A Collaborative Model for Improving Information Sharing among Cancer Care Groups using Software Engineering Principles
Davis Byamugisha, Francis Kamuganga, Adones Rukundo, John Businge
TL;DR
Problem: Delays in cancer case management arise from fragmented information sharing among care groups. Approach: A DES-based collaborative model inspired by GitHub version control and discretionary access control is implemented in AnyLogic to coordinate information flow across core teams and stakeholders. Contributions: A two-layer architecture (Core Team Collaboration and Information Access) plus a 7-step workflow demonstrates how to reduce delays and improve early diagnosis and survival prospects. Significance: The framework supports inclusive collaboration across clinicians, administrators, patients, and caregivers and can be extended to other chronic care management contexts, with future work focusing on real-world deployment and impact measurement.
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.