Real-time tracking of clinician workload and errors using EHR activity
Integrating real-time clinical activity and behavioral responses for characterizing cognitive load and errors (IGNITE)
This project uses electronic health record activity and decision-support tools to see how clinician workload and behavior relate to mistakes and burnout that affect patient care.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Washington University NIH-funded |
| Lab location | 1 site (Saint Louis, United States) |
| Project ID | NIH-11143765 on NIH RePORTER |
What this research studies
From a patient perspective, the team will use data automatically recorded by the electronic health record—such as clicks, documentation time, and navigation patterns—along with behavioral signals to measure clinicians' cognitive load in real time. They will link these objective workload measures to documented errors and safety events to find patterns when mistakes are more likely. The project builds on pilot findings that EHR audit logs can track workload without adding surveys, and it will test decision-support approaches to reduce high-load situations. The aim is to develop tools or workflow changes that lower clinician stress and help prevent errors during care.
Who could benefit from this research
Good fit: Ideal candidates are patients who receive care at participating Washington University clinical sites where their routine EHR interactions and related safety events can be analyzed without extra visits.
Not a fit: Patients receiving care outside the participating hospitals or those expecting direct experimental treatments likely will not receive direct benefits from this systems-focused project.
Why it matters
Potential benefit: If successful, this work could lead to tools or workflow changes that reduce clinician overload and lower the risk of medical errors for patients.
How similar studies have performed: Early pilot work by this team and other studies suggest EHR audit logs can reflect clinician workload and link to burnout and errors, but applying real-time decision support to prevent errors is still relatively new.
Where this research is happening
Saint Louis, United States
- Washington University — Saint Louis, United States (Active)
Researchers
- Principal investigator: Kannampallil, Thomas George — Washington University
- Study coordinator: Kannampallil, Thomas George
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.