About the Project
Role: Product Designer
Objective: Enhance the accuracy and efficiency of surgical tool tracking, reducing the risk of tool misplacement and ensuring smooth surgical procedures by designing a mobile app that facilitated scanning of surgical trays.
Platform: Mobile
Task
I was responsible for designing this mobile app from the ground up. My job involved gathering user requirements, translating those into wireframes, and working with both the development team and medical professionals to ensure the interface was intuitive, reliable, and compliant with hospital standards.
Results
30% Reduction in Tool Misplacements: The app’s scanning feature allowed surgical staff to confirm each tool’s location, leading to fewer errors.
25% Increase in Surgical Preparation Efficiency: Nurses and attendings reported smoother workflows and faster setup times.
15% Reduction in Overall Surgery Time: With quick tool identification and real-time tracking, teams spent less time searching for instruments and more time focusing on patient care.
Situation
Operating rooms often rely on manual or outdated processes to track surgical tools. Ortolligence approached our agency, Digica, to solve this problem by creating a mobile application that would reduce the risk of tool misplacement and improve operating room efficiency. Surgeons needed fast identification of instruments, nurses needed minimal workflow disruptions, and IT staff required seamless integration with existing systems.
Action
Deep-Dive User Research
Interviews and Observations: I observed procedures and interviewed surgeons, nurses, and IT staff. Their feedback highlighted the need for an app that offered quick scanning, minimal navigation steps, and reliable performance under pressure.
Focus Groups: I hosted group discussions with operating room teams to refine key features such as real-time tool tracking and integrated safety checks.
Wireframing and Prototyping
Initial Wireframes: Based on user insights, I created simple wireframes that mapped out scanning flows, real-time inventory updates, and error notifications.
Iterative Refinements: Through regular feedback sessions, I made sure the interface felt natural for surgeons who often have limited time to tap through screens.
Collaboration with Developers
Technical Feasibility: I worked closely with our AI and machine learning specialists to align app design with image recognition capabilities.
User-Centric Adjustments: We focused on performance optimizations, ensuring the scanning feature worked accurately under hospital lighting conditions and across varying device hardware.
High-Fidelity Design and Testing
Polished Visuals: I introduced a clear, uncluttered layout with large icons for quick identification.
Beta Releases: A beta version was deployed in selected operating rooms. I gathered feedback on clarity, response time, and how well the app integrated into existing workflows.
Continuous Iteration: After each round of feedback, I revised the interface, refined scanning accuracy, and added prompts for missing or misplaced tools.
