2025•Fraser Health Authority

Patient Safety Learning System Platform

Improving patient safety event management and report generation

TailwindHealthcareWeb DesignData Visualization

Team

Managing Consultant, Data Scientists

Duration

January - Present

Role

UX/UI/Product Designer

Overview

The Fraser Health Quality Team is responsible for managing patient safety data and quality of care within the healthcare network. This information is shared site teams and used to drive discussions on improving safety practices.

The Problem

The Patient Safety Learning System (PSLS) is a tool used by the Fraser Health Quality Team to manage patient safety reports. Most reported incidents fall under harm levels 1 to 3 involving no harm, minor harm, and moderate harm events. These are often overlooked, as the team tends to prioritize level 4 and 5 incidents involving Severe Harm or Death. The problem with this is that the organization of these low harm events are not intuitive resulting in reports going unaddressed for prolonged periods of time, and trends have shown that some low harm events have escalated to high harm.

Solution

The Patient Safety Learning System Platform is a new tool that would access the reporting data from the legacy system and move the approach for addressing patient safety concerns from reactive to proactive.

  • Provides an AI Theming feature which would categorize the numerous amount of low and high harm reports.
  • A report-generating wizard that streamlines the report creation process and moves these to the site committees efficiently with user-friendly templates (Not included in MLP).
  • AI model that flags low-harm incidents with potential to escalate to high-harm incidents, encouraging early intervention.

Projected Results

  • Free up Resources: Quality team coordinators have more time to perform other tasks when they spend less of there day manually adjusting PSLS generated reports.
  • Improved Workflow: Organizing the harm events by theme can provide higher quality insights into drivers and areas affected.
  • Reactive to Proactive: By flagging low-harm events that could become a greater issue, teams can work quicker to address the problem before it escalates.

My Contribution

Discovery & Research

  • Researched modern web application interfaces and intuitive AI analytics tools.
  • Organized stakeholder interviews with Quality team directors and coordinators to understand pain points and processes for generating reports and data utilization.

Design & Testing

  • Created wireframes and high-fidelity designs using Figma.
  • Interviewed Fraser Health Quality team members for feedback and validation.
  • Ran usability tests with Quality team members for further feedback and support.

Key Takeaways

  • Designing for proactive action can shift how healthcare teams approach safety, moving from reacting to harmful events, towards preventing them.
  • AI-powered categorization helps make sense of overwhelming data, enabling teams to focus on patterns and systemic issues.
  • Close collaboration with stakeholders throughout the design process ensures the solution aligns with real-world needs.

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