期刊
CHRONOBIOLOGY INTERNATIONAL
卷 32, 期 6, 页码 731-738出版社
TAYLOR & FRANCIS INC
DOI: 10.3109/07420528.2015.1041600
关键词
Cardiovascular; EMS; epidemiology; prehospital
Diagnosed cardiovascular disease has well-reported temporal patterns, with demand distribution peaks in the late morning and greater case numbers on Mondays and in winter. We aimed to report temporal patterns of presumptive cardiovascular disease cases as determined after emergency medical services (EMS) assessment and to characterize the demand distribution by day of the week. We conducted a secondary analysis of all Ambulance Victoria cases in metropolitan Melbourne (Victoria, Australia) between January 2008 and December 2011. Analyzed data included time of call, incident mechanism, location type, final assessment (paramedic diagnosis'') and patient age. We employed Poisson's regression to analyze case numbers and trigonometric regression to quantify distribution patterns. The 182 983 cases of presumptive cardiovascular disease observed during the study period constituted 15.2% of total demand. The median age of persons attended was 72 (IQR 57-82) and there was an almost even split between genders (51% female). Peak numbers of most cardiovascular case types occurred between 09:00 and 11: 00; the only exception was acute pulmonary edema, which had peak case numbers at 06:00. Trigonometric regression showed distinct time of day distribution patterns, which did not alter by season. Although weekend day demand was lower than on Mondays, due to a different distribution pattern, these differences were not constant over the 24-hour period. There were up to 27% fewer cases at 09:00 and up to 2.8% more cases at 01:00 on weekends compared to Mondays. We have shown that examination of presumptive cardiovascular disease using not only case counts but also demand distribution patterns allows for a greater understanding of ambulance demand. Monday might be the most frequent day for cardiovascular cases but different patterns of demand occur on weekends. Increased knowledge of when different types of cases are most likely to occur will help inform EMS planning, including paramedic capacity and resources.
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