Missed Appointments in an Outpatient Clinic for Adolescents, an Approach to Predict the Risk of Missing

The Double-Chain Markov Model is a two-level probabilistic model with a nonobserved hidden part and a visible level. The hidden level is used to classify data into a number of general types of behaviors regarding missed appointments. Each appointment of a patient is linked to the most probable type of behavior in function of the behavior of the same patient during the previous appointment and of covariates. At the visible level, each type of behavior is then fully described through a Markovian regression-like model using covariates and the fact of having or not missed each of the last three appointments to predict the probability of missing the current appointment.