Predictors of failed attendances in a multi-specialty outpatient centre using electronic databases

A retrospective study was conducted on outpatient clinic attendances at Tan Tock Seng Hospital, Singapore from 2000 to 2004. 22864 patients were randomly sampled for analysis. The outcome measure was failed outpatient appointments according to each patient's latest appointment.Failures comprised of 21% of all appointments and 39% when using the patients' latest appointment. Using odds ratios from the mutliple logistic regression analysis, age group (0.75 to 0.84 for groups above 40 years compared to below 20 years), race (1.48 for Malays, 1.61 for Indians compared to Chinese), days from scheduling to appointment (2.38 for more than 21 days compared to less than 7 days), previous failed appointments (1.79 for more than 60% failures and 4.38 for no previous appointments, compared with less than 20% failures), provision of cell phone number (0.10 for providing numbers compared to otherwise) and distance from hospital (1.14 for more than 14 km compared to less than 6 km) were significantly associated with failed appointments. The predicted probability model's diagnostic accuracy to predict failures is more than 80%.A few key variables have shown to adequately account for and predict failed appointments using existing electronic databases. These can be used to develop integrative technological solutions in the outpatient clinic.Failure to comply with outpatient medical appointments is a perennial problem, affecting costs, causing scheduling conflicts, and interrupting continuity of care. Failed appointments in different outpatient settings have ranged from 12% to 42% [1-7]. The resulting economic costs range from ￡65 per failed appointment in the United Kingdom in 1997 [2] to 3–14% of total outpatient clinic income in the United States [8]. This problem may be compounded if non-compliance with appointments is an indication of poorer clinical outcomes [9]. Most studies on failed appointments focused on the socio-economic and demographic factors that affect failures [1,10-