Mid-cycle revenue leakage is one of the most stubborn challenges in the healthcare revenue cycle. Missed utilization reviews, documentation gaps, and delays in provider engagement don’t just affect reimbursement — they impact operations, slow patient throughput, fuel denials, and strain already overburdened staff.
Using AI to protect integrity + efficiency
While many organizations attempt to patch these issues with traditional tools, those solutions often lack the speed, precision, and adaptability needed to keep pace with today’s healthcare environment. Increasingly, health systems are turning to AI designed specifically for clinical and financial workflows to close these gaps earlier in the care continuum.
That shift to AI was the focus of a recent Becker’s Healthcare discussion featuring:
- Mary Murray Moss, Executive Director of Finance, Infirmary Health
- Linda Supplee, R.N., MHA, CCM, FACHE, Chief Population Health Officer, Genesis HealthCare System
Here are 3 takeaways from the panel about using AI to improve revenue integrity, streamline processes, and reduce administrative burden.
1. Organizations must move beyond legacy tools to AI-powered solutions
Traditional, retrospective approaches to revenue integrity are reactive by nature. By the time a denial is issued or a documentation gap surfaces, the opportunity to prevent revenue loss has often passed.
However, AI designed specifically for CDI and UM changes that equation. By analyzing data in real time, these solutions can:
- Surface high-priority cases for review
- Allow staff to shore up documentation
- Refocus resources on the encounters most likely to affect financial and clinical outcomes
2. Addressing mid-cycle vulnerabilities reduces revenue leakage
Mid-cycle vulnerabilities are a top cause of lost revenue. But there are several practical strategies successful teams use to address them:
- Intervene at the documentation stage
Closing gaps before discharge reduces downstream rework and strengthens claims upfront. - Break down silos between clinical documentation integrity (CDI) and utilization management (UM)
Aligning teams creates a more holistic understanding of patient status, driving more consistent decision-making. - Prioritize adoption, not just implementation
Successful rollouts require strong change management and clear communication about how AI supports — rather than replaces — clinical staff.
3. Healthcare-specific AI yields fast returns + fewer disruptions
Purpose-built AI is exponentially more valuable and effective than bolt-on or generic tools. Healthcare-specific AI not only delivers quicker ROI but also minimizes the tradeoffs often seen with software adoption, such as increased clicks or workflow disruption.
By surfacing the right information at the right time, staff can focus on high-impact cases without additional administrative burden. The result:
- Reduced denials
- Improved throughput
- Stronger financial resilience
Preventing mid-cycle revenue leakage with AI
For both Infirmary and Genesis, the benefits of early, AI-driven intervention extend beyond revenue capture. Optimized workflows have eased staff burden, supported faster patient movement, and built greater confidence in the integrity of clinical and financial processes.
See what optimized Clinical Integrity + Revenue Capture can do for you.
