Uploaded June 2026 | Updated September 2026, 3 weeks ago
Your Real-World Evidence (RWE) pipeline shouldn't be the bottleneck. If you're spending programmer-weeks moving data from SQL to PowerPoint, you're doing work that could be automated.
In this demo, we’ll show you how to move from ad-hoc, manual study cycles to a reproducible, audit-ready pipeline on the infrastructure your organization already trusts.
Samiul Haque will walk through:
1. The end of the SQL bottleneck: How epidemiologists can query synthetic Medicare claims (OMOP CDM) using AI-assisted cohort exploration, running natively inside Snowflake via Snowflake Cortex.
2. Reproducible comparative effectiveness: Building propensity-scored analyses in a single Quarto document, from cohort definition to Cox modeling.
3. Audit-ready publishing: Generating interactive payer evidence packages (dashboards, forest plots, audit trails) that are accessible to reviewers without exposing your internal infrastructure.
If your team is running observational studies and you're tired of proving what you already know, join us. We’ll show you how to cut study turnarounds while extending your existing validation footprint.
_____
Instead of a large webinar Q&A for this session, we're hosting small-group sessions where you can connect directly with Posit and other community members to ask questions, share your own experiences, and have a real conversation. You can sign up here: posit.co/coffee-chat
Your Real-World Evidence (RWE) pipeline shouldn't be the bottleneck. If you're spending programmer-weeks moving data from SQL to PowerPoint, you're doing work that could be automated.
In this demo, we’ll show you how to move from ad-hoc, manual study cycles to a reproducible, audit-ready pipeline on the infrastructure your organization already trusts.
Samiul Haque will walk through:
1. The end of the SQL bottleneck: How epidemiologists can query synthetic Medicare claims (OMOP CDM) using AI-assisted cohort exploration, running natively inside Snowflake via Snowflake Cortex.
2. Reproducible comparative effectiveness: Building propensity-scored analyses in a single Quarto document, from cohort definition to Cox modeling.
3. Audit-ready publishing: Generating interactive payer evidence packages (dashboards, forest plots, audit trails) that are accessible to reviewers without exposing your internal infrastructure.
If your team is running observational studies and you're tired of proving what you already know, join us. We’ll show you how to cut study turnarounds while extending your existing validation footprint.
_____
Instead of a large webinar Q&A for this session, we're hosting small-group sessions where you can connect directly with Posit and other community members to ask questions, share your own experiences, and have a real conversation. You can sign up here: posit.co/coffee-chat
