
501 - 1000 employees
π₯ Healthcare
ποΈ Government
π€ Artificial Intelligence
Healthcare β’ Government β’ Artificial Intelligence
Commence is a healthcare data and technology company that delivers data-centered solutions to make health data more accessible, discoverable, and interoperable. The company pairs clinical expertise with AI-driven data transformation and a technology platform to address fraud, waste & abuse, independent dispute resolution, peer and independent reviews, quality improvement, and patient advocacy. Commence serves federal health agencies (CMS, VA, Defense Health Agency), state & local government programs, and commercial health customers, focusing on improving outcomes, accuracy, and program integrity.
π₯ 10 minutes ago
π΅ Arizona, Colorado, +24 more states β Remote
π΅ $130k - $160k / year
β° Full Time
π Senior
π Program Manager
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501 - 1000 employees
π₯ Healthcare
ποΈ Government
π€ Artificial Intelligence
Healthcare β’ Government β’ Artificial Intelligence
Commence is a healthcare data and technology company that delivers data-centered solutions to make health data more accessible, discoverable, and interoperable. The company pairs clinical expertise with AI-driven data transformation and a technology platform to address fraud, waste & abuse, independent dispute resolution, peer and independent reviews, quality improvement, and patient advocacy. Commence serves federal health agencies (CMS, VA, Defense Health Agency), state & local government programs, and commercial health customers, focusing on improving outcomes, accuracy, and program integrity.
β’ Serve as a subject matter expert (SME) in VA disability benefits adjudication and federal program analysis β’ Translate deep regulatory knowledge of VA disability rating criteria into structured business logic for AI model training and validation β’ Evaluate evidence sufficiency across VA disability claims β’ Support federal program delivery activities β’ Define and operationalize the regulatory and evidentiary definition of Ready for Decision (RFD) across targeted VA disability condition types β’ Produce a condition-by-condition RFD Criteria Reference Guide mapping evidentiary requirements to 38 CFR Parts 3 and 4 and M21-1 adjudication standards β’ Review and validate AI-generated determinations against the claim file or synthesized data; assess accuracy, reasoning quality, and correct identification of missing or incomplete development β’ Review AI-compiled medical records and generated assessments for completeness and validity against applicable rating criteria β’ Translate VA rating knowledge into structured business logic suitable for AI model training and workflow validation β’ Maintain a running Edge Case Log documenting claim scenarios where AI determinations are incorrect or incomplete, with specific regulatory citations β’ Provide ad hoc SME consultation on condition-specific standards, regulatory updates, and claims development pathways throughout program delivery.
β’ Minimum 2 years of direct compensation claim rating experience as a VBA Rating Veteran Service Representative (RVSR) β’ Broad familiarity across high-volume VA disability condition types and prior experience as a subject matter expert, trainer, or quality reviewer in a VA program context β’ Expert-level knowledge of 38 CFR Part 3 (Adjudication) and Part 4 (Schedule for Rating Disabilities) β’ Working knowledge of M21-1 adjudication procedures, including evidentiary sufficiency standards and Ready for Decision (RFD) criteria β’ Ability to assess the sufficiency of private medical records (PMR), service treatment records (STR), C&P exam reports, nexus opinions, buddy statements, VA Form 201 (personnel file) β’ Ability to translate complex regulatory knowledge into clear written deliverables β including analytical memos, criteria documentation, and structured feedback β suitable for technology development teams and senior executive audiences β’ Ability to obtain and maintain a VA Public Trust clearance.
β’ Reasonable accommodations for individuals with disabilities β’ Equal employment opportunity policies
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