Kidney Week 2025 Early Program - Advances in Research Conference 2025: Generative Artificial Intelligence in Kidney Disease Research and Management-Post-Trial Implementation and Clinical Decision Support

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Video Summary

Dr. Bashar Kadhim (Yale internist and clinical informatics specialist) explains why post-trial clinical decision support (CDS) is crucial to ensure effective therapies are actually adopted in practice. With hundreds of thousands of clinical studies and frequently changing guidelines, clinicians struggle to consistently apply recommendations during short visits, especially as fatigue and EHR data burden increase. CDS can close these gaps by delivering patient-specific, guideline-based recommendations at the point of care.<br /><br />He outlines the health IT context in Epic (development environments moving from proof-of-concept to test to production) and the phases of CDS development: build and validate cohort-identification logic, run a “silent” phase to verify accuracy, conduct a pilot with 5–10 clinicians for iterative feedback and optimization, design an effective interface and order sets, then obtain committee approval. Using examples like the PROMPT-LIPID and PROMPT-CKD trials, he describes dynamic, precision-style alerts that show why a patient qualifies and recommend tailored actions while reducing alert fatigue through adaptive rules.<br /><br />For multi-site scaling, he contrasts slow “PDF screenshot” build guides with Epic’s Turbocharger packages (XML) that can deploy builds in hours, though local configuration differences require adjustments. To standardize and speed data extraction, he proposes distributing parameterized Epic Report Workbench/Cogito SQL reports so sites can generate consistent CSV outputs without long analytics queues. For secure data sharing, he reviews SFTP, cloud platforms, and REDCap (with APIs enabling automated instrument creation and easy uploads). He concludes that stakeholder management and demonstrating ROI with data are key, and highlights a “new frontier” of engaging patients via MyChart education and tasks alongside clinician alerts.

Asset Subtitle

Bashar Kadhim

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Module ARC

Speaker Bashar Kadhim

Keywords

clinical decision support (CDS)

Epic EHR implementation

post-trial adoption of therapies

precision alerts and alert fatigue reduction

Turbocharger XML deployment

Cogito SQL and Report Workbench data extraction

MyChart patient engagement