfaction (4). They, too, were able to demonstrate that overall satisfaction was more strongly associated with the perception that the wait interval was shorter than expected, rather than actual waiting times. An additional factor that may influence patient satisfaction is level of acuity. Boudreaux et al. (7) determined that emergent patients had greater satisfaction when compared with urgent and routine patients. The greatest association with satisfaction was with perceived throughput times, with the urgent patients less satisfied than routine patients, despite similar wait times. These findings support the Disconfirmation Paradigm, where the urgent, more acutely ill patients would have a greater expectation to be seen expeditiously than the routine, less acutely ill patients. Appropriately, dissatisfaction arises when the acute patients’ service expectations fail to be met. There are several clinical implications associated with validation of the Disconfirmation Paradigm. Primarily, our results suggest that targeting perceived wait times and expectations, rather than actual wait times, might offer promise for improving ED patient satisfaction. Considering the amount of money and resources that are often devoted toward improving actual throughput times, such as adding staff, expanding the physical plant, and adding fast-tracks,
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targeting expectations might represent a more cost-effective option. For this reason, efforts aimed at changing the patient’s expectations, rather than actually shortening the time it takes to process the patient, has intuitive appeal. At the very least, it should be viewed as a complementary approach to other process improvement efforts designed to reduce actual throughput times. For systems with severe constraints on space or financial resources that do not allow expansion, either in terms of physical layout or in terms of staffing, strategies that target patients’ expectations may be one of the few options available to affect satisfaction with throughput times. Changing patients’ expectations may not be as easy as one might think, however. Although two studies have found that minimal education interventions designed to change patients’ expectations of their ED care can improve patient satisfaction, others have not (8,11–13). Krishell and Baraff created a brochure that explained ED processes, such as the triage process and how it affects the order of being seen (11). Using a randomized, controlled trial, they were able to conclude that patients receiving the brochure rated satisfaction higher across several domains, including overall satisfaction. One hypothesized mechanism for why such an intervention can be effective is that it helps to change patients’ expectations to be more in line with the reality of how an ED prioritizes patient care and manages throughput. A patient who has a more thorough understanding of why he is waiting and how long typical patients wait may actually modify his own expectations. Put in the vocabulary of the Disconfirmation Paradigm, greater congruence between patient expectations and reality is likely to result in confirmation (or positive disconfirmation) and, ultimately, greater satisfaction with the visit. Others, however, have failed to show an impact using simple interventions on overall patient satisfaction. Mowen et al. predicted that patients given an estimated waiting time at triage would be significantly more satisfied that those who were not (8). They randomized ED patients with “minor” complaints to receive either an estimated waiting
T. N. Cassidy-Smith et al.
time or no information at all. They did not find any differences in satisfaction between the groups, finding that patients in the intervention group did not even remember being told the estimate. In addition, Sun et al. recently published an intervention study that examined the effects of printed information distributed to patients about what to expect in the ED (13). Similar to the Krishell and Baraff (11) study, Sun found no differences in satisfaction between the treatment and control conditions. The ambiguity in these results demonstrates that simple manipulations in modifying expectations may not necessarily improve patient satisfaction with throughput times or satisfaction with their overall visit. More intensive or novel interventions designed to modify patients’ expectations should be the focus of future research. Our study had several limitations. First, we did not collect data during low census hours (12:00 a.m.– 8:00 a.m.), allowing for the possibility that patients seen during these periods have different expectations and actual wait times. In addition, we excluded severely ill patients, who were likely to have faster throughput times based on acuity, thereby excluding patients with wait times that were likely better than expected. Thirdly, we were unable to account for additional factors that may relate to satisfaction or perceived delays, such as extent of workup received, including what tests were performed, or if any consultants were involved in patient care, both of which would increase overall wait times. Finally, admitted patients often waited for hours for an inpatient bed to become available. Because subject enrollment in this investigation was completed shortly after a patient disposition was made, it is likely that we neglected to capture changes in admitted patients’ satisfaction before transfer to the floor. Administration of the survey just before floor transfer of boarded patients proved too difficult and would have resulted in a significant amount of lost data. Furthermore, differentiating between dissatisfaction with ED boarding wait time and ED disposition time would have been impossible. It is also plausible that long term boarders (⬎6 h) would have had greater wait
Figure 1. Hypothetical role of disconfirmation in how throughput times affect satisfaction.
Satisfaction and Throughput Times
time dissatisfaction than brief ED boarders, with the prolonged ED stay negatively affecting wait time satisfaction at all levels. The immediate enrollment of subjects after the disposition decision attempted to address this potential confounder. In conclusion, although it has become clear that patient expectation disconfirmation is most important in determining patient satisfaction, innovative ways to change these expectations that are supported by research are lacking. Our results provide further support for the model outlined in Figure 1 and suggest that reducing throughput times alone will probably not result in marked changes in patient satisfaction. The data support that a viable alternative or complement to reducing actual throughput times is to focus our efforts on developing novel interventions to modify patients’ expectations. Acknowledgments—We thank the following individuals for their help in data collection and study design: Daryl SpruillGraham, Christopher Lawler, and Ramon Perez.
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