Prescribing patterns of medication for respiratory diseases cluster analysis of the Portuguese electronic prescription database

Autores da FMUP
Participantes de fora da FMUP
- Sousa, A.
- Amaral, R.
- Fonseca, J.AB -
Unidades de investigação
Abstract
We aimed to describe, for the first time, the prescribing patterns among patients on persistent respiratory treatment, from the Portuguese electronic prescription and dispensing database. This was a one-year retrospective population-based analysis of prescriptions (n = 39810) for medication for respiratory diseases and exacerbations. Cluster analysis was applied based on medication and prescrib-ers’ specialty. Prescribing patterns were grouped and labelled as: possible medication for asthma and allergic rhinitis (General Practitioners-GPs and allergists to younger patients); COPD (GPs and pulmonologists to older patients); asthma or Asthma-COPD Overlap (GPs and pulmonologists); exacerbation, infection and relievers. This analysis was an important first step to understand the Portuguese reality on the treatment of respiratory diseases. © 2022 Associazione Allergologi Immunologi Italiani Territoriali e Ospedalieri-AAIITO. Published by EDRA SpA. All rights reserved.
Dados da publicação
- ISSN/ISSNe:
- 1764-1489,
- Tipo:
- Article
- Páginas:
- 229-239
- Link para outro recurso:
- www.scopus.com
European Annals of Allergy and Clinical Immunology EDRA S.p.A
Citações Recebidas na Scopus: 3
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Keywords
- Asthma; chronic obstructive pulmonary disease; cluster analysis; electronic prescribing; retrospective studies
Proyectos asociados
A machine learning-based approach to support the assessment of clinical coded data quality in the context of Diagnosis-Related Groups classification systems
Investigador Principal: José Alberto da Silva Freitas
Estudo Clínico Académico . 2020
Citar a publicação
Sousa A,Amaral R,Almeida R,Freitas A,Fonseca J-. Prescribing patterns of medication for respiratory diseases cluster analysis of the Portuguese electronic prescription database. Eur. Ann. Allergy Clinical Immunol. 2021. 65. (5):p. 229-239.