On Demand: Addressing the Pervasive Burden of Delayed Identification of Disease-Webinar Recording

Video Transcription

Video Summary

The webinar addresses the widespread problem of delayed disease identification—especially in structural heart programs—as patient volumes and guideline-based eligibility expand faster than systems can operationally manage. Speakers present Cedars-Sinai as a “blueprint” for improving timely treatment by combining better patient identification with streamlined care-pathway tracking.<br /><br />Biome’s team explains how hospitals are “data rich but insight poor,” with clinicians and administrators often relying on different, mistrusted data sources. Biome integrates registry-quality clinical data with administrative/financial data to pinpoint high-yield improvement opportunities, quantify the cost of complications, and track ROI of quality initiatives. A key module is Biome’s cloud-based Echo Surveillance engine, which uses clinically intelligent NLP to convert unstructured echocardiogram reports into structured severity classifications and actionable patient lists. This supports early detection of untreated valvular disease, improving outcomes and reducing costly urgent/emergent interventions. Benchmarking data highlighted major cost differences between elective and urgent TAVR, reinforcing the financial and clinical value of earlier intervention. In one center, Biome processed 26 million rows across 185,000 patients and identified thousands with untreated aortic stenosis; within eight weeks, Cedars screened 200 additional TAVR candidates, completed 40+ elective TAVRs, and generated over $1M in added margin.<br /><br />Cedars-Sinai then operationalized care delivery inside Epic using Epic’s Structural Heart Patient Tracking Tool, customized smart forms, phase-based tracking, automated checklist tasks, reports, and dashboards to replace manual “sticky note” workflows. The build required iterative collaboration over 12–18 months and clinician champions. Speakers emphasize benefits: fewer crisis presentations, better scheduling and capacity, improved follow-up compliance, reduced burnout, and expansion to other valve diseases and broader cardiology use cases.

Keywords

valvular heart disease

delayed identification

Epic EHR system

Biome cloud analytics

AI echo report analysis

urgent TAVR to elective conversion

patient tracking tool

clinical and financial data integration

early intervention outcomes

interdisciplinary collaboration

delayed disease identification

structural heart program

aortic stenosis detection

TAVR elective vs urgent

echocardiogram NLP

Echo surveillance engine

Epic Structural Heart Patient Tracking Tool

care pathway tracking dashboards