Working Group Webinar Library

Home healthcare serves a growing population of older adults with complex chronic conditions. Identifying patients at high risk for emergency department visits or hospitalizations is crucial for targeting preventive interventions, yet current risk prediction models relying on electronic health record (EHR) data have suboptimal performance. Patient-nurse verbal communication during home visits may provide a rich additional data source to enhance these models.

Traditional systematic literature review (SLR) methodologies suffer from inefficiency due to their time-consuming and resource-intensive nature. Our goal is to improve this process by developing an efficient Intelligent Systematic Literature Reviews (ISLaR) system, using Generative Pre-Trained Transformer 4 (GPT-4), for real-time article screening and data extraction.

Recent developments in AI have demonstrated the potential for improving our ability to detect and diagnose cancers earlier. William Hsu will present three unique experience evaluating AI in multiple cancer screening scenarios.

Who is in control of the content of the progress note? What is truly required for billing purposes and what are we holding onto for the sake of tradition/habit? How can you regain control of your note and remove the bloat that has built up over the years?

STARR is Stanford’s single integrated data lake containing clinical data of different modalities from the three Stanford Hospitals and associated clinics. STARR contains “raw” and “analysis-ready” data as well as tools to analyze this data.