We are seeking experienced medical billers to review and assess AI-generated outputs related to durable medical equipment (DME) billing, with a focus on claim lifecycles, payer rules, documentation sufficiency, and denials/appeals handling.
You will work asynchronously on a dedicated review platform, performing short, structured evaluations to help train and refine AI models to support DME revenue cycle workflows.
This is a remote, flexible and short term project (~2-3 months)
Key Responsibilities:
Reviews & Issue Identification: Perform structured reviews of AI outputs, assessing intake, eligibility/benefits, prior authorisations, coding, submission, payment posting - flagging errors, omissions and compliance risks.
DME Documentation Validation: Verify presence and adequacy of physician orders, proof of delivery, same/similar checks, rental vs. purchase documentation and medical necessity.
Payer Rules & Lifecycle Checks: Validate payer rules, frequency limits, coverage determinations, timely filing and claim readiness.
Denials & Appeals Assessment: Classify denial reasons, propose corrective actions, assemble needed supporting documents, and outline appropriate reconsideration/appeal pathways and resubmission strategies.
Feedback & Continuous Improvement: Provide clear, actionable feedback to refine guidelines, identify edge cases and improve AI-assisted decisioning and mapping.
Qualifications:
DME billing experience: Minimum 2 years of experience.
Knowledge: Strong understanding of claim lifecycles, DME documentation, payer rules, denials and appeals.
Attention to detail: Proven track record of accuracy and consistency in medical billing.
Technical proficiency: Comfortable using structured data labeling tools and digital platforms.
Language: Professional working English proficiency for written deliverables.
Legal Status
You will have the right to work in your country of residence.
You will work as an independent contractor.
Why Join Us?
Flexible Work Arrangements: Part-time and remote work options available.
Competitive Compensation: Hourly compensation in line with level of experience.
Professional Development: Gain hands-on experience in data labelling, AI model fine-tuning and contributing to the future of medical billing.
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