Dynamic Analysis of Hospital Data: An Interactive Approach to Health Management

  • Vinícius Pedroso PUCRS
  • Artur Kniest PUCRS
  • Giovanna Castro PUCRS
  • Isabel H. Manssour PUCRS

Abstract


The growing volume of data from DATASUS, including hospital admission records, presents challenges such as a lack of standardization and incompleteness. Visual exploratory analysis emerges as an effective tool to facilitate its interpretation and assist in decision-making. This work aims to apply interactive visualization and data exploration techniques to analyze hospital occupancy in Rio Grande do Sul, providing an online dashboard that allows queries about hospitalizations in the region. The tool enables the analysis of, for instance, the most common procedures and the distribution of hospitalizations over a year, providing information for a more efficient allocation of hospital resources.

References

da Silva, B. N., Costa, M. A. S., Abbas, K., and Galdamez, E. V. C. (2017). Eficiência hospitalar das regiões brasileiras: Um estudo por meio da análise envoltória de dados. Revista de Gestão em Sistemas de Saúde, 6(1):76–91.

Ferdib-Al-Islam, Robbani, R., and Ullah, M. W. (2022). Cov-hm: Prediction of covid-19 patient’s hospitalization period for hospital management using smote and machine learning techniques. In Proceedings of the 2nd International Conference on Computing Advancements (ICCA), page 25–33, NY, USA. Association for Computing Machinery.

Kandogan, E., Balakrishnan, A., Haber, E. M., and Pierce, J. S. (2014). From data to insight: work practices of analysts in the enterprise. IEEE Computer Graphics and Applications, 34(5):42–50.

Keim, D., Kohlhammer, J., Ellis, G., and Mansmann, F. (2010). Mastering the information age solving problems with visual analytics. Eurographics Association.

Mascarenhas, M. D. M. and Barros, M. B. d. A. (2015). Evolução das internações hospitalares por causas externas no sistema público de saúde - Brasil, 2002 a 2011. Epidemiologia e Serviços de Saúde, 24:19 – 29.

Milani, A. M. P., Loges, L. A., Paulovich, F. V., and Manssour, I. H. (2021). Prava: Preprocessing profiling approach for visual analytics. Information Visualization, 20(2-3):101–122.

Organization, W. H. (2021). Global strategy on digital health 2020-2025. Licence: CC BY-NC-SA 3.0 IGO.

Preim, B. and Lawonn, K. (2020). A survey of visual analytics for public health. In Computer Graphics Forum, volume 39, pages 543–580. Wiley Online Library.

Secco, C. A., Sina, L. B., and Nazemi, K. (2024). Medical visual analytics - an interactive approach for analyzing electronic health records. In 2024 28th International Conference Information Visualisation (IV), pages 143–149.

Souza, L. L. d. and Costa, J. S. D. d. (2011). Internações por condições sensíveis à atenção primária nas coordenadorias de saúde no rs. Revista de Saúde Pública, 45(4):765–772.
Published
2025-06-09
PEDROSO, Vinícius; KNIEST, Artur; CASTRO, Giovanna; MANSSOUR, Isabel H.. Dynamic Analysis of Hospital Data: An Interactive Approach to Health Management. In: UNDERGRADUATE RESEARCH WORKS CONTEST - BRAZILIAN SYMPOSIUM ON COMPUTING APPLIED TO HEALTHCARE (SBCAS), 25. , 2025, Porto Alegre/RS. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2025 . p. 31-36. ISSN 2763-8987. DOI: https://doi.org/10.5753/sbcas_estendido.2025.7234.