Short-term unscheduled return visits of adult patients to the emergency department

J Emerg Med. 2014 Aug;47(2):131-9. doi: 10.1016/j.jemermed.2014.01.016. Epub 2014 Mar 15.


Background: Emergency department (ED) crowding is a major international concern that affects patients and providers.

Study objective: We describe the characteristics of patients who had an unscheduled related return visit to the ED and investigate its relation to ED crowding.

Methods: Retrospective medical record review of all unscheduled related ED return visits by patients older than 16 years of age over a 1-year period. The top quartile of ED occupancy rates was defined as ED crowding.

Results: Eight hundred thirty-seven patients (1.9%) made an unscheduled related return visit. Length of stay (LOS) at the ED for the index visit and the LOS for the return visit (5 h, 54 min vs. 6 h, 51 min) were significantly different, as were the percent admitted (11.6% vs. 46.1%). Of these patients, 85.1% and 12.0% returned due to persistence or a wrong initial diagnosis, of their initial illness, respectively, and 2.9% returned due to an adverse event related to the treatment initially received. Patients presented the least frequently with an alcohol-related complaint during the index visit (480 patients), but they had the highest number of unscheduled return visits (45 patients; 9.4%). Unscheduled related return visits were not associated with ED crowding.

Conclusion: Return visits impose additional pressure on the ED, because return patients have a significantly longer LOS at the ED. However, the rate of unscheduled return visits and ED crowding was not related. Because this parameter serves as an essential quality assurance tool, we can assume that the studied hospital scores well on this particular parameter.

Keywords: crowding; emergency department; incidence; patient characteristics; return visit.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Belgium
  • Crowding
  • Emergency Service, Hospital / statistics & numerical data*
  • Female
  • Humans
  • Length of Stay
  • Logistic Models
  • Male
  • Middle Aged
  • Patient Readmission / statistics & numerical data*
  • Retrospective Studies
  • Young Adult