Antidepressant drug prescribing in Italy, 2000: analysis of a general practice database.

Abstract

Databases of subjects receiving antidepressants provide evidence on the use of drugs in typical patients and settings under real-world conditions. This study analysed a general practice database to estimate the prevalence of antidepressant drug use, describe the use of these compounds by gender and age and estimate the prevalence of occasional versus non-occasional users. The general practice database of Chivasso, a city near Turin in Piedmont, was analysed. The database includes all community (i.e. outside hospitals) prescriptions reimbursed by the National Health System in the population living in the study area. From the database, the total number of units of antidepressant drugs prescribed over a 6-month period was extracted. Using the general practice patient code, all records were converted into a sample of patients receiving one or more prescriptions of one or more antidepressants. During the 6 months surveyed, 12,930 antidepressant prescriptions were dispensed to 3751 patients, resulting in a prevalence of use of 19 patients per 1000 inhabitants (confidence interval 18.3, 19.5). The prevalence of use progressively increased with age and was more than double in females than males (female/male ratio 2.16). Paroxetine was the most prescribed compound, followed by amitriptyline and fluoxetine. However, in older subjects, the top two antidepressants were trazodone and amitriptyline. Nearly one-fourth of all dispensed antidepressants were prescribed on one occasion only; occasional users were slightly younger than non-occasional users. In Italy, databases have been used to monitor the prescription of medicines, but they have always provided aggregate data on drug sales and consumption. In this study, a sample of typical patients receiving antidepressants under real-world conditions was analysed to help clarify what happens in clinical practice. Databases of patients receiving antidepressants should be adopted to suggest public health priorities and generate original research hypotheses to be formally tested with experimental studies.