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Data Abstraction Quality – Lessons from Your Peers ...
Data Abstraction Quality – Lessons from Your Peers
Data Abstraction Quality – Lessons from Your Peers
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Video Transcription
Video Summary
The session, titled "Data Abstraction Quality Lessons from Your Peers," was moderated by a representative from the Heart Hospital Plano and featured presentations by Jennifer Waters from Baylor Scott & White, the Heart Hospital, and Vicky Van Meyder from Ohio Health in Columbus, Ohio. Jennifer Waters shared how her department transformed from merely surviving to thriving over the past year and a half. She attributed this success to teamwork, real-time data management, and process improvements, particularly by transitioning to a pod-based abstraction system. Jennifer emphasized the importance of maintaining real-time data, which prevents backlogs and allows proactive consultations with physicians. Her team manages 10 registries covering over 8,000 procedures and 6,500 follow-up visits annually. She also highlighted successful cross-training efforts that enabled her team to maintain quality data abstraction during staff shortages.<br /><br />Vicky Van Meyder discussed Ohio Health's approach to improving Inter-Rater Reliability (IRR) in cardiac registries. By shifting from a peer-to-peer review to a team-based IRR approach, they achieved more consistent and accurate data abstraction. She described how they engaged in roundtable discussions to reconcile discrepancies and improve processes, resulting in Ohio Health being recognized as a high-performing facility for data abstraction. Vicky stressed the importance of regularly reviewing and updating IRR practices to maintain data quality and leverage automation for efficiency. Both presenters emphasized the role of teamwork and continuous improvement in achieving excellence in data abstraction and quality assurance.
Keywords
Data Abstraction
Quality Assurance
Teamwork
Real-Time Data
Pod-Based Abstraction
Inter-Rater Reliability
Process Improvement
Cross-Training
Automation
Cardiac Registries
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