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Characteristics of frequent attenders in an emergency department: analysis of 1-year attendance data

Research output: Contribution to journalArticle

L. Moore, A. Deehan, P. Seed, R. Jones

Original languageEnglish
Pages (from-to)263 - 267
Number of pages5
JournalEMERGENCY MEDICINE JOURNAL
Volume26
Issue number4
DOIs
Publication statusPublished - Apr 2009

King's Authors

Abstract

Background: There is a significant literature examining the reasons why patients attend emergency departments frequently. This body of work suggests that sociodemographic characteristics are important in understanding why patients re-attend, but it does not provide a definition of what frequent attendance means. This paper aims to identify personal and attendance factors associated with frequent attendance at an emergency department. Methods: One-year emergency department attendance data from a south-east London teaching hospital (2006-7) were analysed. The dataset was analysed at two levels: the individual patient level and the attendance level. Frequencies and cross-tabulations were produced to describe the dataset. Confidence intervals were calculated for both patient and attendance level data. Results: 82 812 patients made 117 187 attendances to the emergency department during 1 year. Each patient made an average of 1.4 attendances; 46% were repeat attendances. The analysis demonstrated differences in the personal and attendance profile of patients who attended the emergency department more frequently during the study period. A change in the patient profile first appeared at the fourth attendance and the change became more pronounced as attendances increased. Frequent attenders were more likely to be men (50.5% of single attendances; 69.5% of >= 10 attendances), older (single attendance, mean age 32 years; >= 10 attendances, mean age 45.6 years), to attend outside daytime hours (51.4% of single attendances; 69.2% of >= 10 attendances) and to be triaged into the more serious categories (36.1% of single attendances; 54.3% of >= 10 attendances). Conclusion: Where local services are being designed to divert frequent attenders, existing data sources can be a rich source of information to inform service design. For example, this analysis identifies older men at their fourth or more attendance as a potentially important group when examining frequent attendance at this particular hospital. It also identified a potential need for services outside normal surgery hours, although frequent attenders tend to be triaged into the more urgent categories.

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