Prescription for psychiatric patients in a Brazilian public hospital: cross-sectional study

Maria R. Fernandes, Laura J. Lopes, Milla P. Rocha, Laís P. Almeida, Tânia R. Ferreira,Carolina B. Rogerio,Cristiane C. Bergamaschi

Revista Brasileira de Farmácia Hospitalar e Serviços de Saúde(2020)

引用 0|浏览0
暂无评分
摘要
Background: The growing use of psychotropic drugs has been attributed to a higher frequency of psychiatric disorders diagnosed, interaction of new drugs on the pharmaceutical market, and new therapeutic indications of existing drugs. Given this scenario, the adequacy of the use of psychotropic drugs needs to be analyzed considering the scientific evidences. Objectives: To assess the appropriateness of drug prescriptions used by psychiatric patients in a public hospital in Sorocaba, according to the best available scientific evidence, and to describe the profile of this population. Methods: This cross-sectional study collected data from clinical records of patients with psychiatric disorders hospitalized in the psychiatric sector of the Sorocaba Hospital Complex, state of São Paulo, Brazil, between August 2015 and December 2016. The outcomes measured were: inappropriate use, presence of contraindication and serious or contraindicated drug interactions, according to the information available on the Dynamed® and Micromedex® 2.0 databases. Results: Patients were predominantly adults, and diagnosed with paranoid schizophrenia or bipolar affective disorder. Antipsychotics, benzodiazepines, and lithium accounted for 84.0% (n=2,938) of the 3,500 drugs prescribed for mental disorders. There were 2,157 (61.6%) inappropriate prescriptions, of which 81.9% corresponded to antipsychotics, benzodiazepines, and lithium. There were 1,712 prescriptions with drug combinations that risked causing drug interactions, predominantly involving antipsychotic use (67.0%). Conclusion: The study revealed a high number of inappropriate prescriptions, pointing to a need for greater prescription adequacy to ensure effective safe treatment for psychiatric patients.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要