AI-Enhanced Incident Reports: Identifying Root Causes and Tracking Trends
Hosted by FAHQ | Presented to the Healthcare Quality Collaborative
Speaker
Dr. Nicole Czubkowski, IE, LSSGB
Nicklaus Children's Health System, Miami, FL
Nicole Czubkowski is a healthcare strategy and transformation leader with experience driving operational improvement, risk reduction, and technology-enabled change across complex healthcare environments. Her work focuses on translating strategy into execution by redesigning processes, aligning stakeholders, and leveraging data, automation, and applied artificial intelligence to improve quality, safety, and financial performance.
About the Presentation
This presentation outlines how artificial intelligence can be integrated into existing incident reporting systems to improve patient safety, reduce subjectivity, and enable proactive risk management. Using Nicklaus Children's Health System as the case study, the presentation explains how a homegrown AI tool ("AskNick") is integrated with RL Solutions to analyze incident reports using natural language processing.
It will describe how AI can systematically review the brief factual descriptions within incident reports to generate a standardized problem list, assign parent and child categories, and identify root causes with greater consistency than traditional human review. Multiple validation trials with risk managers are highlighted, showing iterative improvements in accuracy and category refinement.
The presentation will discuss how AI categorized data can be leveraged for predictive modeling, trend analysis, and real-time dashboards. These capabilities allow organizations to identify high risk periods, correlate incidents with operational factors (such as census, acuity, and staffing), and implement proactive interventions — ultimately reducing manual workload, improving reporting timeliness, and strengthening patient safety outcomes.
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