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| Journal of the New Zealand Medical Association,
20-January-2012, Vol 125 No 1348
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Pre-hospital delay in acute coronary syndromes:
PREDICT CVD-18
Daniel Garofalo, Corina Grey, Mildred Lee, Daniel Exeter,
Andrew J Kerr
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.
MethodsStudy 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).
ResultsThere 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
 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
*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
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
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)
Table 5. Median times (IQR) in the path from
onset of symptoms to reperfusion in STEMI patients
DiscussionHalf 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.
ConclusionsThere 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
References:
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