Mastering Medical Record Reviews: Accuracy, Compliance & the Human-in-the-Loop [Inovalon Empower] скачать в хорошем качестве

Mastering Medical Record Reviews: Accuracy, Compliance & the Human-in-the-Loop [Inovalon Empower]

As CMS and OIG increase scrutiny on risk adjustment and RADV audits, health plans face mounting pressure to ensure medical record review accuracy, compliance, and defensibility. In this Empower webinar, industry experts break down: • What’s changing in RADV audits • Why retrospective reviews raise red flags • How AI and analytics can support — not replace — human expertise • Real-world coding examples that trigger audit risk • Best practices for conservative, compliant diagnosis submission This session is essential viewing for: ✔️ Risk adjustment leaders ✔️ Coding and compliance teams ✔️ Health plan executives ✔️ Data, analytics, and AI strategy leaders ⏱ Chapters 00:00 – Medical Record Review & RADV Compliance: Session Overview 00:43 – Why CMS & OIG Are Intensifying RADV Audits 01:09 – Risk Adjustment Red Flags: The 99% Retrospective Review Problem 01:29 – In-Home Assessments Without Supporting Medical Evidence 02:13 – Payer Perspective on RADV Audits & Compliance Risk 03:21 – Coding Accuracy vs. Financial Impact for Health Plans 04:18 – Overpayments vs. Underpayments in Risk Adjustment Audits 05:00 – RADV Audit Expansion: What CMS Is Changing 06:14 – Federal Court Ruling on RADV Extrapolation Explained 07:10 – Coding Capacity Constraints & Workforce Challenges 08:46 – Why Risk Adjustment Data Accuracy Matters More Than Ever 09:58 – The 3 Pillars of a Compliant Medical Record Review Program 10:36 – Using Data & Analytics to Stratify Risk Adjustment Members 11:23 – Prospective vs. Retrospective Chart Reviews 12:25 – Monitoring & Measuring Risk Adjustment Program Impact 13:42 – Coding Technology Challenges in Complex Medical Records 14:59 – AI-Assisted Coding: Smarter Condition Recognition 15:44 – Why Human-in-the-Loop Is Essential for Compliance 18:44 – Real RADV Audit Examples: Where AI Alone Fails 19:07 – Coding Pitfall: “Suggestive Of” ≠ Diagnosed 20:16 – BMI, Secondary Codes & Missing Primary Diagnoses 21:18 – Diabetes, Renal Disease & Incorrect Attribution Errors 22:07 – Past Medical History vs. Active Conditions in Coding 23:20 – Cancer & Stroke Coding Rules Explained 24:19 – Best Practices for Conservative Diagnosis Submission 25:00 – Medical Record Retrieval & Digital Chart Access Challenges 26:49 – Final Takeaways: Accuracy, Compliance & Collaboration 🔔 Subscribe for more insights on risk adjustment, medical record review, and healthcare data analytics. --- Connect with us on social media Linkedin:   / inovalon   Facebook:   / inovalon   X:   / inovaloninc   Instagram:   / inovaloninc   Bsky: https://bsky.app/profile/inovalon.bsk... --- Inovalon Healthcare Empowered™ https://www.inovalon.com #Inovalon #medicalrecords #medicalrecordreview #CMS