5 ways to prevent revenue leakage before claims are submitted
November 18, 2025 | Josh Amrhein
Hospitals have long fought revenue leakage after the damage is already done, when a claim is denied, delayed or written off. But as payer scrutiny grows and operating margins tighten, more leaders are realizing the real opportunity lies before a claim ever leaves the building.
A recent Becker’s Hospital Review article, “AI and Medical Necessity: The Next Frontier in Revenue Protection,” captured the shift well. It noted that even properly authorized services are being denied for lacking medical necessity, a gap that often surfaces weeks or months after care is delivered. These denials are harder to predict, tougher to appeal and more expensive to resolve than traditional coding or billing errors. In other words, they represent one of the most preventable sources of hidden revenue loss.
5 ways to prevent revenue leakage before claims are submitted
- Shift from denials management to denials prevention
Focus on identifying and resolving issues before claims are submitted. Prevention reduces missed reimbursements, accelerates cash flow and minimizes administrative burden.
- Use predictive analytics to flag risk before billing
Machine learning tools can assess claims pre-submission, predict reimbursement likelihood and alert teams to documentation gaps or medical necessity risks.
- Break down silos across revenue cycle functions
Form cross-functional teams that include clinical documentation integrity (CDI), coding, utilization review and finance to address root causes collaboratively and improve transparency.
- Target front-end denials for maximum impact
Nearly 40% of denials originate during scheduling, registration or authorization. Improving these workflows can prevent denials before they reach billing.
- Quantify ROI to build support for change
A sample ROI analysis showed a 1.67% reduction in denial rates, 753 denials avoided, and $36 million in denied dollars recovered, demonstrating the financial value of proactive strategies.
The cost of downstream fixes
When revenue leakage is caught late, hospitals spend millions in rework. An AIHCP article published this summer estimated that health systems lose a significant portion of their rightful revenue daily due to operational inefficiency, billing errors, and administrative oversight. Most leakage isn’t caused by a single bad decision, but by small, systemic misses that accumulate across documentation, coding, and billing workflows.
For executives, the financial impact is clear: Every hour spent on appeals, rebills, or clinical validation audits pulls resources from higher-value work. Worse, it delays reimbursement and complicates cash flow forecasting. In tight margin environments, those leaks can quietly drain millions a year.
Where leakage begins
Revenue leakage starts in the handoff between clinical documentation, coding and revenue cycle operations. A provider’s note that’s incomplete or ambiguous. A diagnosis that doesn’t align with payer medical necessity criteria. A coding edit that gets bypassed to meet a billing deadline.
Each of these issues can trigger denials or underpayments downstream. The problem isn’t effort or intent, but that traditional workflows rely on humans catching complex documentation gaps in real time, typically under pressure. With today’s scale and payer complexity, this workflow is unrealistic
AI-enabled guardrails upstream
What both the Becker’s and AIHCP articles describe is a new model for protecting revenue, embedding predictive, AI-enabled guardrails early in the process.
Machine learning tools can now scan documentation, coding patterns and payer rules to flag at-risk claims before submission. They can alert clinical documentation integrity (CDI) and coding teams when a record lacks sufficient justification for medical necessity or when documentation doesn’t match the coded diagnosis. Some systems even integrate directly with the electronic health record (EHR), prompting clinicians at the point of documentation to add clarity before the case moves forward.
This “upstream” approach turns revenue protection from a reactive function into a proactive one. Instead of identifying leakage after it’s occurred, hospitals can prevent it by improving first pass claim accuracy and reducing rework.
What executives should be asking
For leaders focused on margin protection and operational efficiency, the right questions aren’t just about denial rates but where in the process risk begins.
- How many claims are corrected or reworked before billing?
- What percentage of denials cite medical necessity or incomplete documentation?
- Are predictive analytics or real-time feedback loops built into clinical workflows?
Organizations that can answer those questions are already ahead. They’re not just fixing leaks but redesigning the systems to stop leaks from forming.
The strategic shift ahead
AI won’t eliminate human expertise, but it changes how it’s applied. Instead of spending hours researching denials, revenue cycle and CDI specialists can focus on higher-value activities like validating complex cases, refining documentation standards and training clinicians.
As the Becker’s article points out, the next frontier in revenue protection isn’t more manpower; it’s smarter alignment between clinical and financial logic. And automation and analytics together can make that alignment scalable.
Hospitals that embrace this shift are finding that the benefits go beyond fewer denials. They see faster cash flow, better staff morale and stronger payer relationships. All by moving their revenue integrity strategy upstream.
Bottom line
Revenue leakage will never disappear entirely, but it can be contained. The key is timing: The earlier you catch risk, the less it costs to fix. With AI-powered insights now capable of surfacing documentation and coding gaps in real time, hospitals have the tools to close the cracks before they widen.
For executives navigating today’s financial pressures, it’s not just operational improvement but revenue protection.
Josh Amrhein is a business manager for revenue integrity at Solventum.