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Forbes
a day ago
- Business
- Forbes
A Data-Driven Fix For Orthopedic Practices Losing To Claim Denials
Sally Ragab, Founder & CEO @ Neunetix. Ask any orthopedic group what keeps their CFO up at night, and one answer dominates: denied claims. National surveys show that orthopedics now sees 9% to 11% of all claims rejected. In dollar terms, a 12-surgeon group billing $85 million a year could watch $8 to $10 million slip away before a single appeal is filed. In a recent article, I explored why the problem is worsening across healthcare. Building on this, a multisite analysis conducted by my company suggests that most leakage is preventable—and faster to plug than many administrators think. What We Studied Between April 2024 and March 2025, my company partnered with 12 independent orthopedic practices (across California, Texas, Florida and New York), which collectively submitted 1.26 million claims. We captured every rejection code, payer response time and downstream appeal outcome. Three findings stood out: 1. The overall claim denial rate dropped from 10.4% in the 12 months before the intervention to 6.7% during the six-month intervention period. 2. Preventable denials—such as those caused by missing claim modifiers or lapses in prior authorizations—fell from 64% to 28%. 3. Additionally, the average number of days that claims remained unpaid in accounts receivable decreased from 46 days to 38 days. To achieve this, all practices followed the same three-step process, which I will outline below. There was no need to hire additional full-time staff or change their electronic health record systems. Why Orthopedics Gets Hit Harder 1. High-Ticket Procedures: Hip- and knee-replacement bundles average between $30,000 and $32,000. One denial can wipe out the revenue from hundreds of physical therapy sessions—more than a year of visits for the average patient. 2. Modifier Complexity: Orthopedic procedures often involve complex coding and modifier usage, and many of the most frequently flagged CPT codes for CO-4 and PR-22 edits stem from this specialty—especially when modifiers are missing or missequenced. 3. Authorization Churn: Payers continue to ratchet up pre‑service checks. CMS now requires prior authorization for all hospital outpatient cervical spinal‑fusion procedures with disc removal, and insurance policies, like UnitedHealthcare's 2024 commercial policy, list every major arthroscopy CPT code as "prior authorization required." As a result, authorization‑related denials for outpatient claims jumped 16% in the past three years (registration required). The Three-Step Denial-Prevention Playbook Run a scrape and review electronic claims and payment files (known as ANSI 835/837 files) to identify which billing modifiers are most commonly linked to denials. In our cohort, simple left/right side coding errors (using -RT for right or -LT for left) accounted for 21% of preventable rejections. A one-hour meeting with the coding team to flag and prevent these errors led to a 2.3% point drop in the denial rate within just one month. Add a simple yes/no binary check to the scheduling system so that surgeries can't be booked unless a valid prior authorization ID is included. Clinics that enforced this safeguard reduced their authorization-related denials from 3.7% to 0.9% in just 90 days. A simple predictive model, trained on about 150,000 past claims, was used to flag new claims that were at high risk of denial. Only claims with a risk score of 0.70 or higher were sent to coders for review—everything else moved through automatically. This reduced the average coder workload by 41%, allowing staff to focus more on higher-value appeals. Financial Impact Across the 12 practices, net collections rose $6.4 million in the first six months—roughly $0.75 million per practice—while denial-related write-offs fell 52%. The average site reached cash-flow breakeven on the project in 51 days. Those numbers align with industry surveys, indicating that 65% of orthopedic denials are preventable and that 30% are never reworked at all. Quick Wins Orthopedic Leaders Can Implement Today As a summary, a focused audit of common billing modifier errors—followed by a short retraining session for coding staff—can lead to a 1.5 to 3 percentage-point drop in overall denials. This typically requires no more than two weeks. Next, adding a mandatory prior authorization field to the surgical scheduling system ensures that procedures can't be booked without a valid authorization ID. Clinics that adopted this safeguard saw authorization-related denials fall by 1 to 2.5 percentage points, with rollout taking about 30 days, including staff training. Finally, integrating a simple AI-based risk scoring tool into the claims submission process can further reduce denials by 2 to 4 percentage points. The tool should flag only the highest-risk claims for manual review, cutting coder workload by about 40% and letting teams focus on appeals and other high-value tasks. In my experience, most practices can launch this model within 60 days. Collectively, these steps can push denial rates below the 7.66% improper payment benchmark CMS reports for 2024. Why Act Now • Payer scrutiny is rising. The "State of Claims 2024" report notes a steady climb in authorization-related denials across all specialties, with orthopedics singled out for high-cost implant cases. • Providers feel the pinch. In Experian's 2024 survey, 73% said denials are rising and 67% said payments are taking longer to arrive. • CMS audits are looming. Improper payment probes increasingly target spinal and total-joint bundles; denial records factor into audit risk scores. The Bottom Line Denied claims shouldn't simply be a cost of doing business—they're a solvable data problem. Our field data proves that taking steps like a disciplined five-day audit, a hard scheduling gate and a modest machine-learning layer can slash orthopedic denial rates by one-third and return millions to the bottom line within a quarter. Your implants are cutting-edge—your denial-defense strategy should be too. Forbes Business Council is the foremost growth and networking organization for business owners and leaders. Do I qualify?
Forbes
26-06-2025
- Business
- Forbes
Healthcare's Denial Crisis Is Getting Worse—Unless Clinics Get Smarter With AI
Sally Ragab, Founder & CEO @ Neunetix. In early 2024, one of our clients, a specialty clinic in the Midwest, discovered it had unknowingly failed to submit over 6,000 claims due to a silent software integration failure. The result: nearly $200,000 in lost revenue, most of it unrecoverable due to expired filing windows. The culprit wasn't negligence or bad billing—it was fragmentation. It can create blind spots—leading to claim submission failures, missed deadlines, and preventable denials. Denied claims siphoned an estimated $260 billion from U.S. healthcare providers in 2024 alone. Specialty clinics—oncology centers, orthopedic practices, infusion providers—are hit hardest. Their margins are tight, their billing is complex and each denial cuts twice: once financially, and again in delayed or denied patient care. That's why the next wave of financial recovery in healthcare isn't coming from new payer contracts—it's coming from smarter tech. And AI, if used efficiently, is leading the way. The Real Cost Of Denials—And The Role Of AI Most providers still rely on a patchwork of systems to track, submit and appeal claims. When those systems don't integrate—or worse, when no one notices—they bleed revenue. AI can't fix everything. But it can predict denials before submission, help identify errors and even generate appeal language. When trained on the right data, it works fast, consistently and at scale. Our examination of 27 peer-reviewed and industry studies published between 2020 and 2025 found that models using advanced algorithms achieved AUROC scores between 0.82 and 0.92, which means it has an excellent predictive ability. Clinics that deployed those tools saw denial rates drop by up to 45%, shaving a median nine days off accounts receivable cycles and preserving roughly $1.4 million in annual savings per 100-bed equivalent each year. In short, today's off-the-shelf machine-learning tools already catch about nine out of 10 risky claims; exotic deep-learning models can do slightly better, but only if you feed them a million-plus past claims—far beyond what a typical clinic keeps on file. Why Specialty Clinics Feel The Pain First Specialty clinics face a perfect storm of challenges: high-cost drugs, evolving payer policies and thousands of diagnosis and procedure codes that need to match up precisely. One denial can equal a $10,000 loss. If one ICD-10 or HCPCS code is wrong—or out of date—the claim can be denied. And those codes change every year. When those denials stack up, clinics risk closing programs or closing entirely Adding to the chaos is the fact that insurers now use their own AI models to reject claims—models that providers often can't inspect. That creates an urgent need for transparency and speed on the provider side. AI won't eliminate denials entirely. But it can help level the playing field. A Five-Step Framework For AI Denial Management To help providers operationalize AI safely and effectively, I recommend this implementation roadmap: 1. Readiness Audit: Start by cataloging your denial categories, A/R metrics and critical claim data (CPT, HCPCS, ICD-10, prior-auth status). Dirty or missing 837/835 data accounts for up to 40% of predictive model errors. 2. Model Selection: Start simple. Boosted-tree models offer strong early performance and are interpretable—so your billing staff can see why a claim is flagged. Avoid 'black box' AI in healthcare. 3. Pilot And Back-Testing: Test the model in 'shadow mode' on a subset of claims for at least 90 days. Target a ≥20% precision lift before considering deployment. 4. Workflow Integration: Embed denial predictions directly into your EHR or billing software. Don't send billers hunting. Route high-risk claims to seasoned billers for pre-submission scrub or immediate appeal. 5. Continuous Governance: Retrain models quarterly. Audit for bias. Document your oversight. States like Connecticut are already drafting legislation that could require human review of AI-influenced decisions. Be ready. Ethics, Transparency And The Provider's Role Let me be clear: AI should not be used to deny care. Our mission at Neunetix is to protect access to care by helping providers recover revenue they've rightfully earned. That means appealing denials—not rubber-stamping them. This distinction matters. A 2025 AMA survey found that 60% of physicians worry AI could be used to systematically deny needed treatment. Transparency, override logs and clinician review should be standard practice. Done right, AI isn't a barrier to care—it's a lifeline for providers. The Bottom Line Specialty clinics don't have time to waste. With denial rates rising and payer rules getting harder to track, it's no longer optional to adopt smarter tools. It's essential. The clinics that embrace AI now—not as a magic fix, but as a smart assistant—will recover faster, protect more patient care and outperform peers still stuck in reactive mode. Knowing why you're getting denied isn't enough if you can't act on it quickly. And if your systems aren't talking to each other, neither are your dollars. Forbes Business Council is the foremost growth and networking organization for business owners and leaders. Do I qualify?
Forbes
16-04-2025
- Health
- Forbes
How AI Can Reshape Access To Specialty Medications
Sally Ragab, CEO @ Neunetix. In 1969, a psychologist named Philip Zimbardo conducted a now-famous experiment. He parked two identical cars in two neighborhoods: one in the Bronx, a high-crime area, and the other in Palo Alto, a quiet, affluent community. The car in the Bronx was quickly vandalized, stripped within hours. The Palo Alto car sat untouched. But then Zimbardo broke one of its windows. Within days, the once-pristine car was equally wrecked. Zimbardo's "broken window theory" suggested that environments left unchecked can lead to systemic dysfunction. I see healthcare facing its own version of this phenomenon. Prior authorizations, which I see as an outdated and fragmented process, have become the "broken window" of specialty medications—neglected, frustrating and quietly draining resources. But unlike in the 1960s, we now have tools that can help. I believe AI offers a path to not just patch the system but to reimagine it entirely. Prior authorizations for specialty medications are often managed manually—often involving faxes and phone calls. Providers report spending 12 to 15 hours a week on these tasks, which can result in delayed treatment, lost revenue and burned-out staff. For a patient waiting on chemotherapy or a biologic for Crohn's disease, that delay isn't just inconvenient—it can be life-altering. AI isn't just a buzzword in this space; it's a practical tool that's already making an impact. Here's what I witness it enabling within the healthcare space: • Real-time eligibility checks by analyzing patient insurance details the moment a prescription is entered. • Predictive denial prevention, flagging incomplete or noncompliant requests before they're submitted. • Natural language processing to extract clinical data from electronic health record notes, lab results and attachments without manual entry. • Automated submission and tracking across payer portals, with proactive alerts on missing information. In my direct experience, I've seen AI reduce approval times from 10 to 14 days to as little as two to three days. That's not theory—that's from real clinics we've partnered with. But AI doesn't work in isolation. To be successful, providers should: 1. Start with high-friction areas (e.g., oncology, rheumatology and rare disease) where prior authorization is frequent and urgent. 2. Involve clinical staff early to identify workflow pain points. 3. Choose AI tools that integrate directly into your electronic health records and don't force a new UI. 4. Review audit logs regularly and tune your AI models to local payer patterns. AI in healthcare raises valid questions: Will it follow HIPAA? Can we trust it to make clinical inferences? The answer is yes, but only with oversight. The best AI tools are transparent, explainable and built with guardrails. Vendors should offer encryption, role-based access control and Systems and Organization Controls 2 (SOC 2) compliance. And just as important: Staff need training not just on how to use the tools, but on how to challenge and verify their decisions. Building off the need for your staff to challenge AI decisions, AI isn't here to replace people; it's here to take the weight off their shoulders. It's the assistant that never sleeps, never gets overwhelmed and doesn't forget payer rules. In the context of healthcare, I see it as a force multiplier enhancing the role of pharmacists, providers and care coordinators. When we introduced AI at a multisite provider group, the most surprising feedback wasn't just about time saved; it was how morale improved. Nurses and coordinators said they finally felt like they could focus on patients again. The future of prior authorizations won't be about eliminating them; it will be about making them invisible. The AI systems will know what's needed before we do. They'll draft documentation, catch gaps and smooth the back-and-forth. But it only happens if we adopt early and thoughtfully. Prior authorizations have been a source of friction for too long. AI gives us the power to fix the "broken windows"—not with duct tape but with real structural change. The next step is ours to take. Forbes Business Council is the foremost growth and networking organization for business owners and leaders. Do I qualify?
