• A Mandal, D Imran, T McKinnell, and G S Rao.
• Department of Plastic & Reconstructive Surgery, University Hospital of North Durham, UK.
• Ann R Coll Surg Engl. 2005 Nov 1; 87 (6): 466-8.

IntroductionAdmission for overnight or longer hospital stay from a day-case unit is an unwelcome event. This audit was designed to identify the incidence of unplanned admissions and also to detect the potential factors for such overstays.Patients And MethodsDetails of plastic surgical day-case patients were obtained from the hospital records for a period of 6 months (February 2002 to July 2002).ResultsThe total number of unplanned admissions was 28 (3.55%). High rates were recorded in patients above the age of 80 years, male patients and body mass index > 30 kg/m2. Duration of surgery (> 45 min) and waiting time in the day surgery unit (> 2.5 h) had significant correlation with the overstays. Grade of the surgeon was not an important determinant factor. Of procedures which resulted in an unexpected admission, the most frequent were otoplasty (8.4%; n = 71) and fasciectomy for Dupuytren's contracture (14.5%; n = 41). Unexpected admissions were also high following rhinoplasty and nipple reconstruction but the total number of operations performed were not significant (n = 12 in each group). Overall, the cause of the overstays were mostly surgical (71.4%) followed by anaesthetic (28.5%) and social (7.1%).DiscussionWith an overall unplanned admission rate of 3.55%, our unit is close to the national standard of 2-3%, as advocated by The Royal College of Surgeons of England. Postoperative bleeding (60%) was the most important surgical reason for overstays followed by intravenous antibiotics, wound drainage, excessive duration of the procedure and additional, unplanned procedures. Among the anaesthetic factors, postoperative pain was the leading cause (62.5%) followed by nausea, vomiting and adverse anaesthetic reaction.ConclusionsThe reasons for unplanned admissions are multifactorial and merit appropriate patient selection and proper estimation of the disease process.

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