RT Journal Article
SR Electronic
T1 Characteristics of frequent attenders in an emergency department: analysis of 1-year attendance data
JF Emergency Medicine Journal
JO Emerg Med J
FD BMJ Publishing Group Ltd and the British Association for Accident & Emergency Medicine
SP 263
OP 267
DO 10.1136/emj.2008.059428
VO 26
IS 4
A1 L Moore
A1 A Deehan
A1 P Seed
A1 R Jones
YR 2009
UL http://emj.bmj.com/content/26/4/263.abstract
AB 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.