Prior Authorization Specialist

Prior Authorization Specialist

DeliverHealth is seeking an experienced Prior Authorization (PA) Specialist to support the continuous improvement of InstaAuth, DeliverHealth's AI-powered and agentic Prior Authorization platform.

The primary responsibility of this role is to evaluate the quality, accuracy, completeness, and efficiency of the AI-driven Prior Authorization workflows executed by InstaAuth. The specialist will review AI-generated prior authorization requests, validate clinical documentation and payer requirements, identify workflow failures, false approvals, false denials, missing information, and automation gaps, and provide structured feedback to Product Management, AI Engineering, and R&D teams.

This is not an operational Prior Authorization processing role responsible for submitting authorizations on behalf of providers. Instead, this is a Product Quality and Clinical AI role focused on continuously improving the intelligence, reliability, and automation capabilities of the InstaAuth platform.

The role serves as the bridge between Prior Authorization operations, payer requirements, clinical documentation, revenue cycle management, and AI product development.

Job Duties & Responsibilities

1. Validate AI-Driven Prior Authorization Workflows

Review end-to-end Prior Authorization workflows executed by InstaAuth to determine whether the AI:

• Correctly identified procedures requiring prior authorization.
• Selected the appropriate payer-specific workflow.
• Collected all required clinical documentation.
• Retrieved the correct payer criteria and medical policies.
• Completed authorization forms accurately.
• Identified missing clinical information.
• Applied payer rules correctly.
• Generated appropriate clinical justification.
• Routed cases to the correct workflow.
• Recommended the appropriate next action.

Assess whether each workflow is:

• Accurate
• Complete
• Clinically appropriate
• Compliant with payer requirements
• Ready for submission
• Optimally automated

2. Audit AI-Generated Authorization Packages

Review authorization packages generated by InstaAuth, including:

• Clinical summaries
• Supporting documentation
• Physician notes
• Diagnosis codes
• Procedure codes
• Medical necessity narratives
• Attachments
• Clinical evidence
• Authorization questionnaires
• Payer-specific forms

Verify that all required information has been captured and organized correctly.

3. Evaluate AI Decision Quality

Validate the AI's ability to:

• Identify documentation deficiencies.
• Recommend additional clinical evidence.
• Detect payer-specific documentation requirements.
• Flag missing medical necessity.
• Suggest alternative documentation.
• Identify coding inconsistencies.
• Recognize authorization exceptions.
• Determine authorization urgency.

Categorize findings as:

• Correct recommendation
• Missing recommendation
• False positive
• False negative
• Incomplete workflow
• Incorrect payer interpretation
• Incorrect clinical recommendation

4. Perform AI Quality Audits

Conduct structured quality audits by measuring:

• Workflow accuracy
• Automation success rate
• Clinical accuracy
• Documentation completeness
• Medical necessity validation
• Payer rule compliance
• Precision
• Recall
• False positive rate
• False negative rate
• Human intervention rate
• Exception handling quality

Maintain quality scorecards and trend analyses.

5. Continuous Product Improvement

Partner closely with Product Management and Engineering teams by providing structured feedback on:

• Workflow failures
• Missing automation opportunities
• Incorrect payer logic
• AI reasoning gaps
• Clinical documentation deficiencies
• Prompt improvements
• Workflow optimization
• User interface improvements
• Automation recommendations
• Confidence scoring enhancements

Participate in recurring Product Quality Review meetings.

6. Payer Knowledge Management

Support Product and AI teams by developing:

• Payer-specific authorization rules
• Clinical policy libraries
• Authorization scenarios
• Gold-standard reference cases
• Exception workflows
• Escalation guidelines
• Authorization knowledge base
• Clinical documentation requirements by payer

Assist in maintaining payer rule accuracy as policies evolve.

7. Specialty-Specific Optimization

Review authorization workflows across specialties such as:

• Orthopedics
• Cardiology
• Gastroenterology
• Imaging & Radiology
• Pain Management
• Oncology
• Behavioral Health
• Neurology
• Physical Therapy
• General Surgery

Recommend specialty-specific workflow improvements.

8. Cross-Functional Collaboration

Work closely with:

• Product Managers
• AI Engineers
• Machine Learning Engineers
• Prompt Engineers
• Clinical Informaticists
• Revenue Cycle Specialists
• Prior Authorization Operations
• QA Engineers
• Data Scientists
• Customer Success teams

Translate operational insights into actionable product requirements and acceptance criteria.

Key Deliverables

• Weekly AI workflow validation reports
• Prior Authorization quality scorecards
• False positive and false negative analyses
• Workflow failure reports
• Automation gap assessments
• Root cause analyses
• Product enhancement recommendations
• Payer-specific feedback reports
• Specialty optimization recommendations
• Gold-standard authorization test cases
• Monthly AI performance trend reports

Knowledge, Skills, & Abilities

Technical Knowledge

Strong understanding of:

• Prior Authorization workflows
• Medical Necessity
• Utilization Management
• Payer Policies
• Clinical Guidelines
• ICD-10-CM
• CPT
• HCPCS
• Revenue Cycle Management
• Clinical Documentation
• Healthcare Compliance
• AI-assisted clinical workflow automation
• Electronic Health Records (Epic, athenahealth, Cerner, eClinicalWorks, etc.)

Core Competencies

• Strong clinical judgment
• Excellent analytical skills
• Attention to detail
• Ability to identify documentation gaps
• Root cause analysis
• Data-driven decision making
• Effective written communication
• Cross-functional collaboration
• Continuous improvement mindset
• Passion for healthcare AI and clinical innovation