A new study proposes an advanced forecasting methodology to enhance cancer treatment planning within Brazil’s Unified Health System (SUS). Developed by researchers at the State University of Rio de Janeiro (UERJ), the plan leverages scientific evidence and patient experience to optimize resource allocation and improve access to care.
The initiative introduces a technical framework for investment planning, aiming to refine the regulation of available positions within SUS. By prioritizing scientific evidence and focusing on the patient’s journey, the new approach seeks to enhance the overall effectiveness of cancer care delivery.
A comparative analysis conducted by the UERJ researcher revealed that the current methods employed in Brazil for cancer forecasting demonstrated lower performance across all tested cancer types when contrasted with the models developed in the study. This suggests a significant opportunity for improvement in predictive accuracy and resource management.
Given these findings, we suggest that the methods evaluated in our study be incorporated into the Inca forecasting methodology. The adoption of more modern and sensitive techniques can provide more accurate and useful estimates for public health planning. For future investigations, we also recommend deepening the comparison between machine learning based models.
Thaís Spiegel, researcher at UERJ
The study’s findings underscore the potential of advanced analytical techniques to inform public health strategies, particularly in complex areas like cancer treatment. The researchers advocate for the integration of these more sophisticated methods to ensure that planning and resource allocation are as precise and effective as possible, ultimately benefiting patient outcomes.
Collaboration for the digital look
