Research, technical methods, and realistic operating stories showing how healthcare teams investigate complex questions and act on what they find.
A landmark estimate puts overtreatment and low-value care at $98–131B a year in 2026 dollars. The strongest evidence supports precise identification, clinician feedback, and patient-inclusive follow-through—not blanket controls.
Read more
How real-world usage, harder benchmarks, richer data structure, and connected context help Falcon become a smarter healthcare research partner.
Read moreA realistic look at how an ACO leadership team can connect data quality, utilization, provider performance, payment integrity, and network strategy before the next board meeting.
Read moreHow explainable billing profiles help healthcare teams spot meaningful provider changes, investigate potential FWA, and start better provider conversations.
Read moreWhat procedure co-occurrence reveals about care settings, practice models, and emerging payment-integrity concerns.
Read more
CMS ships the monthly and the annual final Model Output Report with byte-identical record layouts — the only thing distinguishing them is the dataset name, and that name rarely survives the parse. Stack the files together and you double-count risk scores. Deduplicate them and you may delete the settled year-end scores outright. The fix is two date fields read in the right direction.
Read moreA plain-language walkthrough of how Medicare overpayments happen, who becomes liable once one is identified, and why contestations—the flip side of overpayment—are a recovery opportunity most risk-bearing orgs leave on the table.
Read moreEnterprise organizations with OpenAI or Anthropic accounts can now connect their LLM platforms directly to Falcon's proprietary healthcare data—and seamlessly hand off to Falcon for deeper investigation without losing context.
Read moreThe first in our research brief series. Medicare spending on urinary catheter codes A4352 and A4353 jumped roughly 20x in two years — and ACOs absorbed the cost. Download the full white paper.
Read moreMost ACOs sit on claims data that could surface millions in billing irregularities — but lack a clear strategy for acting on it. Here's how structured, evidence-based outreach gets providers to self-correct without formal enforcement.
Read moreMedicare Advantage membership is a moving target — Medicaid eligibility shifts, CMS databases lag, and if you miss a rejection without proactively reaching out, the loss is yours. We built the Transaction Monitor so plans can stay on top of every enrollment transaction, year-round.
Read moreNew Pulse Landscape views and Web Search Agent give you instant access to thousands of facilities and providers across ACOs, FQHCs, and SNFs — powered by public and proprietary data sources.
Read moreWhy we're building AI that starts as your conversational partner and evolves into the autonomous intelligence layer running your healthcare operations. The gap in the market, what we're learning, and where this is all heading.
Read moreLoad specialized healthcare knowledge, SQL templates, and analytical frameworks into your AI conversations. Skills transform complex domain expertise into reusable, shareable building blocks.
Read moreSet up recurring AI-powered reports delivered daily, weekly, or monthly. Turn your one-time data pulls into automated workflows that keep your team informed.
Read moreGet started with Falcon Health in three simple steps. From signing in to exploring Sentinel and Pulse, we'll show you the way.
Read moreIntroducing Pulse & Sentinel v0.0.14—the first step in our vision to eliminate coordination overhead. When lean, expert teams can execute directly without handoffs, healthcare analytics moves at the speed of thought.
Read moreIntroducing Pulse & Sentinel v0.0.13—removing the three fundamental bottlenecks in healthcare analytics: opaque AI, fragmented data, and technical barriers. Now with transparent tool usage, unified data access, and automatic visualization generation.
Read moreTo effectively combat healthcare fraud, we need to think like fraudsters. Learn how understanding fraudster tactics (from timing and threshold gaming to identity manipulation) reveals critical system vulnerabilities and enables more effective fraud detection.
Read moreMost healthcare data platforms make you jump through hoops before you can evaluate if they're right for you. We think that's backwards. Now you can try Pulse, Scope, and Sentinel (all three products) with just an email address.
Read moreWith healthcare fraud draining $760+ billion annually, pattern-matching detection methods are fighting a losing battle. Learn how investigative AI agents are revolutionizing fraud detection by reasoning like human experts instead of memorizing historical cases.
Read moreManual fraud investigation across internal datasets, digital footprints, and public records takes weeks. Our AI agent orchestrates specialized sub-agents across all three data pillars, delivering comprehensive investigation reports in hours instead of days.
Read moreDespite impressive general intelligence, AI models struggle with specialized healthcare fraud detection. The gap isn't capability, it's context. Here's how Falcon AI bridges general intelligence to actionability by giving AI the right domain-specific tools, achieving 8.3/10 performance vs 6.5-7.2 for baseline models.
Read moreThe Medicare Coverage Database governs $32 billion in improper payments yet finding relevant policies requires navigating 10,000+ documents with inconsistent medical terminology. Current search tools fail, forcing analysts to manually hunt through irrelevant results. Here's how Falcon Healthcare built AI that actually understands healthcare data.
Read more
When "recession-proof" becomes free-fall, and billions vanish overnight
Read moreStop being blindsided by utilization spikes and fraud schemes that traditional analytics miss. See how enhanced completion factor methodology with adaptive service grouping transforms reactive payers into proactive ones.
Read moreHHS-OIG revealed their keystroke error detection algorithm in 2023. We analyzed real client data and found 12.81% of I110 codes might be I10 typos, representing millions in audit exposure.
Read moreHow we built custom domain-driven tools for our AI investigator to navigate Medicare coverage databases, turning fuzzy policy language into precise, searchable criteria that dramatically improve fraud detection accuracy.
Read more