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Med J Aust ; 198(11): 612-5, 2013 Jun 17.
Artigo em Inglês | MEDLINE | ID: mdl-23919709

RESUMO

OBJECTIVE: To accurately estimate the proportion of patients presenting to the emergency department (ED) who may have been suitable to be seen in general practice. DESIGN: Using data sourced from the Emergency Department Information Systems for the calendar 2013s 2009 to 2011 at three major tertiary hospitals in Perth, Western Australia, we compared four methods for calculating general practice-type patients. These were the validated Sprivulis method, the widely used Australasian College for Emergency Medicine method, a discharge diagnosis method developed by the Tasmanian Department of Human and Health Services, and the Australian Institute of Health and Welfare (AIHW) method. MAIN OUTCOME MEASURE: General practice-type patient attendances to EDs, estimated using the four methods. RESULTS: All methods except the AIHW method showed that 10%-12% of patients attending tertiary EDs in Perth may have been suitable for general practice. These attendances comprised 3%-5% of total ED length of stay. The AIHW method produced different results (general practice-type patients accounted for about 25% of attendances, comprising 10%-11% of total ED length of stay). General practice-type patient attendances were not evenly distributed across the week, with proportionally more patients presenting during weekday daytime (08:00-17:00) and proportionally fewer overnight (00:00-08:00). This suggests that it is not a lack of general practitioners that drives patients to the ED, as weekday working hours are the time of greatest GP availability. CONCLUSION: The estimated proportion of general practice-type patients attending the EDs of Perth's major hospitals is 10%-12%, and this accounts for < 5% of the total ED length of stay. The AIHW methodology overestimates the actual proportion of general practice-type patient attendances.


Assuntos
Serviço Hospitalar de Emergência/estatística & dados numéricos , Medicina Geral/estatística & dados numéricos , Mau Uso de Serviços de Saúde/estatística & dados numéricos , Aglomeração , Feminino , Humanos , Tempo de Internação/estatística & dados numéricos , Masculino , Austrália Ocidental/epidemiologia
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