Missed appointments in an outpatient clinic for adolescents, an approach to predict the risk of missing

J Adolesc Health. 2008 Jul;43(1):38-45. doi: 10.1016/j.jadohealth.2007.12.017. Epub 2008 Apr 18.


Purpose: To predict the risk of an adolescent patient to miss an appointment, based on the previous appointments and on the characteristics of the patient and the appointment.

Methods: Two thousand one hundred ninety-three (1873 females) patients aged 12 to 20 years having scheduled at least four appointments were included. We assessed the rate of missed nonexcused appointments of each patient. Second, a Markovian multilevel model was used to predict the risk of defaulting.

Results: Forty-five percent of the patients have not missed even once, and 14% of females and 17% of males have missed >25% of their appointments. Females show two types of behaviors (an abstract concept that groups individuals based on a combination of their appointment-keeping and their recorded type of healthcare need) depending on the diagnosis. Somatic, gynecology, violence, and counseling diagnoses are mostly grouped together. In this group, having already missed and having an appointment with a paramedical provider increases the risk of missing. In the second group (eating disorders and psychiatric diagnoses) having already missed and a longer delay between appointments influence the risk of missing, although the risk is lower for this latter group. Males only show one type of behavior regarding missed appointments. Having missed a previous appointment, being older, having cancelled the next to last appointment and the type of diagnosis explain the risk of missing.

Conclusions: Patients who have already defaulted have a higher risk of defaulting again. Means of control regarding missed appointments should consequently focus on defaulters, to decrease the associated workload. Reminders could be a solution for the follow-up appointments scheduled with a long delay.

MeSH terms

  • Adolescent
  • Adolescent Health Services / statistics & numerical data
  • Adult
  • Ambulatory Care Facilities* / statistics & numerical data
  • Appointments and Schedules*
  • Child
  • Continuity of Patient Care
  • Databases as Topic
  • Female
  • Humans
  • Male
  • Markov Chains
  • Patient Compliance*
  • Risk Assessment
  • Switzerland