Case StudyWound Management Cloud Data Platform
About This Project
Client specializing in predictive analytics, with a system that leverages AI to predict how a wound will heal using specialized image capture and analysis, was looking to expand their ecosystem to include a centralized datastore and cloud backend to enable clinical workflows and algorithm research, add connectivity with hospital and clinic networks, and support interoperability with clinical record keeping (EMR).
- Challenges
- Approach & Solution
- Outcomes
• Client has advanced clinical and scientific capabilities but limited experience with FDA regulated system development
• Cloud solution must integrate with existing system architecture as-is
• Solution must be extensible for future integration with EMR
• Documented user needs for clinician and data scientist user types
• Captured system requirements to achieve connectivity and remote user needs
• Developed architecture & design, including:
• Data models
• APIs
• Automated data synchronization mechanism
• Connectivity gateway
• Implemented software and executed verification
• Achieved goal of supporting clinical workflows and algorithm research, including:
• Images automatically synched to Cloud, key clinical data variables are extracted
• AI algorithm integrates image and clinical data for wound analysis
• Images can be analyzed against proprietary clinical database
• Objective and immediate assessment of wound healing with potential to predict the course of wound healing achieved