The aim of this study was to examine risk factors that predict persistent healthcare frequent attendance among a frequent attender (FA) population.
Prospective cohort study without intervention.
Primary healthcare centre in Tampere, Finland.
A total of 85 primary healthcare working-age patients participated in the study. All participants were FAs in the first study year.
We identified two groups of patients: temporary FAs and persistent FAs. A patient was considered as a persistent FA if he or she visited the health centre at least eight times a year for at least three out of four follow-up years. Some 59 different variables were examined as potential risk factors for persistent FA. P-course, a web-based Naïve Bayesian classification tool, was used for the modelling of the data.
In our model, the most influential predictive risk factors for persistent frequent attendance in an FA population were female gender, body mass index above 30, former frequent attendance, fear of death, alcohol abstinence, low patient satisfaction, and irritable bowel syndrome. New observations were high body mass index, alcohol abstinence, irritable bowel syndrome, low patient satisfaction, and fear of death.
In FA analyses, distinction between temporary and persistent frequent attendance should be made. Our Bayesian model could be used for identifying persistent FAs in uncertain situations. The model can quite easily be further developed as a practical decision support tool for general practitioners. However, before its use in practice, the external validity of the model will need to be defined.