csapAIH: uma função para a classificação das condições sensíveis à atenção primária no programa estatístico R*

Abstract

Hospitalizations due to ambulatory care sensitive conditions (ACSC) are an indirect indicator of primary health care. A package in the R program was developed in order to automatize the classification of codes of the International Statistical Classification of Diseases and Related Health Problems - 10th Revision (ICD-10), according to the Brazilian list of ACSC, and provide functionalities for the management of the "reduced files" of the inpatient hospital authorization (AIH). The csapAIH package contains a homonym function, which reads the data according to its nature (file or data frame with AIH structure, or a factor with ICD-10 codes) and returns, according to defined options, a databank or vector containing the classification for the hospitalization. This article presents the package and the function csapAIH, its installation mode and use, and examples of its functionalities, which may add quickness, precision and validity to the research of ACSC in Brazil.

Pacote csapAIH: a Lista Brasileira de Internações por Condições Sensíveis à Atenção Primária no programa R

“…The incorporation of the read.dbc 8 function lets csapAIH read the compressed DATASUS files (.dbc format), which was one of the main limitations found in the first version of the package. 17 The independence of other software for expanding .dbc extension files ensures that data reading, management and analysis can be done with a single command script -even though it may possibly be long, or divided into several files that can be retrieved with another script. In the case of R and with the facilities of RStudio 3 (among others 4 ), the content and form of the results can also be reproduced.…”

“…Below we present the current situation of the package, with changes made with effect from version 0.0.1. 17 Version 0.0.2 was released in February 2018 and has not been published in the scientific literature. This article is focused on the use of the package, especially for working with AIH files.…”

“…Apart from tabulating cases occurring in a given region, its purpose was to classify each hospitalization according to the ACSC groups so that this information could be handled as a variable in the hospitalization database. 12,17 Since then changes have been made to optimize working with AIH files and to allow tables and graphs showing ACSC group distribution to be generated, thus facilitating the publication of results and reports of research on this indicator.…”

Forecast UTI: aplicativo para previsão de leitos de unidades de terapia intensiva no contexto da pandemia de COVID-19

“…In this context, one of the main uncertainties of Brazilian National Health System (SUS) hospital managers lies in forecasting the number of intensive care unit (ICU) beds needed for severe cases of the disease, taking into consideration the epidemic's temporal dynamics. With the aim of assisting Public Health decision-making, researchers have developed computerized tools 4,5 which, through the application of mathematical models, are able to estimate the daily number of new COVID-19 cases, based on distribution and severity of the disease, so as to be able to forecast its impact on capacity to provide ICU beds. In short, these methods make short-term forecasts based on official health data and, by means of online applications, enable users to adjust those data according to local needs.…”

Internações por condições sensíveis à atenção primária à saúde, 2008-2015: uma análise do impacto da expansão da ESF na cidade do Rio de Janeiro

“…Em outras palavras, por ser um indicador hospitalar, com sua lista brasileira construída pouco tempo após a Política Nacional de Atenção Básica (PNAB) de 2006, existem limites para sua utilização como parâmetro único de avaliação da APS, em que os atributos essenciais e derivados devem se desdobrar em diversas atuações da equipe multidisciplinar, a qual necessita convergir saberes para o cuidado integral dos usuários. Nesse sentido, é importante adotar estratégias que garantam a boa qualidade da informação, com a criação de rotinas e de programações estatísticas que sejam funcionais e que garantam agilidade, precisão e validade dos dados 27 .…”