false
OasisLMS
Catalog
AUGS FPMRS Webinar: Clinical Prediction Models and ...
April14WebinarRecording
April14WebinarRecording
Back to course
[Please upgrade your browser to play this video content]
Video Transcription
Video Summary
Dr. Eric Jelocic, an Associate Professor of OB-GYN at Duke University, presented a webinar on Health Services Research at the FPRMS. He discussed the development and validation of patient-centered prediction tools for various women's health conditions, including pelvic floor disorders and urinary incontinence. Dr. Jelocic highlighted the importance of clinical prediction models in improving patient and clinician decision-making and emphasized the need for accurate and well-calibrated models. He also discussed the challenges and limitations of different types of prediction models, such as risk factor identification, counting risk factors, decision trees, and nomograms. Dr. Jelocic stressed the significance of validation in assessing the performance of prediction models and shared the Tri-Pod statement, which provides guidelines for reporting a model's development and validation. He also touched on emerging issues related to the regulation of prediction algorithms and the potential for algorithmic bias and unfairness in decision-making. Dr. Jelocic concluded the webinar by encouraging clinicians to consider incorporating prediction models into their practice to improve patient care and shared decision-making.
Keywords
Dr. Eric Jelocic
patient-centered prediction tools
women's health conditions
clinical prediction models
validation
Tri-Pod statement
algorithmic bias
decision-making
patient care
×
Please select your language
1
English