Back to all posts
Co-Founder
Valentina Gallegos
BA, CPC, CRC
A medical coding professional and Subject Matter Expert in Risk Adjustment and HCC coding, known for her strong focus on accuracy, compliance, and documentation quality. Her work helps connect clinical detail with better coding outcomes, supporting both healthcare standards and patient-centred care.
21 articles by Valentina Gallegos
- AIBest AI Medical Coding Tool 2026: Comparison GuideNo single platform is universally best. A side-by-side look at CLAIRE, Fathom, CodaMetrix, Nym Health and RapidClaims across autonomy, EHR integration, compliance and ROI, and where vendor accuracy claims diverge from independent testing.
- Medical CodingClaire AI for Surgical Procedure Coding: Mastering ICD-10-PCS with Clinical ReasoningClaire AI brings clinical reasoning to ICD-10-PCS surgical coding—determining root operations, validating device coding, and constructing accurate seven-character codes to prevent DRG errors and audit risk.
- Medical CodingHow Claire AI Reduces Inpatient Coding Audit Risk and Improves ComplianceClaire AI reduces inpatient coding audit risk with comprehensive pre-submission validation—catching missed diagnoses, POA errors, and unsupported severity coding before claims are submitted, while building audit-defense documentation and a proactive compliance culture.
- Medical CodingClaire AI and Sepsis Coding: Clinical Reasoning for Complex DiagnosesClaire AI brings structured clinical reasoning to sepsis coding—analyzing documentation against Sepsis-3 criteria, identifying organ dysfunction, and generating compliant queries to distinguish sepsis, severe sepsis, and septic shock.
- Medical CodingHow Claire AI Helps Inpatient Coders Write Better CDI Queries FasterClaire AI helps inpatient coders write compliant, physician-friendly CDI queries faster—identifying documentation gaps, generating ACDIS/AHIMA-compliant language, and improving physician response rates 20-30%.
- AIHow to Read Medical Documentation Like a Senior Coder: Developing Clinical Pattern RecognitionA skill-building guide for inpatient coders to develop the clinical reasoning, pattern recognition, and documentation analysis techniques that distinguish expert coding professionals.
- AIRevision vs Replacement Joint Procedures: Critical ICD-10-PCS Coding Differences for Inpatient CodersA detailed guide to distinguishing joint revision from replacement procedures with root operation selection, device value assignment, and clinical scenario analysis.
- AIThe Future of the Medical Coding Workforce in the AI EraAI will not eliminate coding jobs but fundamentally transform them. Human coders shift to quality oversight, exception management, CDI, and complex case resolution as the workforce evolves toward higher-skill roles.
- AIRemote Medical Coding with AI Assistance: Best Practices for Productivity and AccuracyA practical guide for remote inpatient coders using AI-powered coding assistants to overcome isolation challenges, maintain quality, and achieve productivity goals from home.
- AIAI's Role in Modern Revenue Cycle Management: Beyond CodingAI transforms revenue cycle management far beyond coding: prior authorization automation, charge capture optimization, denial prediction, intelligent payment posting, and predictive cash flow analytics. Organizations report 15-25% lower days in AR and 30-40% fewer denials.
- Medical CodingEmergency Department Coding with AI: Achieving Speed and Accuracy Under PressureED coding operates under unique speed and documentation constraints. AI assigns E&M levels, procedure codes, and diagnoses in real-time at 93-96% accuracy, cutting turnaround from 3-7 days to same-day and reducing denials 20-30%.
- Medical CodingAI Solutions for Outpatient Medical Coding: Challenges and OpportunitiesOutpatient coding is the highest-volume environment in healthcare. AI hits 94-97% accuracy on E&M selection, procedure coding, and modifiers, cutting turnaround from days to hours and lifting accuracy 20-35%.
- Medical CodingAI in Specialty Medical Coding: Cardiology, Orthopedics, Oncology, and BeyondSpecialty coding demands deep clinical knowledge. AI models trained on specialty-specific data hit 93-98% accuracy across cardiology, orthopedics, oncology, and radiology, beating general coding AI by 15-25%.
- ComplianceEnsuring Regulatory Compliance with AI Medical Coding Tools: A 2026 GuideAI coding enhances compliance through consistent guideline application, audit trails, and proactive risk flagging, but requires governance, human oversight, and validation to meet CMS, OIG, and payer requirements.
- Medical CodingReducing Claim Denials Through AI-Powered Medical Coding AccuracyCoding issues cause 40-60% of claim denials. AI-powered pre-submission validation cuts denial rates 40-50% by catching errors, missing documentation, and authorization gaps before claims reach payers.
- Medical CodingMedical Coding Accuracy: Proven Strategies to Achieve 95%+ in Your OrganizationAchieving 95%+ medical coding accuracy requires a comprehensive approach combining guideline knowledge, quality assurance, continuous education, and technology support — including AI tools that reduce error rates by 30–50%.
- AIThe ROI of Medical Coding AI Tools: Calculating Real Returns for Healthcare OrganizationsHealthcare organizations implementing medical coding AI tools typically achieve ROI within 6-12 months through reduced claim denials, productivity gains, and captured revenue from improved coding specificity.
- AIHow to Evaluate Medical Coding AI Platforms: A Comprehensive ChecklistA comprehensive, vendor-ready checklist to evaluate AI coding platforms: explainability, accuracy, workflow fit, guideline updates, oversight, security, costs, and pilot design.
- AIWill Medical Coding Be Replaced by AI?Will AI replace medical coders? The data says no — learn what employment trends, salaries, and real-world adoption show about the future of coding.
- AIHow AI Medical Coding Tools Improve Accuracy Through Explainable Clinical ReasoningMedical coding accuracy directly impacts healthcare reimbursement, compliance, and data quality.
- AIAI Medical Coders vs. Human Coders: Why Collaboration WinsWhy AI medical coders and human coders achieve better results together, backed by research on accuracy, efficiency, and real-world outcomes.
Experience Clinical Clarity Today
Join medical coding professionals who trust CLAIRE for accurate, explained guidance. Start your free trial - no credit card required. No EMR integration needed.
The AI Medical Coding Assistant,
Built for Real-World Clinical Workflows
© 2026 CLAIRE IT AI. All rights reserved.