Knowledge Management for Brazilian Cancer Care Services

Area of Science:

• Oncology
• Health Services Research
• Operations Research

Background:

• Brazil faces a complex cancer care scenario with nearly 600,000 new cases annually.
• Long waiting queues for cancer diagnosis and treatment are common, impacting patient quality of life and cure rates.
• Early diagnosis and timely initiation of treatment are critical for improving cancer patient outcomes.

Purpose of the Study:

• To develop a decision support system (DSS) to optimize cancer patient flow in Brazil.
• The DSS aims to improve the identification of access alternatives and appointment scheduling.
• The goal is to reduce patient waiting times for cancer treatment initiation.

Main Methods:

• The Theory of Constraints (TOC) was applied to identify bottlenecks in the patient treatment pathway.
• Discrete Events Simulation (DES) modeling was utilized to analyze and reduce patient waiting times.
• The study focused on improving resource allocation and scheduling within cancer care services.

Main Results:

• The developed DSS effectively identifies critical bottlenecks in cancer patient care pathways.
• Discrete Events Simulation demonstrated a significant potential for reducing patient waiting times.
• The system facilitates improved appointment scheduling and resource utilization for cancer treatment.

Conclusions:

• The integration of TOC and DES provides a robust framework for addressing inefficiencies in cancer care.
• The decision support system offers a viable solution to mitigate long waiting times for cancer patients in Brazil.
• Optimizing patient flow through such systems can enhance treatment accessibility, quality of life, and survival rates.