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Co-Founder
Courtney Hoatson
RHIA, CDIP, CCS, CRC, LSSGB
A healthcare informatics professional and certified coding specialist whose work brings together clinical expertise, documentation integrity, and transparent AI reasoning. With nationally recognised credentials across health information management, CDI, risk adjustment, and coding, she leads Claire with a clear focus: building practical AI that strengthens clinical judgment and supports healthcare professionals with clarity and confidence.
14 articles by Courtney Hoatson
- AIBest AI Medical Coding Assistants for Coders 2026Autonomous coding or AI-assisted augmentation? A comparison of CodaMetrix, Nym, Fathom, Solventum, RapidClaims, Optum and CLAIRE, and why vendor accuracy numbers deserve scrutiny.
- Medical CodingClaire AI for POA Indicator Accuracy: Preventing Hospital-Acquired Condition Reporting ErrorsClaire AI improves POA indicator accuracy by analyzing the clinical timeline for each diagnosis, flagging HAC-program conditions, and preventing the over- and under-reporting errors that drive unfair quality penalties.
- Medical CodingClaire AI for HCC Coding and Risk Adjustment: Capturing Accurate RAF ScoresClaire AI helps risk adjustment teams capture accurate RAF scores—identifying all qualifying HCC conditions, validating documentation specificity for RADV audits, and generating compliant queries while avoiding overcoding.
- Medical CodingHow Claire AI Boosts Inpatient Coder Productivity by 15-30%Claire AI lifts inpatient coder productivity 15-30% by eliminating time-consuming work—automating documentation review, accelerating code selection, cutting supervisor escalation 40-60%, and preventing rework through quality validation.
- Medical CodingClaire AI vs Traditional Computer-Assisted Coding: What Is the Difference?Claire AI differs from traditional CAC systems in three ways: clinical reasoning over keyword matching, collaboration over replacement, and educational explanations that build coder knowledge. A full comparison vs CAC, autonomous, and manual coding.
- AIUnderstanding SOI and ROM: How Complication and Comorbidity Coding Impacts Hospital Quality MetricsSeverity of illness and risk of mortality scores are the invisible architecture behind hospital quality measurement. How CC and MCC coding drives SOI and ROM, and how to capture the conditions that are commonly missed.
- AICalculating ROI on AI Medical Coding Investments: A Financial Guide for Healthcare LeadersHealthcare organizations typically reach positive ROI on AI coding within 6-12 months, with three-year returns of 200-400%. A financial framework covering TCO, value drivers, and realistic timelines.
- Medical CodingHow AI Improves Inpatient Medical Coding and DRG Assignment AccuracyInpatient coding drives hospital reimbursement through DRG assignment. AI captures principal diagnosis, secondary diagnoses, and CC/MCCs to deliver 15-25% CMI improvement, 30-40% fewer DRG mismatches, and 95-97% accuracy.
- Medical CodingIntegrating AI Medical Coding with Electronic Health Records: The Complete Technical GuideAI coding integrates with EHRs through HL7 FHIR APIs, native vendor APIs, or middleware. Deep integration takes 3-9 months and delivers 40-60% efficiency and 25-35% accuracy gains over standalone systems.
- AIMedical Coding AI Agent vs. Medical Coding Assistant: Understanding the DifferenceA medical coding AI agent acts autonomously to process and code charts with minimal human intervention, typically handling routine cases independently. A medical coding AI assistant supports human coders by providing recommendations, explanations, and guidance while the coder remains the final decision-maker. Research shows that AI assistant models achieving human-AI collaboration deliver 0.93 F1 accuracy, outperforming both fully autonomous agents (0.80-0.84) and human-only coding (0.72). For healthcare organizations, the assistant model provides better accuracy, compliance safety, and coder development.
- ComplianceMedical Coding Compliance in the AI Era: Navigating Regulations and RiskMedical coding compliance in the AI era requires maintaining human accountability while leveraging artificial intelligence for accuracy improvements.
- AIMedical Coding AI Assistant: What to Look For in 2026When selecting a medical coding AI assistant, prioritize explainability, clinical accuracy, workflow integration, and human control.
- Medical CodingCommon Medical Coding Mistakes That Cause CPC Exam FailureThe CPC exam is one of healthcare’s toughest certification tests. Learn the mistakes that cause most failures—and proven strategies to pass.
- AIWhat Is a Medical Coding AI Assistant? A Practical Guide for Remote CodersA practical guide to medical coding AI assistants for remote coders and certification students, how they work, key capabilities, and what to look for.
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