iCardio: Aplicação de Business Intelligence na Avaliação da Disparidade Regional da Assistência Cardiovascular com Dados do Mundo Real
Abstract
BACKGROUND: The assessment of cardiovascular care in Brazil is challenged by the country's vast territory and the large volume of data. Business Intelligence (BI) tools may enhance the visualization and utilization of such information to support public health decision-making. OBJECTIVES: To demonstrate the practical application of the interactive dashboard iCardio in analyzing regional inequalities in high-complexity cardiovascular care in Brazil. METHODS: Descriptive study based on secondary data made available by the iCardio dashboard, which integrates healthcare information from the Brazilian Unified Health System (SUS). Variables from 2019 were analyzed by region, considering service volume, mortality rates, hospital readmissions, and patient travel distance. RESULTS: Analyses of cardiovascular surgery and interventional cardiology procedures indicated that the Southeast region exhibited the lowest mortality rates (in-hospital: 5.65%, 30 days after procedure: 5.73%, and 30 days after discharge: 6.77%). The North had the highest mortality rates (in-hospital: 7.56%, within 30 days after the procedure: 7.7%, and within 30 days after discharge: 8.7%). The South and Central-West regions registered the highest readmission rates within 30 days after the procedure (9.79% and 10.3%, respectively) and within 30 days after discharge (11.7% and 11.97%, respectively). The South also presented the highest standardized procedure rate (10.54), nearly double that of the Southeast (6.02). The Northeast showed the longest mean patient travel distance (94.59 km). CONCLUSIONS: The use of BI through the iCardio dashboard enables rapid and accessible analysis of healthcare data, with the potential to inform evidence-based decision-making, optimize resource allocation, and identify regional disparities in cardiovascular care.
Fields of Study & Subjects
Artificial Intelligence in Healthcare and Education
Medical Coding and Health Information
Artificial Intelligence in Healthcare
Publication details
- Journal / source
- Arquivos Brasileiros de Cardiologia
- Publisher
- Sociedade Brasileira de Cardiologia
- Volume
- 123
- Issue
- 4
- Pages
- e20250765–e20250765
- Publication date
- 1 January 2026
- Language
- PT