Verified recordSoftware Development

Jami Morris

Sr Rcm Data & Decision Support Specialist at Webpt

Based in Williamsburg, United States

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Seniority

Other

Department

Other

Location

Williamsburg

Industry

Software Development

Company size

891

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Email

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j•••••••@webpt.com

Phone

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Background

About Jami Morris

Optimizing Healthcare Operations with Lean Six Sigma, Automation & Data-Driven Strategy Certified Lean Six Sigma Green Belt | CAPM | RCM Process Automation Architect I specialize in healthcare Revenue Cycle Management (RCM) optimization - leveraging Lean Six Sigma methodologies, automation, and data analytics to eliminate inefficiencies, reduce costs, and accelerate revenue cycles. With deep experience in no-code platforms and process redesign, I drive scalable, cross-functional improvements across complex healthcare ecosystems. Key Expertise: Lean Six Sigma Process Optimization – Led enterprise-wide improvements that reduced administrative burden, streamlined payer workflows, and enhanced revenue integrity Automation & No-Code Solutions – Built Zapier, SmartSuite, and AppSheet workflows that eliminate manual work, reduce error rates, and increase productivity Cross-Functional Leadership – Collaborated with Compliance, Finance, IT, and Ops leaders to centralize access, enhance transparency, and standardize procedures Data-Driven Strategy & Reporting – Unified fragmented data sources to enable real-time dashboards, accurate forecasting, and smarter decision-making Strategic Impact Highlights: RCM Payer Portal Initiative – Standardized access for 600+ Members, improving compliance and eliminating inconsistent workflows Workflow Automation – Reduced 396+ monthly hours of manual effort through targeted automation initiatives Credential Management Overhaul – Transitioned to 1Password, saving 100+ hours monthly and enhancing security SSO & Portal Access Automation – Cut 750+ hours/month in manual processes, saving over $90K annually Lean-Based Process Improvements – Applied DMAIC and waste-reduction strategies to reduce rework and boost first-pass yield in RCM ops

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