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Implications of England's Four-Hour Target for Quality of Care and Resource Use in the Emergency Department
HEALTH POLICY/ORIGINAL RESEARCH
Implications of England’s Four-Hour Target for Quality of Care and Resource Use in the Emergency Department Ellen J. Weber, MD, Suzanne Mason, MD, FRCS, Jennifer V. Freeman, PhD, Joanne Coster, MSc From the Department of Emergency Medicine, University of California, San Francisco, San Francisco, CA (Weber); and the School of Health and Related Research, University of Sheffield, Sheffield, United Kingdom (Mason, Freeman, Coster).
Study objective: In 2005, England implemented a controversial target limiting patient stays in the emergency department (ED) to 4 hours. We determine the effect of the “4-hour target” on quality of care and resource use. Methods: This was a retrospective study of 15 purposively sampled EDs in England, representing a range of performance on the target. The EDs provided administrative data on all visits for May and June, 2003 to 2006. These years spanned the period before the target until more than a year after full implementation. We assessed changes in admission rate, investigations, deaths in the ED, and return visits within 1 week for all patients and separately for those aged 65 years or older. Regression analyses adjusted for clustering at the hospital level and changes in acuity reflected by ambulance arrivals. Results are expressed as the estimated annual change in the percentage of patients experiencing the outcome, with 95% confidence intervals (CIs). Results: A total of 772,525 ED visits were analyzed; visits increased 19% during the 4-year period. Between 2003 and 2006, the percentage of patients arriving by ambulance decreased from 27.8% to 25.8% (annual change from 2003 ⫺0.80%; 95% CI for change: ⫺1.48% to ⫺0.12%). Visits by individuals aged 65 years or older were stable (19.9% to 19.1%; annual change ⫺0.19%; 95% CI for change ⫺0.44% to 0.06%). Between 2003 and 2006, admissions from the ED were unchanged, at 23% (95% CI for change ⫺0.43% to 1.11%). The percentage of patients receiving blood tests increased from 13.8% to 19.8% (annual change 1.00%; 95% CI for change ⫺0.09% to 2.08%). Frequency of radiologic studies decreased slightly, from 38.0% to 35.7% (annual change ⫺0.60%; 95% CI ⫺1.58% to 0.37%). Deaths in the ED and return ED visits within 1 week were unchanged. Return visits resulting in hospital admission increased initially and then returned to 2003 levels (annual change ⫺3.10%; 95% CI ⫺7.32% to 1.11%). Conclusion: England’s 4-hour target did not appear to have a negative effect on quality or safety of ED care and had little effect on test use. [Ann Emerg Med. 2012;60:699-706.] Please see page 700 for the Editor’s Capsule Summary of this article. A feedback survey is available with each research article published on the Web at www.annemergmed.com. A podcast for this article is available at www.annemergmed.com. 0196-0644/$-see front matter Copyright © 2012 by the American College of Emergency Physicians. http://dx.doi.org/10.1016/j.annemergmed.2012.08.009
INTRODUCTION Emergency department (ED) crowding is an international problem, with well-documented negative influences on quality and safety of care.1-12 In 2005, England instituted an emergency care target, setting a maximum limit on the length of stay of 4 hours from time of arrival to discharge home or moving to an inpatient bed.13,14 Australia, New Zealand, and parts of Canada have since followed suit with targets of 4 to 8 hours.10,11,15 In the United States, where crowding has been labeled a “crisis” for years, the Centers for Medicare & Medicaid Services is just beginning to monitor ED length of stay.16,17 Although potentially speeding ED patient flow and reducing waits for physician evaluation or admission, a focus on time risks causing perverse consequences. Emergency physicians could simply choose to admit patients rather than attempt to evaluate them within the 4-hour Volume , . : December
window, resulting in more admissions. In addition, the number of laboratory tests and radiographs might increase as a substitute for a period of observation, and ED deaths or return visits might increase because of incomplete evaluations, diagnostic errors, or insufficient discharge instructions and follow-up arrangements as providers keep an eye on the clock. In 2011, England’s coalition government de-emphasized the 4-hour target in favor of quality measures.18,19 Yet the target was never formally evaluated. We therefore conducted a study to evaluate how quality of care and resource use was affected by the 4-hour target.
MATERIALS AND METHODS This quantitative analysis is part of a mixed-methods study conducted between June 2008 and April 2010, designed to Annals of Emergency Medicine 699
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Editor’s Capsule Summary
What is already known on this topic In 2005, the English government required 98% of emergency department (ED) visits have door-todeparture time of less than 4 hours, but no quality or resource assessment accompanied the measure. What question this study addressed In a purposive sample of 15 English EDs, what happened to admissions, laboratory and imaging investigations, deaths in the ED, and return visits before and after imposition of the target? What this study adds to our knowledge ED length of stay improved during this period, although only some EDs actually met the target for 98% of patients. Patient outcomes and measures of utilization did not change appreciably. How this is relevant to clinical practice Implementation of external targets alone does not alter ED quality of care or resource use.
determine the effect of the 4-hour target on organizational behavior and patient outcomes. The study was approved by the Ethics Committee of the National Health Service (REC08/H0206/16) and the R&D offices of all Trusts involved. Setting In 2005, the National Health Service in England imposed a target that 98% of all ED patients must be seen, treated, and either discharged home or admitted to an inpatient ward within 4 hours.13,14 The target was announced in 2003 and gradually implemented with increasing thresholds for compliance during 2004 until reaching the 98% threshold on January 1, 2005. Acute Trusts (hospitals) received a financial incentive for meeting each threshold, with the last payment in early 2005. Notably, the leadership of the Trust—not the ED—was held accountable to the Health Ministry for meeting the target. For approximately the next 5 years, Trusts reported that 96% to 98% of ED patients had lengths of stay of 4 hours or less, although the 98% threshold was met consistently in less than half of EDs. Selection of Participants Using published data for performance on the target from the third quarter of 2007, we sorted all Acute Trusts in England into high, middle, and low performers.20 From each performance tier, we selected 12 Trusts spanning the range of size, hospital type, and geographic location within England. Lead clinicians from EDs in these Trusts were contacted by 700 Annals of Emergency Medicine
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letter and asked to participate in the data collection part of the study. One reply indicated that the Trust did not have a Level I ED, resulting in invitations to a total of 35 departments. Twenty EDs agreed to participate. Data Collection and Processing Information technology personnel from participating EDs were asked to provide routine patient-level data for all patients attending their department in May and June 2003 to 2006 inclusive. The study years represented the interval from the announcement of the target to 1.5 years after its establishment at the 98% threshold; the months were selected to avoid major holidays and quarterly changeovers of junior physicians. The following data fields were requested: unique identifier (National Health Service number or hospital number), date and time of arrival, date of birth (or age), sex, mode of arrival, presenting complaint, investigations (laboratories and ECGs) and imaging performed in the ED, disposition, diagnosis, and date and time of leaving the department. Methodological details and results of the qualitative aspect of the mixed-methods study have been reported previously.21 Briefly, investigators visited 9 of the 20 consenting sites, conducting interviews with ED leadership and observing the department’s operations. Information about changes made in the department obtained from interviews and observation was used in interpreting the quantitative results presented here. Outcome Measures Outcomes of interest were changes over time in the following areas: (1) percentage of patients admitted to the hospital from the ED; (2) percentage of patients undergoing laboratory testing, ECG, or imaging in the ED; (3) percentage of patients who died in the ED; (4) percentage of patients discharged from the ED who returned within 1 week and, within this group, the percentage of return visits that resulted in hospital admission. We selected these outcomes as proxies of quality, safety, and resource use that could be obtained from routine data. To distinguish any differential effect on older patients who might have more complex or subtle illnesses, we performed subgroup analyses on the same endpoints for patients 65 years and older. The proportion of patients who left the ED (for a hospital bed, discharge, or transfer) within 4 hours was calculated to determine whether performance on the target improved over time. Primary Data Analysis Duplicate visit entries were identified by using hospital number, patient identification, date, and time of arrival and were deleted from the data file. The following variables were categorized and coded to ensure uniformity across the departments: age, mode of arrival, disposition, and whether the patient underwent any laboratory, ECG, or radiology studies (coded separately). Most hospitals did not distinguish among patients who may have spent time in an ED’s clinical decision Volume , . : December
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unit, and therefore only final disposition was considered. The time each patient spent in the ED was defined as the time from registration until leaving the department, with the date or time of admission and the date or time of discharge. Patients who were dead on arrival were excluded and patients with missing data for a particular element (eg, time of arrival) were excluded for that particular analysis. The unique identifier was used to count the number of patients at each site who had 1 or more return visits within 1 week. We chose this interval because a return visit within 1 week is likely to be related to the presenting problem on the initial visit. For the categorical, binary outcomes such as percentage treated within 4 hours, a hospital-level analysis was conducted. To estimate the average effect for each year, data were combined across all hospitals, with analytic weights proportional to hospital size. These annual effects were tabulated, together with their 95% confidence intervals (CIs). To examine whether there was any change during the study period, a linear regression was conducted on the data for each hospital, with year as the predictor variable. Because there was evidence that the proportion of ambulance arrivals changed over time, this variable was included as a factor in the linear regression. Each regression produced estimates of the expected change during the study period in that hospital. To assess whether there was a change during the study period, these estimates were analyzed with a 1-sample t test. Analytic weights proportional to hospital size were applied to each hospital coefficient to allow for the differences in hospital size. The results are presented as the average change in the percentage of patients experiencing this outcome during the study period, together with 95% CIs. Length of stay in the department was investigated with a random-effects regression model, with hospital fitted as a random effect to adjust for clustering at the hospital level and ambulance arrival fitted as a factor. For time to discharge, the baseline value at 2003 is given, whereas for the following years, the value is the change relative to this baseline. Data analysis was performed with SAS (version 9.2; SAS Institute, Inc., Cary, NC) and Stata (version 10; StataCorp, College Station, TX).
RESULTS Of the 20 EDs agreeing to participate, 3 were unable to accumulate and submit the data, and 1 failed to reply after numerous contacts. One hospital was able to supply data for only 2005 and 2006 and so could not be included in this analysis. The 15 remaining Trusts were evenly distributed with regard to their performance on the target and represented a range of teaching and nonteaching hospitals and location (Table 1). A total of 772,525 visits were analyzed. ED visits for May and June increased 19% during the 4 years, from 171,988 in 2003 to 204,727 in 2006 (Figure 1; Table 2). The percentage of patients arriving by ambulance decreased from 27.8% to 25.8% during the 4 years (annual change ⫺0.80%; 95% CI ⫺1.48% to ⫺0.12%); the proportion of patients aged 65 years or older Volume , . : December
Table 1. Characteristics of hospitals included in the study. Hospital 10 14 8 4 12 6 13 9 3 5 7 15 2 1 11
ED Visits*
Type of Hospital
Location
Performance † Tier
48,841 60,120 66,791 93,606 172,686 230,717 75,262 77,572 111,066 119,529 74,708 61,271 71,695 152,213 131,318
Nonteaching Nonteaching Teaching Nonteaching Teaching Teaching Nonteaching Teaching Teaching Nonteaching Nonteaching Nonteaching Nonteaching Nonteaching Nonteaching
Suburban Suburban Urban Suburban Urban Urban Rural Urban Urban Suburban Suburban Suburban Suburban Suburban Suburban
Lowest Lowest Lowest Lowest Lowest Lowest Middle Middle Middle Middle Highest Highest Highest Highest Highest
*Annual ED visits to the Trust reported to the Department of Health (2008).14 † Performance tier for 2007, latest data at start of study.14
Left in ≤ 4 hours Attendances
Radiology
Admissions
Laboratory Return visits Death in ED
Figure 1. Percentage of patients with each outcome of interest (left y axis) and the change (right y axis) in patient visits between 2003 and 2006 at the 15 participating Trusts.
decreased slightly but did not change significantly over time (annual change ⫺0.19%; 95% CI ⫺0.44% to 0.06%). The percentage of patients treated who left the ED within 4 hours increased by 19%, from 84.9% (95% CI 80.1% to 89.8%) to 96.4% (95% CI 94.5% to 98.3%) during the 4 years (Figure 1; Table 2). The percentage of patients leaving within 4 hours ranged among sites from 66% to 96% in 2003 and 85% to 99% in 2006 (Figure 2). From 2003 to 2006, the percentage of patients admitted to the hospital from the ED was unchanged overall and in both young and elderly (Figure 2; Table 2). From 2003 to 2006, the percentage of patients undergoing blood tests increased from 13.8% to 19.8%, but the annual change was not significant for the group as a whole or for those older than 65 years (Table 2). Overall, radiologic imaging decreased slightly; however, after adjustment this decrease was Annals of Emergency Medicine 701
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Table 2. Length of stay, admissions, resource use, and return visits during the study. Variable
2003
2004
Demographics Patient visits (May and June) Arriving by ambulance, % Patients ⱖ65 y, % Treated in 4 h, % † Length of ED stay (95% CI), min
171,988 27.8 (24.5 to 31.2) 19.9 (17.9 to 21.9) 84.9 (80.1 to 89.8) 136 (125 to 146)
195,639 27.1 (24.4 to 29.8) 19.7 (17.7 to 21.6) 90.6 (87.7 to 93.4) ⫺21.4 (⫺22.1 to ⫺20.6)
Laboratory tests and radiology, % Laboratory tests, all Young Elderly (ⱖ65 y) Radiologic study, all Young Elderly (ⱖ65 y) CT scan, all Young Elderly (ⱖ65 y) ECG Young Elderly (ⱖ65 y)
13.8 (11.4 to 16.3) 9.6 (8.0 to 11.2) 31.1 (24.7 to 37.6) 38.0 (32.1 to 43.9) 35.6 (30.1 to 41.1) 49.1 (40.3 to 57.9) 1.35 (0.93 to 1.76) 1.32 (0.90 to 1.74) 1.55 (1.09 to 2.01) 10.2 (7.6 to 12.8) 6.0 (4.4 to 7.6) 27.3 (20.3 to 34.2)
15.7 (12.8 to 18.6) 11.4 (9.1 to 13.7) 34.4 (27.8 to 41.0) 36.5 (31.4 to 41.6) 34.2 (29.6 to 38.7) 47.1 (38.8 to 55.3) 1.20 (0.89 to 1.51) 1.12 (0.84 to 1.40) 1.75 (1.02 to 2.49) 10.8 (8.5 to 13.1) 6.4 (5.0 to 7.8) 29.0 (22.9 to 35.1)
Disposition from ED, % Admitted to hospital, all Young Elderly (ⱖ65 y) Died in ED Young Elderly (ⱖ65 y)
23.2 (19.9 to 26.5) 16.4 (14.0 to 18.7) 50.9 (45.5 to 56.3) 0.24 (0.19 to 0.28) 0.13 (0.08 to 0.17) 0.78 (0.63 to 0.93)
23.6 (20.5 to 26.7) 17.2 (14.7 to 19.7) 50.9 (45.6 to 56.1) 0.19 (0.16 to 0.22) 0.09 (0.07 to 0.11) 0.64 (0.52 to 0.75)
6.23 (4.68 to 7.77) 6.62 (4.92 to 8.32) 4.65 (3.87 to 5.42) 29.9 (18.5 to 41.3) 27.8 (15.2 to 40.4) 43.4 (34.5 to 52.3)
5.86 (4.78 to 6.94) 6.12 (4.88 to 7.36) 5.10 (4.39 to 5.80) 35.3 (22.9 to 47.6) 31.2 (18.6 to 43.7) 52.9 (38.6 to 67.2)
119 (70 to 196) 122 (74 to 194)
106 (62 to 171) 116 (68 to 176)
Return visits (nⴝ241,030), % Return visits within 1 wk, all Young Elderly (ⱖ65 y) Return visits ending in admission Young Elderly (ⱖ65 y) Return visits: time in department for original visit, median (IQR), min Did not return within 1 wk Returned within 1 wk
—, Not applicable. *The majority of hospitals coded this only when patients had arrived by ambulance. † Value for 2003 is the estimated value, whereas for the other years it is the change relative to this value. ‡ Comparison between individuals who did not return and those who returned within 1 week.
not significant for all patients (annual change ⫺0.60%) or among the elderly subgroup (annual change 0.46%) (Table 2). CT use increased from 1.35% to 1.47% of all patients and from 1.55% to 2.72% of elderly patients, although this increase was not statistically significant. Frequency of ECGs increased among the elderly but did not reach statistical significance. Deaths in the ED were rare events and remained unchanged across the 4-year period (Table 2). Seven departments provided unique patient identifiers; therefore, only data from these departments were included in the return visit analysis. Among the 241,030 visits in these departments, the percentage of patients returning to the ED within 1 week did not change significantly over time (Figure 1; Table 2). Return visits resulting in hospital admission initially 702 Annals of Emergency Medicine
increased and then decreased to below the 2003 level for both young and elderly patients (Table 2). Patients who returned to the ED within 1 week had a significantly longer length of stay on their initial visit than did those who did not return, although this was by an average of only 6.5 minutes (Table 2). A number of similar process changes had been implemented in the EDs visited during the qualitative portion of the study (Figure 3). Intake processes were streamlined to eliminate unnecessary delays to a physician. Most of the departments had empowered nurses to order and collect laboratory tests, ECGs, and radiographs early after patient arrival before a clinician was seen. Hours of coverage by emergency medicine consultants (attending physicians), as well as nurse practitioners, were expanded. All sites visited had established Volume , . : December
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Table 2. Continued. 2005
2006
Missing Data, %
Estimated Annual Change in Percentage (95 CI)
200,171 26.6 (23.7 to 29.6) 19.7 (17.6 to 21.7) 95.4 (93.5 to 97.3) ⫺29.9 (⫺30.6 to ⫺29.1)
204,727 25.8 (22.9 to 28.7) 19.1 (17.4 to 20.9) 96.4 (94.5 to 98.3) ⫺28.1 (⫺28.8 to ⫺27.4)
— * 0.3 4.8 4.8
⫺0.80 (⫺1.48 to –0.12) ⫺0.19 (⫺0.44 to 0.06) 3.99 (2.43 to 5.56) —
17.3 (13.3 to 21.3) 12.7 (9.8 to 15.6) 37.0 (27.8 to 46.1) 35.3 (30.6 to 40.1) 32.6 (28.6 to 36.7) 47.6 (39.4 to 55.7) 1.74 (1.32 to 2.15) 1.43 (1.10 to 1.75) 3.12 (2.29 to 3.94) 13.2 (9.3 to 17.0) 8.7 (5.9 to 11.4) 32.4 (23.1 to 41.6)
19.8 (16.5 to 23.2) 14.5 (11.9 to 17.1) 42.5 (35.2 to 49.8) 35.7 (31.6 to 39.8) 33.1 (29.8 to 36.4) 49.4 (40.7 to 58.1) 1.47 (1.14 to 1.81) 1.21 (0.94 to 1.49) 2.72 (2.07 to 3.37) 13.7 (10.9 to 16.6) 8.5 (6.6 to 10.5) 35.8 (27.9 to 43.8)
19.6 20.1 17.3 13.2 13.5 11.6 13.5 13.9 11.9 19.9 20.5 17.6
1.00 (⫺0.09 to 2.08) 0.72 (⫺0.16 to 1.60) 2.22 (⫺0.07 to 4.51) ⫺0.60 (⫺1.58 to 0.37) ⫺0.88 (⫺1.81 to 0.05) 0.46 (⫺0.82 to 2.74) 0.14 (⫺0.16 to 0.44) 0.08 (⫺0.16 to 0.32) 0.33 (⫺0.25 to 0.92) 0.44 (⫺0.46 to 1.34) 0.25 (⫺0.50 to 1.00) 1.35 (⫺0.79 to 3.50)
24.5 (21.4 to 27.6) 17.8 (15.2 to 20.4) 52.9 (47.8 to 58.0) 0.22 (0.18 to 0.26) 0.09 (0.08 to 0.11) 0.82 (0.63 to 1.00)
22.8 (19.9 to 25.6) 16.5 (14.2 to 18.8) 50.4 (45.3 to 55.5) 0.18 (0.15 to 0.21) 0.07 (0.05 to 0.09) 0.71 (0.58 to 0.83)
2.6 2.6 2.7 — — —
0.34 (⫺0.43 to 1.11) 0.37 (⫺0.25 to 0.99) 0.23 (⫺1.18 to 1.64) ⫺0.02 (⫺0.06 to 0.02) ⫺0.01 (⫺0.04 to 0.02) ⫺0.05 (⫺0.18 to 0.07)
5.55 (4.62 to 6.48) 5.71 (4.71 to 6.71) 5.03 (4.25 to 5.80) 33.0 (24.1 to 42.0) 28.6 (19.1 to 38.1) 52.8 (41.8 to 63.9)
5.98 (5.15 to 6.80) 6.09 (5.30 to 6.87) 5.63 (4.58 to 6.67) 24.9 (20.0 to 29.9) 20.3 (16.4 to 24.2) 45.3 (37.2 to 53.3)
— — — — — —
117 (69 to 180) 123 (76 to 187)
115 (68 to 178) 125 (75 to 189)
— —
0.02 (⫺1.53 to 1.56) 0.09 (⫺1.56 to 1.75) ⫺0.25 (⫺1.32 to 0.82) ⫺3.10 (⫺7.32 to 1.11) ⫺1.68 (⫺4.72 to 1.37) ⫺7.09 (⫺16.11 to 1.92) Mean difference (min) ‡ Reference 6.55 (4.6 to 8.43)
a clinical decision unit. These are areas in which patients unlikely to need admission but requiring more observation or tests than could be completed in 4 hours can be evaluated “off the clock.”
LIMITATIONS This study is limited to 15 EDs in England, but these demonstrated a range of performance on the target, as well as location and type of hospital. Therefore, we have no reason to suspect that our findings cannot be generalized to other Acute Hospital Trusts in England. Moreover, our estimates of admission rates for these years are consistent with Department of Health data for the entire country for these and subsequent years.22,23 Only some of the participating departments provided Volume , . : December
us with unique identifiers, despite our having approval for obtaining this information; this limited the size of the analysis on return visits. Additionally, lack of integrated information technology systems and electronic medical records meant that some data (such as time of departure) was hand entered by staff and some investigations may not have been recorded. However, if anything, we would have expected improved capture of activities over the years as information technology systems developed. Our results are limited to outcomes that could be determined with administrative data and address outcomes for the ED only. There may be quality problems not captured by these data. Using only the data available from these departments, we were unable to evaluate the incidence of deaths after Annals of Emergency Medicine 703
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Figure 2. Percentage of patients discharged within 4 hours at each of the 15 Trusts between 2003 and 2006.
discharge from the ED or the quality of care for emergency patients once admitted to the hospital. In our qualitative interviews, ED staff worried that admitted patients might be sent to wards that were either inappropriate or unable to provide timely care.21 Further study of these aspects of a time target for EDs is needed.
DISCUSSION To our knowledge, ours is the first study using patient-level data to evaluate a comprehensive set of outcomes for the quality of ED care under England’s 4-hour target. For the Trusts in this study, the target did not result in more admissions, unplanned return visits within 1 week, or ED deaths. Moreover, resource use did not change, suggesting that investigations were not substituted for observation and that patient evaluations were not being deferred to inpatient or outpatient settings to save time. These findings were true regardless of patient age. Health care targets and performance measures are increasingly being used to improve quality and decrease costs, yet they are the subject of much debate.22,24-32 Critics warn of the potential for cheating, effort substitution (in which the activity being measured takes precedence over other equally valuable efforts), distortion of priorities (the patient waiting the longest receives the intervention instead of the one with the most acute need) or simply improving the figures but not the care. Indeed, targets do not always have their intended effects. The pneumonia antibiotic-timing core measure in the United States resulted in overt gaming and subtle changes in practice, with questionable benefit.29,33 In England, an 8-minute ambulance arrival target did not improve outcomes of patients accessing the out-of-hospital system, and a waiting time target for patients with bladder cancer did not result in earlier treatment.34,35 With regard to England’s 4-hour emergency target, evidence of digit preference bias in recorded discharge times and a spike in the number of patients recorded as leaving the department in the last 704 Annals of Emergency Medicine
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20 minutes have raised suspicion of cheating.27,28,36-38 On the other hand, a study from Harvard’s Kennedy School of Government found no evidence of gaming or effort substitution under the 4-hour target.22 A cynical interpretation of our results is that outcomes did not change substantially because the target in reality was not met. Indeed, in the early years of the target there were widespread anecdotal accounts of patients being moved to a “stop the clock” area, separated from the ED only by a line on the floor.13 A more likely explanation, however, and one supported by our mixed-methods approach, is that EDs and to some extent— but with less dispatch—the wider Trust made substantial process changes to meet the target and reduce crowding.21 In our previously published qualitative interviews, emergency staff reported determination to provide the same value-added care as before the target and avoid slipping into a mode of deferring evaluation and treatment to alternate sites that were not the focus of the mandate. As we observed, they accomplished this by reorganizing processes to improve flow, speed decisionmaking, and allow extended observation for patients likely to be discharged. Arguably, the target had its greatest effect on flow by putting pressure on wards to promptly receive admitted ED patients waiting for inpatient beds, eliminating (to a large extent) a major contributor to ED crowding, the “boarding” of admitted patients.21 Combining our interviews and observations with the data presented in this study suggests that with appropriate safeguards and a desire to do the right thing, the unintended consequences of targets can be minimized. As in the rest of England, the Trusts in this study significantly improved performance but only some were able to
Process Changes Made within UK EDs Streaming: Separate tracks for Majors (patients arriving by ambulance and walk-in patients with high-risk complaints) and Minors (all other ambulatory patients) See and Treat: Patients see only one provider who can provide definitive care, often nurse practitioner or a registrar. Eliminating formal triage: Walk-in patients do not automatically undergo formal triage acuity scoring. Nurses selectively assess patients to rule out a serious condition, or provide pain medication, or if the wait will be too long for a provider. "Minors" are seen in order of arrival. Investigations on arrival: Ambulance patients and other "Majors" have laboratories ordered on arrival, at the discretion of the nurse before the doctor sees them. Increased senior supervision: The number of emergency medicine Consultants and their time in the department increased. Increased coverage by advanced level nursing (nurse practitioners). Clinical Decision Units: Patients likely to be discharged, but needing more observation, or advanced testing (e.g. troponin, stress test, ultrasound) can be sent to these units to undergo further evaluation off the clock. In most places, they remain under the care of the emergency department.
Figure 3. Processes commonly implemented to meet the 4-hour target at the 9 departments visited in the qualitative portion of the study. Volume , . : December
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reach the 98% mark. And although quality of ED care appears to be comparable before and during the target, we cannot provide evidence that care improved, which, given the significant financial and emotional investment, one might reasonably expect. In April 2011, after a change in government, the Secretary of State for Health abandoned the 4-hour target in favor of a “dashboard of quality indicators” for EDs. These were developed in conjunction with the UK College of Emergency Medicine.39 The change in emphasis resulted from a combination of concerns that process measures were not good indicators of quality, and a more political objective of dismantling the “target culture” of the previous Labor government.40 Time remains an indicator within this new dashboard, but the 4-hour target has been reduced to require 95% of patients being seen and treated within this period. (The United Kingdom’s College of Emergency Medicine had long argued for a threshold of 95% to ensure patient safety, as well as success in meeting the target.) Our data demonstrate that targets can have value in addressing otherwise insoluble issues. Targets are implemented in a top-down fashion, giving providers little choice but to make them work despite competing interests within the various parts of the organization.21,41,42 The 4-hour target raised the profile of ED patients and ended the practice of boarding admitted patients, something that was beyond the ED’s control. Although the target caused massive upheaval within the National Health Service, most emergency physicians do not want to go back to the “bad old days.”21 Since the changes in the target were first announced by the Coalition government, time patients spend in the ED has increased.20 In summary, according to the data examined, the 4-hour target did not result in poorer quality of ED care. The effect on quality (or lack of it) is likely related to processes EDs implemented to guard against inadequate evaluation and unnecessary admissions. We conclude that targets per se may not be harmful as long as they remain focused on the patient. The authors acknowledge Michael Campbell, PhD, Angela Carter, PhD, and Ruth L. Hew, MD, for contributions to the analysis of the data and all the departments that participated in the quantitative and qualitative portions of the study. Supervising editor: Robert L. Wears, MD, PhD Author contributions: EJW and SM were responsible for study conception, design, and supervision. EJW, SM, and JC were responsible for data collection. JC was responsible for data cleaning. All authors were responsible for coding. JVF and JC were responsible for statistical analysis. All authors were responsible for the design of the Tables. EJW and JVF were responsible for production of the Figures. All authors were responsible for data interpretation and drafting, revision, and finalizing of the article. All authors had full access to all the data (including statistical reports and tables) in the study and take responsibility for the integrity of the data and the Volume , . : December
accuracy of the data analysis. EJW takes responsibility for the paper as a whole. Funding and support: By Annals policy, all authors are required to disclose any and all commercial, financial, and other relationships in any way related to the subject of this article as per ICMJE conflict of interest guidelines (see www.icmje.org). Dr. Weber and Dr. Mason are members of the 2 professional societies that provided partial support for this study. They have no other affiliations with the sponsors. This study was supported by grants from the BUPA Foundation, the Society for Academic Emergency Medicine (United States), and the College of Emergency Medicine (United Kingdom). The study sponsors had no role in design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the article. Publication dates: Received for publication February 6, 2012. Revisions received May 5, 2012, and July 31, 2012. Accepted for publication August 6, 2012. Presented as an abstract at the Society for Academic Emergency Medicine Annual Meeting, June 2011, Boston, MA; and as a poster at the UK College of Emergency Medicine Scientific Meeting, September 2011, Newcastle-on-Tyne. Dr. Callaham recused himself from the decisionmaking process. Address for correspondence: Ellen J. Weber, MD, E-mail [email protected].
REFERENCES 1. Diercks DB, Roe MT, Chen AY, et al. Prolonged emergency department stays of non-ST-segment-elevation myocardial infarction patients are associated with worse adherence to the American College of Cardiology/American Heart Association guidelines for management and increased adverse events. Ann Emerg Med. 2007;50:489-496. 2. Fee C, Weber EJ, Maak CA, et al. Effect of emergency department crowding on time to antibiotics in patients admitted with community-acquired pneumonia. Ann Emerg Med. 2007;50:501509, 509.e501. 3. Pines JM, Hollander JE, Localio AR, et al. The association between emergency department crowding and hospital performance on antibiotic timing for pneumonia and percutaneous intervention for myocardial infarction. Acad Emerg Med. 2006;13: 873-878. 4. Pines JM, Pollack CV Jr, Diercks DB, et al. The association between emergency department crowding and adverse cardiovascular outcomes in patients with chest pain. Acad Emerg Med. 2009;16:617-625. 5. Chalfin DB, Trzeciak S, Likourezos A, et al. Impact of delayed transfer of critically ill patients from the emergency department to the intensive care unit. Crit Care Med. 2007;35:1477-1483. 6. Moskop JC, Sklar DP, Geiderman JM, et al. Emergency department crowding, part 1— concept, causes, and moral consequences. Ann Emerg Med. 2009;53:605-611. 7. Richardson DB. Increase in patient mortality at 10 days associated with emergency department overcrowding. Med J Aust. 2006;184:213-216. 8. Schull MJ, Vermeulen M, Slaughter G, et al. Emergency department crowding and thrombolysis delays in acute myocardial infarction. Ann Emerg Med. 2004;44:577-585.
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England’s Four-Hour Target for Emergency Department Quality of Care 9. Guttmann A, Schull MJ, Vermeulen MJ, et al. Association between waiting times and short term mortality and hospital admission after departure from emergency department: population based cohort study from Ontario, Canada. BMJ. 2011;342:d2983. 10. Ontario Ministry of Health and Long-Term Care. Emergency room targets. 2009. Available at: http://www.health.gov.on.ca/en/pro/ programs/waittimes/edrs/targets.aspx. Accessed December 20, 2011. 11. Australian Government. A National Health and Hospitals Network: Further Investments in Australia’s Health. Department of Health and Ageing: Canberra, Australia; 2010. Available at: http://www. health.gov.au/internet/main/publishing.nsf/Content/nhhnreport-2/$File/NHHN%20Report%20two.pdf. Accessed August 28, 2012. 12. Pines JM, Hilton JA, Weber EJ, et al. International perspectives on emergency department crowding. Acad Emerg Med. 2011;18: 1358-1370. 13. Department of Health. The NHS Plan. A Plan for Investment. A Plan for Reform. London Stationery Office; 2000. Available at: http://www.dh.gov.uk/en/Publicationsandstatistics/Publications/ PublicationsPolicyAndGuidance/DH_4002960. Accessed December 22, 2011. 14. Department of Health. Clinical exceptions to the 4 hour emergency care target. 2003. Available at: http://www.dh.gov.uk/assetRoot/04/07/95/56/04079556.pdf. Accessed December 20, 2011. 15. New Zealand Ministry of Health. Shorter stays in ED health target. June 2011. Available at: http://www.health.govt.nz/ourwork/hospitals-and-specialist-care/emergency-departments/ shorter-stays-emergency-departments-health-target. Accessed December 14, 2011. 16. Kellermann AL. Crisis in the emergency department. N Engl J Med. 2006;355:1300-1303. 17. Centers for Medicare & Medicaid Services. Final Rule: Medicare Program; Hospital Inpatient Prospective Payment Systems for Acute Care Hospitals and the Long-Term Care Hospital Prospective Payment System and FY 2012 Rates; Hospitals’ FTE Resident Caps for Graduate Medical Education Payment. Washington, DC: Federal Register; 2011. [CMS-1518-F; CMS-1430-F]. Available at: http://www.cms.gov/AcuteInpatientPPS/FR2012/itemdetail.asp? filterType⫽none&filterByDID⫽-99&sortByDID⫽1&sortOrder⫽ ascending&itemID⫽CMS1250103&intNumPerPage⫽10. Accessed December 20, 2011. 18. Guly H, Higginson I. Obituary for the four-hour target. Emerg Med J. 2011;28:179-180. 19. College of Emergency Medicine. Abolition of the four hour waiting standard (July 2010). Available at: http://secure.collemergencymed. ac.uk/Development/Policy%20and%20Service%20Development/ Quality%20Indicators/. Accessed December 7, 2011. 20. Department of Health. Total time spent in accident and emergency. Available at: http://www.dh.gov.uk/en/Publicationsandstatistics/ Statistics/Performancedataandstatistics/AccidentandEmergency/ DH_079085. Accessed October 14, 2011. 21. Weber EJ, Mason S, Carter A, et al. Emptying the corridors of shame: organizational lessons from England’s 4-hour emergency throughput target. Ann Emerg Med. 2011;57:79-88.e71. 22. Kelman S, Friedman JN. Performance improvement and performance dysfunction: an empirical examination of distortionary impacts of the emergency room wait-time target in the English National Health Service. J Public Adm Res Theory. 2009;19:917-946. 23. Hospital Episode Statistics. Accident and emergency attendances in England (experimental statistics), 2009-2010. National Health Service Information Centre for Health and Social Care. Available
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at: http://www.hesonline.org.uk/Ease/ContentServer?siteID⫽ 1937&categoryID⫽1502. Accessed October 1, 2011. Bevan G. Have targets done more harm than good in the English NHS? No. BMJ. 2009;338:a3129. Gubb J. Have targets done more harm than good in the English NHS? Yes. BMJ. 2009;338:a3130. Locker T, Mason S, Wardrope J, et al. Targets and moving goal posts: changes in waiting times in a UK emergency department. Emerg Med J. 2005;22:710-714. Locker TE, Mason SM. Analysis of the distribution of time that patients spend in emergency departments. BMJ. 2005;330:11881189. Locker TE, Mason SM. Are these emergency department performance data real? Emerg Med J. 2006;23:558-559. Wachter RM, Flanders SA, Fee C, et al. Public reporting of antibiotic timing in patients with pneumonia: lessons from a flawed performance measure. Ann Intern Med. 2008;149:29-32. Appleby J, Boyle S, Devlin N, et al. Do English NHS waiting time targets distort treatment priorities in orthopaedic surgery? J Health Serv Res Policy. 2005;10:167-172. Propper C, Sutton M, Whithall C, et al. Incentives and Targets in Hospital Care: Evidence From a Natural Experiment. Bristol: Centre for Market & Public Organisation, University of Bristol; 2008. Available at: http://www.bristol.ac.uk/cmpo/publications/ papers/2008/wp205.pdf. Accessed September 23, 2011. Cooke MW. Reforming the UK emergency care system. Emerg Med J. 2003;20:113-114. Nicks BA, Manthey DE, Fitch MT. The Centers for Medicare and Medicaid Services (CMS) community-acquired pneumonia core measures lead to unnecessary antibiotic administration by emergency physicians. Acad Emerg Med. 2009;16:184-187. Turner J, O’Keeffe C, Dixon S, et al. The costs and benefits of changing ambulance service response time performances. A report to the Department of Health. Sheffield: Medical Care Research Unit, University of Sheffield; 2006. Available at: http:// www.sheffield.ac.uk/mcru/reports.html. Accessed December 20, 2011. Blick C, Bailey D, Haldar N, et al. The impact of the two-week wait rule on the diagnosis and management of bladder cancer in a single UK institution. Ann R Coll Surg Engl. 2010;92:46-50. Bevan G, Hood C. What’s Measured Is What Matters: Targets and Gaming in the English Public Health Care System. Swindon: Economic & Social Research Council; 2005. Available at: http:// www.publicservices.ac.uk/wp-content/uploads/dp0501.pdf. Accessed July 24, 2011. Hughes G. Four hour target for EDs: the UK experience. Emerg Med Australas. 2010;22:368-373. Mason S, Weber EJ, Coster J, et al. Time patients spend in the emergency department: England’s 4-hour rule—a case of hitting the target but missing the point? Ann Emerg Med. 2012;59:341349. Department of Health. A&E clinical quality indicators: best practice guidance for local publication. June 23, 2011. Available at: http://www.dh.gov.uk/en/Publicationsandstatistics/ Publications/PublicationsPolicyAndGuidance/DH_127776. Accessed April 25, 2012. Department of Health. Abolition of the four-hour waiting standard in accident and emergency. June 21, 2010. Available at: http:// www.dh.gov.uk/en/Publicationsandstatistics/Lettersandcirculars/ Dearcolleagueletters/DH_116918. Accessed April 25, 2012. Ramanujam R, Rousseau D. The challenges are organizational not just clinical. J Organ Behav. 2006;27:811-827. Statt D. Group dynamics and working-group relationships. Psychology and the World of Work. Basingstoke: Palgrave; 1994: 122-139.
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Implications of England’s Four-Hour Target for Quality of Care and Resource Use in the Emergency Department Ellen J. Weber, MD, Suzanne Mason, MD, FRCS, Jennifer V. Freeman, PhD, Joanne Coster, MSc From the Department of Emergency Medicine, University of California, San Francisco, San Francisco, CA (Weber); and the School of Health and Related Research, University of Sheffield, Sheffield, United Kingdom (Mason, Freeman, Coster).
Study objective: In 2005, England implemented a controversial target limiting patient stays in the emergency department (ED) to 4 hours. We determine the effect of the “4-hour target” on quality of care and resource use. Methods: This was a retrospective study of 15 purposively sampled EDs in England, representing a range of performance on the target. The EDs provided administrative data on all visits for May and June, 2003 to 2006. These years spanned the period before the target until more than a year after full implementation. We assessed changes in admission rate, investigations, deaths in the ED, and return visits within 1 week for all patients and separately for those aged 65 years or older. Regression analyses adjusted for clustering at the hospital level and changes in acuity reflected by ambulance arrivals. Results are expressed as the estimated annual change in the percentage of patients experiencing the outcome, with 95% confidence intervals (CIs). Results: A total of 772,525 ED visits were analyzed; visits increased 19% during the 4-year period. Between 2003 and 2006, the percentage of patients arriving by ambulance decreased from 27.8% to 25.8% (annual change from 2003 ⫺0.80%; 95% CI for change: ⫺1.48% to ⫺0.12%). Visits by individuals aged 65 years or older were stable (19.9% to 19.1%; annual change ⫺0.19%; 95% CI for change ⫺0.44% to 0.06%). Between 2003 and 2006, admissions from the ED were unchanged, at 23% (95% CI for change ⫺0.43% to 1.11%). The percentage of patients receiving blood tests increased from 13.8% to 19.8% (annual change 1.00%; 95% CI for change ⫺0.09% to 2.08%). Frequency of radiologic studies decreased slightly, from 38.0% to 35.7% (annual change ⫺0.60%; 95% CI ⫺1.58% to 0.37%). Deaths in the ED and return ED visits within 1 week were unchanged. Return visits resulting in hospital admission increased initially and then returned to 2003 levels (annual change ⫺3.10%; 95% CI ⫺7.32% to 1.11%). Conclusion: England’s 4-hour target did not appear to have a negative effect on quality or safety of ED care and had little effect on test use. [Ann Emerg Med. 2012;60:699-706.] Please see page 700 for the Editor’s Capsule Summary of this article. A feedback survey is available with each research article published on the Web at www.annemergmed.com. A podcast for this article is available at www.annemergmed.com. 0196-0644/$-see front matter Copyright © 2012 by the American College of Emergency Physicians. http://dx.doi.org/10.1016/j.annemergmed.2012.08.009
INTRODUCTION Emergency department (ED) crowding is an international problem, with well-documented negative influences on quality and safety of care.1-12 In 2005, England instituted an emergency care target, setting a maximum limit on the length of stay of 4 hours from time of arrival to discharge home or moving to an inpatient bed.13,14 Australia, New Zealand, and parts of Canada have since followed suit with targets of 4 to 8 hours.10,11,15 In the United States, where crowding has been labeled a “crisis” for years, the Centers for Medicare & Medicaid Services is just beginning to monitor ED length of stay.16,17 Although potentially speeding ED patient flow and reducing waits for physician evaluation or admission, a focus on time risks causing perverse consequences. Emergency physicians could simply choose to admit patients rather than attempt to evaluate them within the 4-hour Volume , . : December
window, resulting in more admissions. In addition, the number of laboratory tests and radiographs might increase as a substitute for a period of observation, and ED deaths or return visits might increase because of incomplete evaluations, diagnostic errors, or insufficient discharge instructions and follow-up arrangements as providers keep an eye on the clock. In 2011, England’s coalition government de-emphasized the 4-hour target in favor of quality measures.18,19 Yet the target was never formally evaluated. We therefore conducted a study to evaluate how quality of care and resource use was affected by the 4-hour target.
MATERIALS AND METHODS This quantitative analysis is part of a mixed-methods study conducted between June 2008 and April 2010, designed to Annals of Emergency Medicine 699
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Editor’s Capsule Summary
What is already known on this topic In 2005, the English government required 98% of emergency department (ED) visits have door-todeparture time of less than 4 hours, but no quality or resource assessment accompanied the measure. What question this study addressed In a purposive sample of 15 English EDs, what happened to admissions, laboratory and imaging investigations, deaths in the ED, and return visits before and after imposition of the target? What this study adds to our knowledge ED length of stay improved during this period, although only some EDs actually met the target for 98% of patients. Patient outcomes and measures of utilization did not change appreciably. How this is relevant to clinical practice Implementation of external targets alone does not alter ED quality of care or resource use.
determine the effect of the 4-hour target on organizational behavior and patient outcomes. The study was approved by the Ethics Committee of the National Health Service (REC08/H0206/16) and the R&D offices of all Trusts involved. Setting In 2005, the National Health Service in England imposed a target that 98% of all ED patients must be seen, treated, and either discharged home or admitted to an inpatient ward within 4 hours.13,14 The target was announced in 2003 and gradually implemented with increasing thresholds for compliance during 2004 until reaching the 98% threshold on January 1, 2005. Acute Trusts (hospitals) received a financial incentive for meeting each threshold, with the last payment in early 2005. Notably, the leadership of the Trust—not the ED—was held accountable to the Health Ministry for meeting the target. For approximately the next 5 years, Trusts reported that 96% to 98% of ED patients had lengths of stay of 4 hours or less, although the 98% threshold was met consistently in less than half of EDs. Selection of Participants Using published data for performance on the target from the third quarter of 2007, we sorted all Acute Trusts in England into high, middle, and low performers.20 From each performance tier, we selected 12 Trusts spanning the range of size, hospital type, and geographic location within England. Lead clinicians from EDs in these Trusts were contacted by 700 Annals of Emergency Medicine
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letter and asked to participate in the data collection part of the study. One reply indicated that the Trust did not have a Level I ED, resulting in invitations to a total of 35 departments. Twenty EDs agreed to participate. Data Collection and Processing Information technology personnel from participating EDs were asked to provide routine patient-level data for all patients attending their department in May and June 2003 to 2006 inclusive. The study years represented the interval from the announcement of the target to 1.5 years after its establishment at the 98% threshold; the months were selected to avoid major holidays and quarterly changeovers of junior physicians. The following data fields were requested: unique identifier (National Health Service number or hospital number), date and time of arrival, date of birth (or age), sex, mode of arrival, presenting complaint, investigations (laboratories and ECGs) and imaging performed in the ED, disposition, diagnosis, and date and time of leaving the department. Methodological details and results of the qualitative aspect of the mixed-methods study have been reported previously.21 Briefly, investigators visited 9 of the 20 consenting sites, conducting interviews with ED leadership and observing the department’s operations. Information about changes made in the department obtained from interviews and observation was used in interpreting the quantitative results presented here. Outcome Measures Outcomes of interest were changes over time in the following areas: (1) percentage of patients admitted to the hospital from the ED; (2) percentage of patients undergoing laboratory testing, ECG, or imaging in the ED; (3) percentage of patients who died in the ED; (4) percentage of patients discharged from the ED who returned within 1 week and, within this group, the percentage of return visits that resulted in hospital admission. We selected these outcomes as proxies of quality, safety, and resource use that could be obtained from routine data. To distinguish any differential effect on older patients who might have more complex or subtle illnesses, we performed subgroup analyses on the same endpoints for patients 65 years and older. The proportion of patients who left the ED (for a hospital bed, discharge, or transfer) within 4 hours was calculated to determine whether performance on the target improved over time. Primary Data Analysis Duplicate visit entries were identified by using hospital number, patient identification, date, and time of arrival and were deleted from the data file. The following variables were categorized and coded to ensure uniformity across the departments: age, mode of arrival, disposition, and whether the patient underwent any laboratory, ECG, or radiology studies (coded separately). Most hospitals did not distinguish among patients who may have spent time in an ED’s clinical decision Volume , . : December
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unit, and therefore only final disposition was considered. The time each patient spent in the ED was defined as the time from registration until leaving the department, with the date or time of admission and the date or time of discharge. Patients who were dead on arrival were excluded and patients with missing data for a particular element (eg, time of arrival) were excluded for that particular analysis. The unique identifier was used to count the number of patients at each site who had 1 or more return visits within 1 week. We chose this interval because a return visit within 1 week is likely to be related to the presenting problem on the initial visit. For the categorical, binary outcomes such as percentage treated within 4 hours, a hospital-level analysis was conducted. To estimate the average effect for each year, data were combined across all hospitals, with analytic weights proportional to hospital size. These annual effects were tabulated, together with their 95% confidence intervals (CIs). To examine whether there was any change during the study period, a linear regression was conducted on the data for each hospital, with year as the predictor variable. Because there was evidence that the proportion of ambulance arrivals changed over time, this variable was included as a factor in the linear regression. Each regression produced estimates of the expected change during the study period in that hospital. To assess whether there was a change during the study period, these estimates were analyzed with a 1-sample t test. Analytic weights proportional to hospital size were applied to each hospital coefficient to allow for the differences in hospital size. The results are presented as the average change in the percentage of patients experiencing this outcome during the study period, together with 95% CIs. Length of stay in the department was investigated with a random-effects regression model, with hospital fitted as a random effect to adjust for clustering at the hospital level and ambulance arrival fitted as a factor. For time to discharge, the baseline value at 2003 is given, whereas for the following years, the value is the change relative to this baseline. Data analysis was performed with SAS (version 9.2; SAS Institute, Inc., Cary, NC) and Stata (version 10; StataCorp, College Station, TX).
RESULTS Of the 20 EDs agreeing to participate, 3 were unable to accumulate and submit the data, and 1 failed to reply after numerous contacts. One hospital was able to supply data for only 2005 and 2006 and so could not be included in this analysis. The 15 remaining Trusts were evenly distributed with regard to their performance on the target and represented a range of teaching and nonteaching hospitals and location (Table 1). A total of 772,525 visits were analyzed. ED visits for May and June increased 19% during the 4 years, from 171,988 in 2003 to 204,727 in 2006 (Figure 1; Table 2). The percentage of patients arriving by ambulance decreased from 27.8% to 25.8% during the 4 years (annual change ⫺0.80%; 95% CI ⫺1.48% to ⫺0.12%); the proportion of patients aged 65 years or older Volume , . : December
Table 1. Characteristics of hospitals included in the study. Hospital 10 14 8 4 12 6 13 9 3 5 7 15 2 1 11
ED Visits*
Type of Hospital
Location
Performance † Tier
48,841 60,120 66,791 93,606 172,686 230,717 75,262 77,572 111,066 119,529 74,708 61,271 71,695 152,213 131,318
Nonteaching Nonteaching Teaching Nonteaching Teaching Teaching Nonteaching Teaching Teaching Nonteaching Nonteaching Nonteaching Nonteaching Nonteaching Nonteaching
Suburban Suburban Urban Suburban Urban Urban Rural Urban Urban Suburban Suburban Suburban Suburban Suburban Suburban
Lowest Lowest Lowest Lowest Lowest Lowest Middle Middle Middle Middle Highest Highest Highest Highest Highest
*Annual ED visits to the Trust reported to the Department of Health (2008).14 † Performance tier for 2007, latest data at start of study.14
Left in ≤ 4 hours Attendances
Radiology
Admissions
Laboratory Return visits Death in ED
Figure 1. Percentage of patients with each outcome of interest (left y axis) and the change (right y axis) in patient visits between 2003 and 2006 at the 15 participating Trusts.
decreased slightly but did not change significantly over time (annual change ⫺0.19%; 95% CI ⫺0.44% to 0.06%). The percentage of patients treated who left the ED within 4 hours increased by 19%, from 84.9% (95% CI 80.1% to 89.8%) to 96.4% (95% CI 94.5% to 98.3%) during the 4 years (Figure 1; Table 2). The percentage of patients leaving within 4 hours ranged among sites from 66% to 96% in 2003 and 85% to 99% in 2006 (Figure 2). From 2003 to 2006, the percentage of patients admitted to the hospital from the ED was unchanged overall and in both young and elderly (Figure 2; Table 2). From 2003 to 2006, the percentage of patients undergoing blood tests increased from 13.8% to 19.8%, but the annual change was not significant for the group as a whole or for those older than 65 years (Table 2). Overall, radiologic imaging decreased slightly; however, after adjustment this decrease was Annals of Emergency Medicine 701
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Table 2. Length of stay, admissions, resource use, and return visits during the study. Variable
2003
2004
Demographics Patient visits (May and June) Arriving by ambulance, % Patients ⱖ65 y, % Treated in 4 h, % † Length of ED stay (95% CI), min
171,988 27.8 (24.5 to 31.2) 19.9 (17.9 to 21.9) 84.9 (80.1 to 89.8) 136 (125 to 146)
195,639 27.1 (24.4 to 29.8) 19.7 (17.7 to 21.6) 90.6 (87.7 to 93.4) ⫺21.4 (⫺22.1 to ⫺20.6)
Laboratory tests and radiology, % Laboratory tests, all Young Elderly (ⱖ65 y) Radiologic study, all Young Elderly (ⱖ65 y) CT scan, all Young Elderly (ⱖ65 y) ECG Young Elderly (ⱖ65 y)
13.8 (11.4 to 16.3) 9.6 (8.0 to 11.2) 31.1 (24.7 to 37.6) 38.0 (32.1 to 43.9) 35.6 (30.1 to 41.1) 49.1 (40.3 to 57.9) 1.35 (0.93 to 1.76) 1.32 (0.90 to 1.74) 1.55 (1.09 to 2.01) 10.2 (7.6 to 12.8) 6.0 (4.4 to 7.6) 27.3 (20.3 to 34.2)
15.7 (12.8 to 18.6) 11.4 (9.1 to 13.7) 34.4 (27.8 to 41.0) 36.5 (31.4 to 41.6) 34.2 (29.6 to 38.7) 47.1 (38.8 to 55.3) 1.20 (0.89 to 1.51) 1.12 (0.84 to 1.40) 1.75 (1.02 to 2.49) 10.8 (8.5 to 13.1) 6.4 (5.0 to 7.8) 29.0 (22.9 to 35.1)
Disposition from ED, % Admitted to hospital, all Young Elderly (ⱖ65 y) Died in ED Young Elderly (ⱖ65 y)
23.2 (19.9 to 26.5) 16.4 (14.0 to 18.7) 50.9 (45.5 to 56.3) 0.24 (0.19 to 0.28) 0.13 (0.08 to 0.17) 0.78 (0.63 to 0.93)
23.6 (20.5 to 26.7) 17.2 (14.7 to 19.7) 50.9 (45.6 to 56.1) 0.19 (0.16 to 0.22) 0.09 (0.07 to 0.11) 0.64 (0.52 to 0.75)
6.23 (4.68 to 7.77) 6.62 (4.92 to 8.32) 4.65 (3.87 to 5.42) 29.9 (18.5 to 41.3) 27.8 (15.2 to 40.4) 43.4 (34.5 to 52.3)
5.86 (4.78 to 6.94) 6.12 (4.88 to 7.36) 5.10 (4.39 to 5.80) 35.3 (22.9 to 47.6) 31.2 (18.6 to 43.7) 52.9 (38.6 to 67.2)
119 (70 to 196) 122 (74 to 194)
106 (62 to 171) 116 (68 to 176)
Return visits (nⴝ241,030), % Return visits within 1 wk, all Young Elderly (ⱖ65 y) Return visits ending in admission Young Elderly (ⱖ65 y) Return visits: time in department for original visit, median (IQR), min Did not return within 1 wk Returned within 1 wk
—, Not applicable. *The majority of hospitals coded this only when patients had arrived by ambulance. † Value for 2003 is the estimated value, whereas for the other years it is the change relative to this value. ‡ Comparison between individuals who did not return and those who returned within 1 week.
not significant for all patients (annual change ⫺0.60%) or among the elderly subgroup (annual change 0.46%) (Table 2). CT use increased from 1.35% to 1.47% of all patients and from 1.55% to 2.72% of elderly patients, although this increase was not statistically significant. Frequency of ECGs increased among the elderly but did not reach statistical significance. Deaths in the ED were rare events and remained unchanged across the 4-year period (Table 2). Seven departments provided unique patient identifiers; therefore, only data from these departments were included in the return visit analysis. Among the 241,030 visits in these departments, the percentage of patients returning to the ED within 1 week did not change significantly over time (Figure 1; Table 2). Return visits resulting in hospital admission initially 702 Annals of Emergency Medicine
increased and then decreased to below the 2003 level for both young and elderly patients (Table 2). Patients who returned to the ED within 1 week had a significantly longer length of stay on their initial visit than did those who did not return, although this was by an average of only 6.5 minutes (Table 2). A number of similar process changes had been implemented in the EDs visited during the qualitative portion of the study (Figure 3). Intake processes were streamlined to eliminate unnecessary delays to a physician. Most of the departments had empowered nurses to order and collect laboratory tests, ECGs, and radiographs early after patient arrival before a clinician was seen. Hours of coverage by emergency medicine consultants (attending physicians), as well as nurse practitioners, were expanded. All sites visited had established Volume , . : December
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Table 2. Continued. 2005
2006
Missing Data, %
Estimated Annual Change in Percentage (95 CI)
200,171 26.6 (23.7 to 29.6) 19.7 (17.6 to 21.7) 95.4 (93.5 to 97.3) ⫺29.9 (⫺30.6 to ⫺29.1)
204,727 25.8 (22.9 to 28.7) 19.1 (17.4 to 20.9) 96.4 (94.5 to 98.3) ⫺28.1 (⫺28.8 to ⫺27.4)
— * 0.3 4.8 4.8
⫺0.80 (⫺1.48 to –0.12) ⫺0.19 (⫺0.44 to 0.06) 3.99 (2.43 to 5.56) —
17.3 (13.3 to 21.3) 12.7 (9.8 to 15.6) 37.0 (27.8 to 46.1) 35.3 (30.6 to 40.1) 32.6 (28.6 to 36.7) 47.6 (39.4 to 55.7) 1.74 (1.32 to 2.15) 1.43 (1.10 to 1.75) 3.12 (2.29 to 3.94) 13.2 (9.3 to 17.0) 8.7 (5.9 to 11.4) 32.4 (23.1 to 41.6)
19.8 (16.5 to 23.2) 14.5 (11.9 to 17.1) 42.5 (35.2 to 49.8) 35.7 (31.6 to 39.8) 33.1 (29.8 to 36.4) 49.4 (40.7 to 58.1) 1.47 (1.14 to 1.81) 1.21 (0.94 to 1.49) 2.72 (2.07 to 3.37) 13.7 (10.9 to 16.6) 8.5 (6.6 to 10.5) 35.8 (27.9 to 43.8)
19.6 20.1 17.3 13.2 13.5 11.6 13.5 13.9 11.9 19.9 20.5 17.6
1.00 (⫺0.09 to 2.08) 0.72 (⫺0.16 to 1.60) 2.22 (⫺0.07 to 4.51) ⫺0.60 (⫺1.58 to 0.37) ⫺0.88 (⫺1.81 to 0.05) 0.46 (⫺0.82 to 2.74) 0.14 (⫺0.16 to 0.44) 0.08 (⫺0.16 to 0.32) 0.33 (⫺0.25 to 0.92) 0.44 (⫺0.46 to 1.34) 0.25 (⫺0.50 to 1.00) 1.35 (⫺0.79 to 3.50)
24.5 (21.4 to 27.6) 17.8 (15.2 to 20.4) 52.9 (47.8 to 58.0) 0.22 (0.18 to 0.26) 0.09 (0.08 to 0.11) 0.82 (0.63 to 1.00)
22.8 (19.9 to 25.6) 16.5 (14.2 to 18.8) 50.4 (45.3 to 55.5) 0.18 (0.15 to 0.21) 0.07 (0.05 to 0.09) 0.71 (0.58 to 0.83)
2.6 2.6 2.7 — — —
0.34 (⫺0.43 to 1.11) 0.37 (⫺0.25 to 0.99) 0.23 (⫺1.18 to 1.64) ⫺0.02 (⫺0.06 to 0.02) ⫺0.01 (⫺0.04 to 0.02) ⫺0.05 (⫺0.18 to 0.07)
5.55 (4.62 to 6.48) 5.71 (4.71 to 6.71) 5.03 (4.25 to 5.80) 33.0 (24.1 to 42.0) 28.6 (19.1 to 38.1) 52.8 (41.8 to 63.9)
5.98 (5.15 to 6.80) 6.09 (5.30 to 6.87) 5.63 (4.58 to 6.67) 24.9 (20.0 to 29.9) 20.3 (16.4 to 24.2) 45.3 (37.2 to 53.3)
— — — — — —
117 (69 to 180) 123 (76 to 187)
115 (68 to 178) 125 (75 to 189)
— —
0.02 (⫺1.53 to 1.56) 0.09 (⫺1.56 to 1.75) ⫺0.25 (⫺1.32 to 0.82) ⫺3.10 (⫺7.32 to 1.11) ⫺1.68 (⫺4.72 to 1.37) ⫺7.09 (⫺16.11 to 1.92) Mean difference (min) ‡ Reference 6.55 (4.6 to 8.43)
a clinical decision unit. These are areas in which patients unlikely to need admission but requiring more observation or tests than could be completed in 4 hours can be evaluated “off the clock.”
LIMITATIONS This study is limited to 15 EDs in England, but these demonstrated a range of performance on the target, as well as location and type of hospital. Therefore, we have no reason to suspect that our findings cannot be generalized to other Acute Hospital Trusts in England. Moreover, our estimates of admission rates for these years are consistent with Department of Health data for the entire country for these and subsequent years.22,23 Only some of the participating departments provided Volume , . : December
us with unique identifiers, despite our having approval for obtaining this information; this limited the size of the analysis on return visits. Additionally, lack of integrated information technology systems and electronic medical records meant that some data (such as time of departure) was hand entered by staff and some investigations may not have been recorded. However, if anything, we would have expected improved capture of activities over the years as information technology systems developed. Our results are limited to outcomes that could be determined with administrative data and address outcomes for the ED only. There may be quality problems not captured by these data. Using only the data available from these departments, we were unable to evaluate the incidence of deaths after Annals of Emergency Medicine 703
England’s Four-Hour Target for Emergency Department Quality of Care
Figure 2. Percentage of patients discharged within 4 hours at each of the 15 Trusts between 2003 and 2006.
discharge from the ED or the quality of care for emergency patients once admitted to the hospital. In our qualitative interviews, ED staff worried that admitted patients might be sent to wards that were either inappropriate or unable to provide timely care.21 Further study of these aspects of a time target for EDs is needed.
DISCUSSION To our knowledge, ours is the first study using patient-level data to evaluate a comprehensive set of outcomes for the quality of ED care under England’s 4-hour target. For the Trusts in this study, the target did not result in more admissions, unplanned return visits within 1 week, or ED deaths. Moreover, resource use did not change, suggesting that investigations were not substituted for observation and that patient evaluations were not being deferred to inpatient or outpatient settings to save time. These findings were true regardless of patient age. Health care targets and performance measures are increasingly being used to improve quality and decrease costs, yet they are the subject of much debate.22,24-32 Critics warn of the potential for cheating, effort substitution (in which the activity being measured takes precedence over other equally valuable efforts), distortion of priorities (the patient waiting the longest receives the intervention instead of the one with the most acute need) or simply improving the figures but not the care. Indeed, targets do not always have their intended effects. The pneumonia antibiotic-timing core measure in the United States resulted in overt gaming and subtle changes in practice, with questionable benefit.29,33 In England, an 8-minute ambulance arrival target did not improve outcomes of patients accessing the out-of-hospital system, and a waiting time target for patients with bladder cancer did not result in earlier treatment.34,35 With regard to England’s 4-hour emergency target, evidence of digit preference bias in recorded discharge times and a spike in the number of patients recorded as leaving the department in the last 704 Annals of Emergency Medicine
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20 minutes have raised suspicion of cheating.27,28,36-38 On the other hand, a study from Harvard’s Kennedy School of Government found no evidence of gaming or effort substitution under the 4-hour target.22 A cynical interpretation of our results is that outcomes did not change substantially because the target in reality was not met. Indeed, in the early years of the target there were widespread anecdotal accounts of patients being moved to a “stop the clock” area, separated from the ED only by a line on the floor.13 A more likely explanation, however, and one supported by our mixed-methods approach, is that EDs and to some extent— but with less dispatch—the wider Trust made substantial process changes to meet the target and reduce crowding.21 In our previously published qualitative interviews, emergency staff reported determination to provide the same value-added care as before the target and avoid slipping into a mode of deferring evaluation and treatment to alternate sites that were not the focus of the mandate. As we observed, they accomplished this by reorganizing processes to improve flow, speed decisionmaking, and allow extended observation for patients likely to be discharged. Arguably, the target had its greatest effect on flow by putting pressure on wards to promptly receive admitted ED patients waiting for inpatient beds, eliminating (to a large extent) a major contributor to ED crowding, the “boarding” of admitted patients.21 Combining our interviews and observations with the data presented in this study suggests that with appropriate safeguards and a desire to do the right thing, the unintended consequences of targets can be minimized. As in the rest of England, the Trusts in this study significantly improved performance but only some were able to
Process Changes Made within UK EDs Streaming: Separate tracks for Majors (patients arriving by ambulance and walk-in patients with high-risk complaints) and Minors (all other ambulatory patients) See and Treat: Patients see only one provider who can provide definitive care, often nurse practitioner or a registrar. Eliminating formal triage: Walk-in patients do not automatically undergo formal triage acuity scoring. Nurses selectively assess patients to rule out a serious condition, or provide pain medication, or if the wait will be too long for a provider. "Minors" are seen in order of arrival. Investigations on arrival: Ambulance patients and other "Majors" have laboratories ordered on arrival, at the discretion of the nurse before the doctor sees them. Increased senior supervision: The number of emergency medicine Consultants and their time in the department increased. Increased coverage by advanced level nursing (nurse practitioners). Clinical Decision Units: Patients likely to be discharged, but needing more observation, or advanced testing (e.g. troponin, stress test, ultrasound) can be sent to these units to undergo further evaluation off the clock. In most places, they remain under the care of the emergency department.
Figure 3. Processes commonly implemented to meet the 4-hour target at the 9 departments visited in the qualitative portion of the study. Volume , . : December
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England’s Four-Hour Target for Emergency Department Quality of Care
reach the 98% mark. And although quality of ED care appears to be comparable before and during the target, we cannot provide evidence that care improved, which, given the significant financial and emotional investment, one might reasonably expect. In April 2011, after a change in government, the Secretary of State for Health abandoned the 4-hour target in favor of a “dashboard of quality indicators” for EDs. These were developed in conjunction with the UK College of Emergency Medicine.39 The change in emphasis resulted from a combination of concerns that process measures were not good indicators of quality, and a more political objective of dismantling the “target culture” of the previous Labor government.40 Time remains an indicator within this new dashboard, but the 4-hour target has been reduced to require 95% of patients being seen and treated within this period. (The United Kingdom’s College of Emergency Medicine had long argued for a threshold of 95% to ensure patient safety, as well as success in meeting the target.) Our data demonstrate that targets can have value in addressing otherwise insoluble issues. Targets are implemented in a top-down fashion, giving providers little choice but to make them work despite competing interests within the various parts of the organization.21,41,42 The 4-hour target raised the profile of ED patients and ended the practice of boarding admitted patients, something that was beyond the ED’s control. Although the target caused massive upheaval within the National Health Service, most emergency physicians do not want to go back to the “bad old days.”21 Since the changes in the target were first announced by the Coalition government, time patients spend in the ED has increased.20 In summary, according to the data examined, the 4-hour target did not result in poorer quality of ED care. The effect on quality (or lack of it) is likely related to processes EDs implemented to guard against inadequate evaluation and unnecessary admissions. We conclude that targets per se may not be harmful as long as they remain focused on the patient. The authors acknowledge Michael Campbell, PhD, Angela Carter, PhD, and Ruth L. Hew, MD, for contributions to the analysis of the data and all the departments that participated in the quantitative and qualitative portions of the study. Supervising editor: Robert L. Wears, MD, PhD Author contributions: EJW and SM were responsible for study conception, design, and supervision. EJW, SM, and JC were responsible for data collection. JC was responsible for data cleaning. All authors were responsible for coding. JVF and JC were responsible for statistical analysis. All authors were responsible for the design of the Tables. EJW and JVF were responsible for production of the Figures. All authors were responsible for data interpretation and drafting, revision, and finalizing of the article. All authors had full access to all the data (including statistical reports and tables) in the study and take responsibility for the integrity of the data and the Volume , . : December
accuracy of the data analysis. EJW takes responsibility for the paper as a whole. Funding and support: By Annals policy, all authors are required to disclose any and all commercial, financial, and other relationships in any way related to the subject of this article as per ICMJE conflict of interest guidelines (see www.icmje.org). Dr. Weber and Dr. Mason are members of the 2 professional societies that provided partial support for this study. They have no other affiliations with the sponsors. This study was supported by grants from the BUPA Foundation, the Society for Academic Emergency Medicine (United States), and the College of Emergency Medicine (United Kingdom). The study sponsors had no role in design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the article. Publication dates: Received for publication February 6, 2012. Revisions received May 5, 2012, and July 31, 2012. Accepted for publication August 6, 2012. Presented as an abstract at the Society for Academic Emergency Medicine Annual Meeting, June 2011, Boston, MA; and as a poster at the UK College of Emergency Medicine Scientific Meeting, September 2011, Newcastle-on-Tyne. Dr. Callaham recused himself from the decisionmaking process. Address for correspondence: Ellen J. Weber, MD, E-mail [email protected].
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England’s Four-Hour Target for Emergency Department Quality of Care 9. Guttmann A, Schull MJ, Vermeulen MJ, et al. Association between waiting times and short term mortality and hospital admission after departure from emergency department: population based cohort study from Ontario, Canada. BMJ. 2011;342:d2983. 10. Ontario Ministry of Health and Long-Term Care. Emergency room targets. 2009. Available at: http://www.health.gov.on.ca/en/pro/ programs/waittimes/edrs/targets.aspx. Accessed December 20, 2011. 11. Australian Government. A National Health and Hospitals Network: Further Investments in Australia’s Health. Department of Health and Ageing: Canberra, Australia; 2010. Available at: http://www. health.gov.au/internet/main/publishing.nsf/Content/nhhnreport-2/$File/NHHN%20Report%20two.pdf. Accessed August 28, 2012. 12. Pines JM, Hilton JA, Weber EJ, et al. International perspectives on emergency department crowding. Acad Emerg Med. 2011;18: 1358-1370. 13. Department of Health. The NHS Plan. A Plan for Investment. A Plan for Reform. London Stationery Office; 2000. Available at: http://www.dh.gov.uk/en/Publicationsandstatistics/Publications/ PublicationsPolicyAndGuidance/DH_4002960. Accessed December 22, 2011. 14. Department of Health. Clinical exceptions to the 4 hour emergency care target. 2003. Available at: http://www.dh.gov.uk/assetRoot/04/07/95/56/04079556.pdf. Accessed December 20, 2011. 15. New Zealand Ministry of Health. Shorter stays in ED health target. June 2011. Available at: http://www.health.govt.nz/ourwork/hospitals-and-specialist-care/emergency-departments/ shorter-stays-emergency-departments-health-target. Accessed December 14, 2011. 16. Kellermann AL. Crisis in the emergency department. N Engl J Med. 2006;355:1300-1303. 17. Centers for Medicare & Medicaid Services. Final Rule: Medicare Program; Hospital Inpatient Prospective Payment Systems for Acute Care Hospitals and the Long-Term Care Hospital Prospective Payment System and FY 2012 Rates; Hospitals’ FTE Resident Caps for Graduate Medical Education Payment. Washington, DC: Federal Register; 2011. [CMS-1518-F; CMS-1430-F]. Available at: http://www.cms.gov/AcuteInpatientPPS/FR2012/itemdetail.asp? filterType⫽none&filterByDID⫽-99&sortByDID⫽1&sortOrder⫽ ascending&itemID⫽CMS1250103&intNumPerPage⫽10. Accessed December 20, 2011. 18. Guly H, Higginson I. Obituary for the four-hour target. Emerg Med J. 2011;28:179-180. 19. College of Emergency Medicine. Abolition of the four hour waiting standard (July 2010). Available at: http://secure.collemergencymed. ac.uk/Development/Policy%20and%20Service%20Development/ Quality%20Indicators/. Accessed December 7, 2011. 20. Department of Health. Total time spent in accident and emergency. Available at: http://www.dh.gov.uk/en/Publicationsandstatistics/ Statistics/Performancedataandstatistics/AccidentandEmergency/ DH_079085. Accessed October 14, 2011. 21. Weber EJ, Mason S, Carter A, et al. Emptying the corridors of shame: organizational lessons from England’s 4-hour emergency throughput target. Ann Emerg Med. 2011;57:79-88.e71. 22. Kelman S, Friedman JN. Performance improvement and performance dysfunction: an empirical examination of distortionary impacts of the emergency room wait-time target in the English National Health Service. J Public Adm Res Theory. 2009;19:917-946. 23. Hospital Episode Statistics. Accident and emergency attendances in England (experimental statistics), 2009-2010. National Health Service Information Centre for Health and Social Care. Available
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