Previous studies have shown a relation between the treatment delay and mortality outcome in MI patients.11–14
However, few studies have investigated the impact of geographical location and none has been representative of a complete population.15
Our data suggest that the distance between home and hospital of admission predicts mortality in subjects experiencing first acute MI both in the community (prehospital) and following discharge from hospital after adjustment for urban-rural code or travel time and other covariates. There was no difference if these results were adjusted only for age, sex and other covariates, suggesting that urban-rural code and travel time are the significant confounders. Other areas that could cause a delay between the onset of symptoms and treatment are the delay by patients in calling for help and the delay between calling for help and the attendance of a doctor. We could not measure these but they could be investigated.16
However, we used a measure of rurality as a possible surrogate measure of patient behaviour in the different geographical settings.
The median travel time was 37 minutes for patients who lived >9 miles from an acute hospital. This time does not include time taken for the ambulance to reach the patient. In addition, these times take no account of adverse traffic or weather conditions. We think that it is unlikely that this group of patients could have met the national target for thrombolysis within 60 minutes of a call for help.
Geographical inequality and early thrombolysis
Our data support the concept that there is geographical inequality of care in patients who have had an acute incident MI. An excess in coronary heart disease (CHD) death rates in young patients was reported outside the state capital cities in Australia.17
The risk factors between the populations and inadequacies in the level of medical care provided were the two main reasons that have been used to explain this excess CHD death. A recent US study showed that a mile increase in distance leads to a nearly 6.5% increase in the number of deaths from a heart attack.18
However in Scotland, the National Health Service is tax funded, free at the point of consumption and covers the entire population. There should thus be no socioeconomic eligibility distinctions in the level of health care given to an individual, being based on need alone. One hypothesis is that the time delay related to distance plays an important part in the prognosis of MI patients. A study from our own region demonstrated that an early thombolysis treatment strategy was achievable and improved outcome.19
However when we adjusted for travel time this did not explain the association between distance from acute facilities and mortality.
A US Veteran Affairs (VA) study investigated the effect of distance between home and hospital of admission on mortality in male post-MI patients.15
They compared the mortality outcome between patients (64%) who lived more than 20 miles from any VA health source and patients (36%) who lived within 20 miles. They found a positive relation between distance and follow-up mortality. However they studied only men and their results may not be generalisable to other healthcare systems. Our study indicates that the distance from home to hospital of admission is an important factor that predicts survival following acute MI.
Study limitations and strengths
There are some limitations in our study. First, we did not have information on smoking, obesity, severity of MI, invasive management after discharge, the treating specialist at the admitting hospital and other unmeasured risk factors, all of which are likely to be important in patients with heart disease. However, we did use the Carstairs socioeconomic deprivation score as a surrogate measure for at least some of these factors.20 21
Also, our previous sensitivity analysis on unmeasured risk factors showed that at least some of these unknown risk factors were unlikely to make a big impact on cardiovascular outcome.22
Second, the distance we used in this study was based on home and hospital addresses. We did not know the exact location of the patients when they had a heart attack. However, given the average age of 72, we would expect that the majority of patients would have had their MI at or near their home. Third, we did not have information on the time of onset of MI symptoms. Fourth, we used linear distance and estimated travel time in the study. However, distance along the road network may be different and there may have been differences in traffic conditions at different times of day.
We observed independent risk reductions in mortality during the follow-up period for lipid-lowering drugs, antiplatelet drugs and β-blockers consistent with the finding from clinical trials and other observational studies.23–28
However we may have underestimated the benefits of cardiovascular drugs because we assumed all patients complied with their drug treatment when in reality this is rarely the case.28
Finally, the diagnostic accuracy of MI death before hospitalisation is open to question. The data retrieved from the General Register Office revealed that in those subjects who had postmortem examinations performed, the diagnosis of MI was almost always confirmed. Presumably those subjects who underwent post mortems were those in whom the diagnosis was in question and was more likely to be incorrect. Thus these postmortem data are reassuring and suggest that prehospital MI death data were reasonably accurate.
The strength of our study is the population-based cohort design, with complete follow-up over the study period. This approach allows a “real-world” population to be studied, representing all socioeconomic groups and within a universal healthcare coverage scheme.29
The results inform us that there may be geographical inequality in healthcare delivery, the cause of which is currently difficult to explain. This relation may influence healthcare policy on the provision of prehospital care such as thrombolysis for MI, the enhanced provision of paramedics and the greater delivery of ambulance services to remote communities. It is in line with the recent Kerr report in Scotland calling for services to be delivered closer to patients wherever possible,30
and studies demonstrating that managed clinical networks can achieve this goal.31
In conclusion, our data suggested that distance from home to hospital may predict mortality outcome in subjects experiencing an acute MI. These data provide support for policies that locate services for acute MI closer to where patients live.