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The New Zealand Medical Journal

 Journal of the New Zealand Medical Association, 20-January-2012, Vol 125 No 1348

Pre-hospital delay in acute coronary syndromes: PREDICT CVD-18
Daniel Garofalo, Corina Grey, Mildred Lee, Daniel Exeter, Andrew J Kerr
Abstract
Aims To study pre-hospital delay, its components and determinants, in patients with acute coronary syndromes (ACS) admitted to Middlemore Hospital Coronary Care Unit.
Methods Consecutive ACS patients admitted between January 2009 and July 2010 were included. Pre-hospital delay was defined as the time from onset of worst symptom(s) to defibrillator availability: either ambulance arrival at the scene or time of hospital arrival (non-ambulance patients).
Results For 805 patients the median delay from symptom onset to defibrillator availability was 174 minutes. Half the cohort had a delay to defibrillator availability of >3 hours. The median delay was an hour longer for patients from areas of greatest deprivation compared with less deprived areas, [208 vs 149 min, respectively (p=0.015)], and 7 hours longer for non-ambulance vs ambulance patients, [553 vs 130 min (p<0.001)]. Māori, Pacific, Indian and those from areas of higher deprivation were less likely to travel to hospital by ambulance. Of ST-elevation myocardial infarction patients eligible for reperfusion, over two-thirds of the total delay between symptom onset and reperfusion occurred pre-hospital.
Conclusion Community intervention targeted at more disadvantaged communities and higher risk ethnic groups should be considered as part of an overall strategy to reduce disparity and improve cardiac outcomes.

Measurement of performance in the Health Service, with the object of lifting the performance of poorly performing sectors to match the standards of the best, is, as far as cardiac services are concerned, now firmly established in the UK.1 This has not yet happened in New Zealand, although a start has been made,2,3 and a recent Ministry of Health publication,4 as an immediate priority, calls for commission of an “audit of access delay for acute coronary syndromes (ACS), stroke and transient ischaemic accidents (patient, health professional and ambulance delays) in several regions.”
Two thirds to three-quarters of deaths from ACS happen outside hospital,5,6 and in victims under age 55 this proportion may be more than 90%.5 There is also a strong inverse relationship between deaths prevented and delay in coming under care,7 the relationship being strongest when “care” is defined as paramedic rather than hospital care. This is because defibrillation administered by ambulance personnel has been shown to be as effective as in hospital, and in that study it was estimated that four times as many deaths had been prevented (up to 30 days after the event) by defibrillation than by thrombolytic treatment.
Two small studies in New Zealand have shown long delays between symptom onset and hospital arrival.8,9 We sought to define the components of pre-hospital delay, and its association with factors including ethnicity, socioeconomic status, distance from hospital, which professional help was first sought from and how patients reached hospital. In patients with ST-elevation myocardial infarction (STEMI), in whom considerable attention has been directed to minimise in-hospital delay to treatment, we looked at the relative pre- and in-hospital components of delay.

Methods

Study design—The study was conducted between 1 January 2009 and 31 July 2010. All patients with a final diagnosis of acute coronary syndrome admitted to Middlemore Hospital’s Coronary Care Unit (CCU) from the community were included. Only first admissions during the study period were included. Patients referred from other hospitals, from outpatient clinics, or ACS that occurred in other hospital wards were excluded. Middlemore Hospital is the base hospital for 500,000 people living in the Counties-Manukau District Health Board (CMDHB) catchment in Auckland, New Zealand. Although the population is predominantly urban, there are rural communities within CMDHB up to 50 km from Middlemore Hospital.
From 2007 Middlemore CCU has routinely collected demographic, risk factor, diagnostic, investigation and in-hospital outcome data on all ACS patients using Acute Predict, an electronic database.10 Demographic and laboratory data are auto populated from hospital databases. Demographic data includes ethnicity and the NZ Deprivation Index 2006 (NZDep06). Clinical and angiographic data are entered by medical staff supervised by the research registrar. Data quality is supported by definition fields within the electronic form and 3-monthly scheduled audits of data quality. For the duration of this study, an additional “pre-hospital delay” data set was collected in new fields added within the existing ACS database.
Data were sourced from the ambulance report and the clinical notes. During the duration of the study the medical teams were specifically asked to inquire about time of onset of symptoms and actions in the pre-hospital phase. This information was gathered by a research registrar or a research nurse on day 0 or 1 post-admission to the CCU.
Data and definitions—All eligible patients were asked for the time and date of onset of their most severe symptom(s). Time of onset of symptoms was defined as time of onset of the chest pain or surrogate symptom (breathlessness, syncope, etc). If there was more than one symptom, or more than one episode of symptoms, the most severe symptom or episode would be chosen. If there was more than one episode of symptoms of equivalent severity, the one lasting for longer was recorded as time of onset. In particular cases where the presentation did not fit these definitions, the research registrar would decide whether an accurate estimate of onset time could be made.
For each patient the professional from whom help was first sought was recorded. The “delay to defibrillator availability” was also defined. This was the time elapsed between onset of symptoms and, either ambulance arrival at the scene (for those patients who first sought help from the ambulance service), or arrival at the hospital (for all the other patients). For patients using the ambulance service, times of despatch, arrival at the scene, departure from the scene, and time of arrival at the hospital were taken from the ambulance report. Patients coming to hospital via other means were divided into those who initially sought help from their regular general practitioner (GP), those who attended a primary care emergency centre (A and E), and those who self presented to hospital. In all these non-ambulance cases, time of arrival at the hospital was defined as the time when they were triaged by a nurse in the Emergency Department.
For this study, selected data recorded in the Acute Predict data set was used. This included patient demographics (age, gender and ethnicity) which auto-populated the electronic record from the hospital patient management system. For these analyses ethnicity was categorised in four groups: European, New Zealand Māori, Pacific, Indian, and Other. As a measure of socioeconomic status, the domicile code (where available and valid) for each patient was obtained from the hospital information system. This was linked to the New Zealand Deprivation 2006 index and reported as decile of deprivation from 1 (least deprived) to 10 (most deprived).
The NZDep06 is a small area index of deprivation that provides a score for each meshblock in New Zealand based on nine variables (reflecting eight types of deprivation).11 Type of ACS diagnosis (ST elevation MI [STEMI], Non-ST elevation MI [NSTEMI] and unstable angina [USA]) at discharge was used.
For patients with STEMI who had in-hospital reperfusion, either pharmacological thrombolysis or primary percutaneous coronary intervention (PCI), the in-hospital delay to reperfusion data was obtained (door-to-needle and door-to-balloon time, respectively).
The individual patient meshblock data was used to estimate the distance that an ambulance would need to travel by road from the patient’s home to Middlemore Hospital.
Statistical analysis—Statistical analysis was performed using STATA v10.0 software. Numbers and percentages of those in different population and diagnostic groups who had arrived at the hospital via ambulance and self transport were calculated and compared using the chi-squared and analysis of variance statistics. Differences in the time between onset of symptoms and the availability of defibrillation between population and diagnostic groups were examined by calculating medians and interquartile ranges, and these were compared using a non-parametric k-sample test on the equality of medians.
A subanalysis of the onset of symptoms to receipt of reperfusion therapy was performed on those who had experienced a STEMI. These patients were grouped according to reperfusion therapy received (none, thrombolysis and PCI). The median and interquartile range of the times between onset of symptoms and arrival at hospital, and times between arrival at the hospital and reperfusion, were calculated for those who received thrombolysis and PCI.
The study was approved by the Northern X Regional Ethics Committee (NTX/09/04/EXP).

Results

There were 1068 consecutive first admissions with an ACS event. Of these, no data was collected for 176 patients due to the admission occurring predominantly over a weekend or holiday period when research staff were not available.
Of the 892 patients available for the study, 24 were ineligible, and a further 63 patients could not give a precise estimate of time of onset of symptoms. There were therefore 805 people for whom the time from symptom onset to defibrillation availability could be calculated. These people comprise the final cohort used for analysis.
Twenty patients (2%) had a cardiac arrest prior to admission or in hospital, and eight people (1%) died in-hospital.
Overall delay (Figure 1)—Overall median time delay from symptom onset to defibrillator availability was 174 minutes (min), and to hospital arrival was 208 min. Less than a quarter of the cohort had defibrillator availability within an hour of symptom onset, another quarter achieved this under 3 hours, but for nearly a third the delay was greater than 6 hours. Delay for STEMI patients was slightly less than for NSTEMI, but there was substantial overlap.
Ambulance compared with self transport—Table 1 shows demographic and clinical information according to whether patients were transported to hospital by ambulance or self-transport.
Three-quarters of the cohort were men; mean age was 61.3 years (SD 12.4). Half the cohort identified themselves as European, 18% Pacific, 12% Māori and 13% Indian. Almost half of the cohort (48%) lived in areas of high socioeconomic deprivation (NZDep06 9–10).
Figure 1. Time to defibrillation availability in STEMI and NSTEMI patients
content01.jpg
Ambulance transport was used by 73% of patients. European patients (82%) were more likely to travel by ambulance than other ethnic groups [Māori (66%), Pacific (63%), and Indian (65%)]. Those from more deprived areas were less likely to come by ambulance. Those coming by ambulance were also slightly older and more likely to have a final diagnosis of STEMI. The time delay from symptom onset to the availability of potentially life-saving defibrillation (ambulance attendance or hospital arrival for those self transported) was approximately four times longer in those not coming by ambulance (130 vs 553 min, respectively, p<0.001). Correspondingly, the time from symptom onset to hospital arrival was markedly longer in those not coming by ambulance.
Delay according to demographics and diagnosis (Table 2 and Figure 1)—For the whole cohort, patients from the most deprived areas (NZDep06 9-10) took an hour longer to come under defibrillator protection than those from less deprived areas (median delay 208 and 149 min, respectively). There were no significant differences by ethnic group, age group or gender. There was a trend towards shorter times in patients with STEMI compared with other ACS, but the median delay in these patients was still just over 2 hours. When this analysis was repeated for delay from onset to hospital arrival, the results were similar (data not shown).
Table 1. Characteristics of pre-hospital delay cohort by method of transport to hospital
Variables
Total cohort
(n=805),
Col %
Ambulance
(n=589),
Row %
Self-transport
(n=216),
Row %
P-value for difference between ambulance & self transport
Gender and age
Male, n (%)
Female, n (%)

Mean age, mean (SD)
Ethnicity
European, n (%)
Māori, n (%)
Pacific, n (%)
Indian, n (%)
Other, n (%)
Deprivation**
NZDep06 1-8
NZDep06 9-10
Final diagnosis
USA, n (%)
Non-STEMI, n (%)
STEMI, n (%)

595 (74%)
210 (26%)

61.2 (12.5)

386 (50%)
94 (12%)
141 (18%)
102 (13%)
43 (6%)

396 (52%)
359 (48%)

44 (5%)
582 (72%)
179 (22%)

433 (73%)
1565 (74%)

62.2 (12.8)

318 (82%)
62 (66%)
98 (63%)
66 (65%)
30 (70%)

306 (77%)
250 (70%)

31 (70%)
408 (70%)
150 (84%)

162 (27%)
54 (26%)

58.7 (11.1)

68 (18%)
32 (34%)
52 (37%)
36 (35%)
13 (30%)

90 (23%)
109 (30%)

13 (30%)
174 (30%)
29 (16%)

0.671


0.0004

<0.0001





0.017


0.001
Distance to hospital
<5 km
5–10 km
10–20 km
>20 km

159 (20%)
212 (26%)
225 (28%)
209 (26%)

106 (67%)
143 (67%)
171 (76%)
169 (81%)

53 (33%)
69 (33%)
54 (24%)
40 (19%)

0.0003
Median time to defibrillation (IQR), min
174 (68, 646)
130 (56, 392)
553 (142, 1700)
<0.0001
Median time to hospital (IQR), min
208 (100, 668)
172 (92, 428)
553 (142, 1700)
<0.0001
Mean time to defibrillation (SD), min
826 (2164)
575 (1508)
1511 (3264)
Mean difference*=
936 (604–1268)
Mean time to hospital (SD), min
852 (2161)
610 (1508)
1511 (3264)
Mean difference*=
901 (569–1232)
*Mean difference (95% confidence interval) between self transport and ambulance groups.
**NZDep06 data missing in 50 people.
Table 2. Median time to defibrillation (interquartile range) for different population/clinical groups
Group
Total cohort (n=805)
P-values
Self transport (n=216)
P-values
Ambulance (n=589)
P-values

Age
<50y (n=162)
50-65y (n=335)
>65y (n=308)
Gender
Men (n=595)
Women (n=210)
Ethnicity
Euro (n=386)
Māori (n=94)
Pacific (n=141)
Indian (n=102)
Other (n=43)
Final diagnosis
USA (n=44)
NSTEMI (n=582)
STEMI (n=179)
174 (68, 646)

173 (70, 684)
178 (70, 640)
165 (61, 641)

164 (64, 646)
184 (84, 676)

173 (62, 656)
226 (86, 724)
164 (64, 622)
163 (76, 774)
164 (58, 516)

195 (61, 558)
189 (76, 760)
128 (50, 378)


0.890



0.453


0.627





0.097
553 (142, 1700)

558 (172, 1394)
510 (140, 1680)
665 (148, 2098)

538 (140, 1700)
630 (148, 1804)

987 (287, 2091)
479 (190, 2454)
312 (84, 770)
591 (161, 1475)
350 (208, 1430)

480 (138, 2150)
615 (220, 1804)
120 (64, 536)


0.255



0.875


0.026





0.01
130 (56, 392)

134 (56, 328)
131 (60, 372)
128 (50, 404)

120 (48, 408)
155 (76, 335)

133 (50, 404)
146 (56, 404)
132 (56, 372)
107 (60, 304)
123 (40, 196)

164 (40, 336)
129 (58, 408)
130 (44, 360)


0.988



0.072


0.901





0.640
Deprivation
NZDep06 1-8 (n=396)*
NZDep06 9-10 (n=359)

149 (65, 596)
208 (76, 732)

0.015

792 (150, 2084)
510 (140, 1430)

0.076

127 (56, 322)
163 (62, 570)

0.150
Distance from hospital
<5 km (n=159)
5-10 km (n=212)
10-20 km (n=225)
>20 km (n=209)

162 (72, 584)
175 (76, 766)
164 (58, 576)
186 (68, 640)

0.909

388 (140, 864)
560 (150, 2084)
557 (120, 1670)
653 (222, 2216)

0.883

115 (56, 328)
134 (58,436)
130 (44, 410)
138 (58, 336)

0.845
Delay according to professional first contacted (Table 3)—Patients who called an ambulance directly, 43% of the cohort, had markedly shorter median delays to defibrillation availability than those who presented directly to hospital (76 and 220 min, respectively). The longest delays were in the over 40% who initially presented to their GP or an A and E clinic (556 and 300 min, respectively).
Table 3. Median onset (IQR) of symptoms to defibrillation availability according to professional help first sought
Professional help sought
Number (%)
Median time (IQR), min
P-value for differences between groups
Mean time (SD), min
Ambulance
Hospital by self referral
GP
Private A and E
Other
Unavailable/don’t know
348 (43%)
109 (14%)
275 (34%)
65 (8%)
5 (1%)
3 (<1%)
76 (34, 195)
220 (84, 536)
556 (162, 1716)
300 (110, 740)
2334 (764, 3810)


<0.0001
269 (769)
649 (1749)
1590 (3201)
791 (1391)
2241 (1845)
Components of delay in patients transferred by ambulance (Table 4)—For those patients transferred by ambulance, the major component of delay was decision time, between symptom onset and ambulance despatch. A median of 2 hours elapsed before the decision was made. In contrast, the median time between ambulance despatch and arrival at the scene was just 8 minutes, and the total time from despatch to hospital arrival was a median of 40 minutes. The distance from the hospital contributed on a very small increase in median time from despatch to arrival at the scene, but a greater delay from departure from the scene to hospital arrival.
STEMI delay pre- and in-hospital (Table 5)—Nearly a third of patients with STEMI were not offered potentially lifesaving reperfusion therapy. This was related to an over 6-hour median delay from symptom onset to hospital arrival. Patients who had reperfusion therapy still had a median pre-hospital delay of 2 hours, which is much longer than the in-hospital delays to thrombolysis or primary PCI (median door-to-needle and door-to-balloon times 40 and 84 min, respectively). Over two-thirds of the total delay between symptom onset and reperfusion therapy occurred in the pre-hospital phase.
Table 4. Median times (IQR) in minutes between ambulance departure and arrival at hospital according to distance of home residence from hospital (n=589)
Start to destination
Total
<5km
5-10km
10-20km
>20km
P-value
Symptom onset to ambulance despatch
120 (48, 396)
106 (44, 320)
120 (52, 420)
118 (36, 400)
124 (48, 324)
0.93
Despatch to arrival at scene
8 (4, 12)
6 (4, 8)
8 (6, 12)
8 (4, 12)
8 (4, 18)
<0.0001
Ambulance arrival to departure
14 (8, 20)
12 (8, 16)
14 (8, 18)
14 (10, 20)
16 (8, 24)
0.01
Ambulance departure from scene to hospital
18 (12, 28)
8 (6, 12)
16 (12, 18)
20 (16, 26)
30 (20, 38)
<0.0001
Symptom onset to hospital
172 (92, 428)
135 (86, 344)
164 (90, 470)
176 (88, 448)
188 (108, 402)
0.35
Table 5. Median times (IQR) in the path from onset of symptoms to reperfusion in STEMI patients
Revascularisation
Onset to hospital
Door to reperfusion
Onset to reperfusion
PCI (n=44)
Thrombolysis (n=80)
No reperfusion (n=55)
124 min (79, 426)
122 min (65, 225)
332 min (128, 944)
84 min (66, 116)
40 min (25, 62)
272 min (164, 519)
180 min (120, 272)

Discussion

Half of all patients with ACS who were admitted to Middlemore CCU spent at least 3 hours of the early and potentially deadly phase of their illness in the community without access to a cardiac defibrillator. This period corresponds to the period when availability of prompt defibrillation is most likely to save lives.5 A third of these patients had a greater than 6 hour delay, including a quarter of those with STEMI. When an ambulance was called the ambulance response times were short. Most of the delay occurred prior to calling for an ambulance.
Patients who called an ambulance directly had the shortest delays, and those who initially contacted their GP or an A and E clinic had much longer delays. Although three-quarters of the cohort were transported by ambulance, only 43% of the cohort called an ambulance directly. The others came by ambulance after consulting their GP or an A and E centre. Māori, Pacific and Indian patients, and those from areas of greatest deprivation were less likely to come to hospital by ambulance. Although the mode of transport is likely to be partly determined by symptom severity, it is unlikely that symptom severity varied between ethnic groups. Rather, this lower rate of ambulance contact is likely to be due to a number of factors including cultural, educational and financial reasons. In New Zealand there is a charge for calling an ambulance, which is an obvious disincentive for those from poorer areas.
Apart from the type of transport used, the only other significant predictor of pre-hospital delay was socioeconomic status estimated by the NZDep06 score. Patients from more deprived areas took an hour longer to defibrillator availability. This association between socioeconomic status and longer delays has also been observed in the United States.12,13 This delay during a critical phase of the illness may be an important contributor to the known higher cardiovascular mortality rates in poorer New Zealanders.14
Of the patients presenting with STEMI, a third presented too late to be offered reperfusion therapy, exposing them to both high risk of lethal arrhythmia and poorer late outcomes due to more extensive myocardial infarction. Of those presenting early enough to be offered reperfusion therapy, the ambulance pre-hospital transport times were very good, and in-hospital door-to-reperfusion therapy times were mostly within international targets. Whilst some small improvement in those and the ambulance transport times may be achieved, by far the biggest modifiable delay for all STEMI patients is the delay in seeking professional help.
What are the implications of this delay? Improved prevention and treatment options have led to a marked reduction in age-adjusted cardiovascular mortality rates in Western countries over the last 40 years, but these rates are now levelling off. Whilst some gains will still be made by improving utilisation of evidence-based therapy and timeliness of reperfusion in hospital, the greatest opportunities for further improvement in outcomes are likely to be made in the community, including improved primary and secondary prevention and reducing delays to appropriate management.
Strategies to reduce pre-hospital delays can improve outcomes by reducing both time to defibrillation access in all ACS, and time to reperfusion in the subgroup with STEMI. Because the benefits of early defibrillation availability occur for all ACS and reperfusion gains occur only in the fifth of patients with STEMI, the greatest benefits of getting ACS patients under earlier paramedic care will probably relate to earlier defibrillation availability.
What can be done? Intervention studies to reduce pre-hospital delays have had mixed results. Two European community intervention studies in the 1980’s and 90’s reduced the median delay to hospitalisation in myocardial infarction from 180 to 138 min, and from 196 to 144 min, respectively.15,16 In contrast, a similar study from the United States17 had shorter delays at baseline and found no significant reduction in delay after community intervention programmes (144 to 138 min).
Another United States study which randomised communities to community intervention versus no intervention also found no effect on delay (140 min in both groups), although they did increase the proportion of patients calling an ambulance.18 It is interesting that in the Physician’s Health Study,19 involving presumably very health literate individuals, the median delay was 114 min.
On the basis of this and the US studies it has been suggested that it may be difficult to reduce delay to less than 2 hours in view of the varying symptomatic presentations and psychological factors involved in making the decision to call for help.18 However, in our cohort the median delay to hospital arrival was 208 min, which is at a level seen pre-intervention in the successful European studies.
Furthermore, people from poorer areas have an hour greater delay than those from wealthier areas. These findings suggest that a community intervention programme targeted at more disadvantaged communities and higher risk ethnic groups which encourages earlier call for help directly to the ambulance service may be a useful part of an overall strategy to reduce disparity and improve cardiac outcomes
Study limitations. We have only included patients admitted to CCU. Patients admitted to other wards, usually with multiple co-morbidities or with significant functional or cognitive impairment, were not part of this analysis. We only have information on those who survived to CCU admission. If the median delay time is 3 hours, it is likely that there were patients who delayed calling for help for a similar time who died suddenly. We have no information regarding this number or details of their delay from this study. For those patients who initially contacted their GP or an A and E centre we did not collect the delay between that initial contact and the subsequent time of call for an ambulance or hospital arrival. This would be useful to collect as a sub-study in any future research.
For this study the time of the call for help was estimated from the time of ambulance despatch. We did not have access to the actual call time, but for ACS patients in the Auckland region ambulance despatch typically occurs within a few minutes of receipt of the call (personal communication, Tony Smith, St John’s Ambulance Service Clinical Director). The NZDep06, the measure of socioeconomic status used, is an area-based measure and does not take into account all determinants of socioeconomic status at an individual level. As a result it is possible that the effects of socioeconomic status may have been underestimated.20
In this study the distance from hospital was defined as the distance from home estimated using the NZ mesh block data. Some patients will have made the call for help from GP surgeries or from their workplace, which will lead to some underestimation of the effect of this variable. Some A and E centres may have had a defibrillator, which would mean the median delay time to defibrillation availability for patients presenting initially to these centres might be slightly overestimated.

Conclusions

There are significant potentially modifiable pre-hospital delays in patients with ACS. These delays are most marked in those groups known to have worse cardiovascular outcomes, and are likely to be a significant contributor to those poorer outcomes. Consideration should be given to developing a community intervention programme targeting at-risk communities to encourage earlier call for help directly to the ambulance service, to reduce disparity and improve cardiac outcomes.
Competing interests: None declared.
Author information: Daniel Garofalo, Cardiology Registrar and Research Fellow, Middlemore Hospital, South Auckland; Corina Grey, Public Health Medicine Registrar, Section of Epidemiology and Biostatistics, School of Population Health, University of Auckland; Mildred Lee, Data Analyst, Counties Manukau District Health Board, South Auckland; Daniel Exeter, Senior Lecturer, Section of Epidemiology and Biostatistics, School of Population Health, University of Auckland; Andrew J Kerr, Cardiologist and Clinical Head of Cardiology, Middlemore Hospital, Counties Manukau District Health Board, South Auckland
Acknowledgements: We acknowledge Dr Robin Norris for his assistance in designing and implementing this study. We also thank Dianne Caveney for her assistance with data collection, Dr Tony Smith from St John’s Ambulance service who provided advice, as well as The National Heart Foundation and the Middlemore Cardiology Research Fund who provided financial support for this study.
Correspondence: Andrew Kerr, c/o Dept of Cardiology, Middlemore Hospital, Otahuhu, Auckland 93311, New Zealand. Email: Andrew.Kerr@middlemore.co.nz
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