Mobile Application for Enhanced Child Abuse Detection and Documentation

Child abuse victims are frequently undiagnosed or misdiagnosed due to clinicians' limited access to high-risk signs and limited knowledge of injury patterns. Existing research is abundant but not readily accessible to frontline clinicians, leading to potential delays in detection and intervention. There is a need for a mobile, user-friendly solution that allows healthcare providers to quickly assess, document, and review injury data without compromising patient confidentiality.

A pediatric healthcare institution seeking innovative tools to improve early detection of child abuse and support clinical decision-making.

• Make comprehensive child abuse research data accessible via a mobile application to enable rapid reference during clinical assessments.
• Design an intuitive, easy-to-use interface that facilitates quick information retrieval while maintaining content richness.
• Integrate an interactive 3D human model to accurately document and visualize injuries across skin, skeletal, and internal organs.
• Implement injury documentation features that support quick, precise input without storing identifiable patient data, ensuring compliance with privacy regulations.
• Support clinicians in enhancing diagnosis accuracy and early detection of abuse cases through guided assessments.

• Secure, mobile-accessible interface for easy reference to child abuse symptoms and injury patterns.
• Interactive 3D human model allowing clinicians to document injuries on skin, skeletal, and internal organs.
• Question-based symptom assessment to guide clinical suspicion of abuse.
• In-app injury documentation with options for annotations and highlighting injury areas.
• Ensuring HIPAA compliance by avoiding storage of personally identifiable information (PII).

• Access to authoritative child abuse research databases for referencing data.
• Optional integration with hospital electronic health record (EHR) systems for injury reporting (without storing PII).

• High responsiveness to support quick assessments, targeting under 2-second load times.
• Strict adherence to HIPAA and data privacy regulations by not storing patient-identifiable data.
• Scalability to accommodate increasing user base across multiple healthcare facilities.
• Offline access capabilities to support use in low-connectivity settings.

The project aims to enhance early detection rates of child abuse by providing clinicians with rapid, reliable access to research data and advanced injury visualization tools. Expected impacts include improved diagnostic accuracy, quicker intervention times, and reduced oversight of abuse cases, aligning with best practices for safeguarding children and potentially saving lives.