Revenue Cycle Process Automation

U.S. dental support organizations (DSOs) are turning to modern revenue cycle management (RCM) technology to tackle costly insurance claim denials and streamline operations. Cloud-based RCM platforms can unify insurance, billing, and patient data across all practices, providing centralized dashboards and real-time analytics. By eliminating redundant systems and automating workflows end-to-end, DSOs gain clearer financial visibility and tighter control over claims. For example, one DSO reports that real-time eligibility verification built into scheduling reduces claim denials and administrative back and forth by catching coverage issues before treatment. These integrated systems ensure patient and payer data flow seamlessly from intake through payment, closing gaps that cause revenue leakage. Automation and AI also play a key role in scrubbing claims for errors before submission. AI-enabled coding tools can interpret clinical notes and automatically assign the correct procedure codes, staying current with the latest coding rules. When errors are caught early, first-pass claim approval rates soar. In fact, industry reports show that intelligent claims engines improve first-pass claim approval rates by validating data and codes against payer rules. This translates into fewer rejections and resubmissions, so billing teams spend less time on appeals. Similarly, automated claims scrubbing has been shown to cut manual claim-cleanup time by over 90%, yielding faster reimbursements and improved cash flow for practices. By reducing human error in coding and documentation, AI tools both reduce the number of denied claims and give staff more time to focus on complex cases. Verifying insurance coverage up front is another critical lever for denial prevention. Modern RCM suites often include real-time eligibility checks that automatically pull patient benefits and deductibles at scheduling. This means patients and staff know expected coverage before work is done. For DSOs, this upfront check is proving powerful: one study found that automating eligibility verification led to an 11x increase in checks and about a 20% drop in denials due to eligibility errors. In practice, real-time verification prevents surprise denials and billing surprises. Patients see transparent estimates, and practices avoid wasted claims submissions. Together with AI-fueled claims validation, real-time eligibility ensures that only clean, complete claims go out the door. Automated RCM platforms with built-in eligibility checks and AI-assisted coding not only slash denial rates, but also signal that the organization is committed to efficiency and growth. In practice, leading DSOs see measurably faster reimbursements, reduced revenue cycle costs, and fewer surprises on the balance sheet. 🔔 Follow me (Sina S. Amiri) for more insights on transforming dental RCM through AI and automation. #Dental #RevenueCycleManagement #ArtificialIntelligence #Tech

Time isn’t just money in RCM—it’s everything. A perfectly coded claim submitted a day late? Denied. A missed insurance check at registration? Rework. A claim lingering in AR for 90+ days? Lost revenue. Revenue Cycle Management (RCM) isn’t just about generating revenue—it’s about how fast and efficiently you move money through the system. The secret to RCM success isn’t just accuracy—it’s speed + accuracy. Here’s how to master the clock in RCM: 1. Front-End Mastery → Fix errors before they happen. - Verify eligibility in real-time to avoid costly rework. - Get prior authorizations upfront to prevent delays. 2. Precision in Coding & Charge Capture → Speed is useless without accuracy. - Batch processing accelerates claims without errors. - Continuous coding upgrades prevent costly rejections. 3. Instant Claim Submission → Every delay costs money. - Daily submission protocols prevent end-of-month bottlenecks. - Automated scrubbing eliminates errors before claims reach payers. 4. Denial Prevention Over Denial Management → Beat denials before they begin. - Real-time denial tracking prevents repeat mistakes. - Prioritize high-dollar claims to protect cash flow. 5. A/R Acceleration → Aged claims are dead weight. - Instant follow-ups ensure no claim is forgotten. - Performance analytics identify revenue leaks before they drain cash. 6. Payment Posting & Reconciliation → Stop leaving money on the table. - Daily reconciliations catch underpayments immediately. - Contract audits hold payers accountable for every dollar. RCM success isn’t just about collecting payments—it’s about controlling time. Every second saved is a dollar earned. How does your team ensure speed + accuracy in RCM? Let’s discuss!

Here’s how doing revenue recognition manually for usage-based pricing (UBP) will look like: Managing multiple contracts with different revenue recognition rules becomes complex, due to fluctuating usage, variable revenue, and a mix of payment methods. This complexity forces finance teams to rely on rough estimates, only to keep things moving. But this means business leaders don’t always have a clear, up-to-date view of their company’s financial health. Let’s break the challenge down: Consider a simple subscription service, billed at $1,200 a year, and paid monthly at $100. Recognizing $100 each month? A breeze :) Now, if they switch to UBP, the revenue fluctuates based on usage, which could be as high as $500 a month, and $10 the next. Suddenly, recognizing revenue isn’t as straightforward because revenue is recognized when and how the service is consumed, but not when it’s billed. And that’s just the start. Add in multiple contracts, each with its own recognition rules: ➡ One contract collects money upfront and records the entire amount at the beginning of the subscription. ➡ Another contract uses a percentage-of-completion method, to recognize revenue based on the proportion of service delivered at any point in time. ➡ A third contract is milestone-based, requiring certain performance criteria to be met before any revenue can be recognized. Now, one cannot manage all this in spreadsheets, as it includes: ➡ Adjusting entries monthly for variable usage. ➡ Handling deferred revenue. ➡ Juggling different recognition methods across contracts. If done manually, it can lead to errors, compliance issues, dissatisfied customers, and shaken investor confidence. Shifting from predictable revenue streams to variable or usage-based patterns requires precision and scalability. That's why automating revenue recognition eliminates errors and maintains compliance. It provides finance teams the freedom to focus on strategy over operational grunt. PS: At Zenskar, we eliminate the manual pain points out of your revenue recognition processes. Our platform automates these operations, giving you accurate financial insights in real-time. #revenue #recognition #finance #accounting #billingerrors

Having spent a lot of time digging into the RCM space recently, it's been fascinating to see how little visibility many health systems and providers have into the underlying drivers of their revenue cycle performance. A clear and accurate picture of the revenue cycle can literally mean the difference between profitability and losing millions of dollars. However, once you start to realize how many different systems are involved in the end-to-end RCM process, its understandable why getting a comprehensive picture is so hard. It's no wonder then that revenue intelligence is becoming a key priority for more and more provider orgs. 📊 ONE DASHBOARD TO RULE THEM ALL The greatest hurdle to having a well-modeled version of the full revenue cycle is data integration: pulling in claims data, clinical data and codes, and data from other billing systems. Once accomplished, it’s much easier to not only get a comprehensive view of the state of revenue and accounts receivable, but to run modeling and see where improvements can be made. For example, visibility into the revenue cycle can enable workflows like: • Understanding common sources of revenue leakage across the system—denials, audits, takebacks, concurrent denials, patient payments, etc.     • Monitoring and identifying changes in performance across service codes, practice sites, providers, and denial reasons.    • Evaluating collection strategies and patient segmentation.    • Reviewing contract performance to identify trends in underpayment or inform re-negotiations.    • Forecasting and understanding the financial health of the system. 💸 CATCHING REVENUE LEAKAGE WITH AI Going a step further, we’re seeing some vendors focus on specific tools to improve denial management and other sources of revenue leakage. This is where machine learning (ML) often comes into play. When payers change their adjudication engines, impacting claims denials, ML is effective at spotting patterns and identifying potential process changes. We’re also seeing some vendors start to use LLMs to produce action reports for specific stakeholders based on intelligence derived from the data. 💡 ➡️ 🏃♀️ STREAMLINING INSIGHT TO ACTION While we see substantial value in having the high-level view and feedback mechanism to improve aspects of the revenue cycle, we're most excited about the potential for solutions that are “self-tuning”—uncovering and acting on the insights in a single self-contained workflow. We think the future of revenue cycle management is intelligent, integrated, end-to-end systems that can reason along the longitudinal journey of a claim, ultimately enabling more efficient issue identification and resolution. --- Current vendors in our revenue intelligence category include: • MedeAnalytics • VisiQuate • adonis • Anomaly • Deloitte Revenue Intellect • Rivet Revenue Diagnostics • Etyon • RevOps Health • Sift Healthcare Rev/Track