DEPRESSION- HIGHLIGHT MOLECULES USED IN PATIENTS FROM SUPPLEMENTARY HEALTH IN BRAZIL
Author(s)
Marra FC, Montezani E
Dapx Intelligence for Healthcare, São Paulo, Brazil
OBJECTIVES: Depression is the most common psychiatric disease in the world that has a reactive environmental character, where the atmosphere can provide this disease. The objective of this study was to identify the types of drug treatments for depression, in 2014, with data from the health insurance of Brazil. METHODS: The patients were identified through the health insurance database of Brazil, from January to December 2014, who bought some antidepressants medication in the analyzed period. From the date of the purchase, it was possible to obtain a methodology capable of identifying the age of these patients and the main molecules used for the treatment. RESULTS: From a total of 884.143 patients who used any type of antidepressant, it was found that 85 % of these patients used the following molecules: Fluoxetine (19.0%), Sertraline (18.6%), Escitalopram (14.1%), Paroxetine (12.8 %), Bupropion (11.1%) and Amitriptyline (9.5%). Considering the age of these patients it was identified that from the age of 30, the incidence in the use of these drugs increases by 18.0%, Fluoxetine is responsible for the growth of 88.5 % in this incidence, with a confidence interval of 95 % and standard error of 2%. CONCLUSIONS: It was identified that the main molecule used for depression, in the sample analyzed, was fluoxetine and the age with higher incidence of purchases of these drugs is between 20 and 50 years. As WHO data (World Health Organization), depression will be the most common disease in the world in 2030. The relationship between doctor and patient has a fundamental importance in successful treatment. Thus, the patient monitoring is extremely important to control the disease in the country.
Conference/Value in Health Info
2015-11, ISPOR Europe 2015, Milan, Italy
Value in Health, Vol. 18, No. 7 (November 2015)
Code
PMH50
Topic
Health Service Delivery & Process of Care, Real World Data & Information Systems
Topic Subcategory
Health & Insurance Records Systems, Health Care Research
Disease
Mental Health