Abstract
This study aimed to evaluate associations among variables in hospital pharmacy services. Thirty variables were used from the project Diagnosis of Hospital Pharmacies in Brazil pertaining to the overall description of the hospital, overall characterization of the hospital pharmacy service, and stages in pharmaceutical care. The statistical techniques were multiple correspondence and cluster analysis. Dimension 1 of the multiple correspondence analysis explained 90.6% of variance, differentiating between hospital pharmacy services based on the presence of certain activities, thus suggesting an axis of characterization for the hospital pharmacy services. The results indicate a direct relationship between compliance with the activities and the type of hospital and pharmacists with specialized training. Cluster analysis identified six clusters related to hospital size; greater compliance with the activities was associated with large hospitals and those with a pharmacist (more time dedicated to the hospital pharmacy service and higher level of training). The study concludes that the techniques were able to identify associations and a concise range of variables for a comprehensive evaluation of hospital pharmacy services in Brazil.
Highlights
O estudo objetivou avaliar a existência de associações entre variáveis de serviços de farmácia hospitalar
This study aimed to evaluate associations among variables in hospital pharmacy services
Thirty variables were used from the project Diagnosis of Hospital Pharmacies in Brazil pertaining to the overall description of the hospital, overall characterization of the hospital pharmacy service, and stages in pharmaceutical care
Summary
A análise de correspondência múltipla 6,7 é uma técnica multivariada capaz de analisar um conjunto grande de variáveis categóricas. Essa técnica é aplicada a uma matriz indicadora Z, formada por códigos binários, em que nas linhas (i) estão presentes os serviços de farmácia hospitalar e nas colunas (j) as categorias das variáveis. As coordenadas principais contêm os valores das posições dos pontos-linha e pontos-coluna para cada uma das dimensões utilizadas para construir o mapa de correspondência. O mapa de correspondência é formado pela projeção das coordenadas principais de linha e/ou de coluna nas duas ou três dimensões (eixos) de maior inércia (maior contribuição para a variabilidade dos dados). A contribuição relativa para a inércia (Ctrjd) é uma medida da variância do eixo dado por uma determinada linha (serviço de farmácia hospitalar) ou coluna (categoria) do mapa, indicando a importância da linha ou coluna para certa dimensão. As suplementares não interferem nos cálculos da análise de correspondência múltipla, mas podem ser usadas para auxiliar na interpretação dos resultados do mapa de correspondência
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