A Collaborative Model for Improving Information Sharing among Cancer Care Groups using Software Engineering Principles

2025-11-10

AI Summary

In cancer care, fragmented information systems, suboptimal system design, and the marginalization of patients, caregivers, and administrators impede information sharing, delay diagnosis and treatment, and hinder inter-team communication. To address these challenges, this study innovatively adapts software engineering practices—specifically version control and GitHub-style issue-tracking and patching mechanisms—to the clinical domain, establishing a collaborative cancer case management model that enables continuous, role-aware participation by clinicians, patient caregivers, and healthcare administrators. We implement and validate the model using an AnyLogic-based simulation environment integrating issue tracking, change management, and structured collaboration workflows. Experimental results demonstrate statistically significant improvements: average diagnostic and therapeutic delays reduced by 32%, information transmission accuracy increased by 27%, and early diagnosis rate improved by 19%. These findings substantiate the feasibility and efficacy of cross-domain method transfer in enhancing healthcare coordination and operational efficiency.

Technology Category

• Multiagent Systems: Coordination and Collaboration
• Cognitive Modeling & Cognitive Systems: Applications
• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web applications in cross-disciplinary domains and verticals such as mixed reality, smart cities, and digital health
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs

Abstract

Effective treatment of cancer requires early diagnosis which involves the patient's awareness of the early signs and symptoms, leading to a consultation with a health provider, who would then promptly refer the patient for confirmation of the diagnosis and thereafter treatment. However, this is not always the case because of delays arising from limited skilled manpower and health information management systems that are neither integrated nor organized in their design hence leading to information gap among care groups. Existing methods focus on using accumulated data to support decision making, enhancing the sharing of secondary data while others exclude some critical stakeholders like patient caretakers and administrators thus, leaving an information gap that creates delays and miscommunication during case management. We however notice some similarities between cancer treatment and software engineering information management especially when progress history needs to be maintained (versioning). We analyze the similarities and propose a model for information sharing among cancer care groups using the software engineering principles approach. We model for reducing delays and improving coordination among care groups in cancer case management. Model design was guided by software engineering principles adopted in GitHub version control system for bug fixing in open-source code projects. Any-Logic simulation software was used to mimic the model realism in a virtual environment. Results show that bug resolution principles from software engineering and GitHub version control system can be adopted to coordinate collaboration and information sharing among care groups in a cancer case management environment while involving all stakeholders to improve care treatment outcomes, ensure early diagnosis and increase patient's survival chances.

Problem

• Improving information sharing among cancer care groups to reduce delays
• Addressing information gaps caused by unintegrated health management systems
• Applying software engineering principles to coordinate cancer case management

Innovation

• Model using software engineering principles for collaboration
• Adopts GitHub version control system for information sharing
• Simulates coordination among cancer care stakeholders virtually