How to Know If You Have a UM Workflow Problem

This is part 2 of a 3-part blog series on why outdated utilization management (UM) is costing your health system millions. Part 1 talks about the current state of denials and why they are increasing. This part explains how to identify when you have a UM problem, and part 3 will explain why you should consider AI-enhanced tools.

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Utilization management (UM) has shifted from being a quiet compliance checkpoint to becoming a central piece of hospital financial infrastructure. Every decision about patient status, level of care, or authorization has a direct impact on reimbursement. Yet, many hospitals struggle to keep pace with payers who now use advanced algorithms to scrutinize every case in milliseconds. The result: mounting denials, staff burnout, and revenue leakage that can no longer be ignored.

So, how do you know if your UM workflow has problems? The warning signs often show up long before the denial letter arrives.

Understanding the Warning Signs in UM Workflows

One of the clearest indicators of issues in your UM workflow is an influx of medical necessity denials. Payer rules often change faster than staff can keep up with, making it nearly impossible for manual reviews to catch every nuance. Another red flag is having a constant review backlog, whether initial, concurrent, or at discharge—especially after weekends or holidays.

Missed conversions are another common UM challenge. If patients are admitted under the wrong status, such as observation instead of inpatient, or vice versa, hospitals either lose revenue or face costly self-denials. Similarly, when reviewers can’t consistently monitor cases for necessary status changes, opportunities for appropriate reimbursement are lost.

Second-level reviews are also a pain point. Limited reviewer experience or poor escalation processes can result in delays, ineffective peer-to-peer discussions, and unnecessary written appeals. This not only increases the administrative burden but also drives up costs associated with denial management. Add in overlooked inpatient-only procedures, long observation stays beyond 30 hours, and suboptimal appeal outcomes, and the financial risk multiplies quickly.

In short, if your UM team is stretched thin, missing conversions, or struggling with backlogs, your UM workflow is already under strain.

These UM Workflow Issues Aren’t Any One Person’s Fault

It’s important to recognize that these problems aren’t the result of poor staff performance. The system is stacked against hospitals. Payers have invested billions in AI and automation to comb through documentation and rapidly deny claims. By contrast, most hospital UM departments haven’t updated their tools in years. They are forced to toggle between EHRs, spreadsheets, and payer portals, patching together fragmented workflows that can’t possibly keep up.

Increasing staff doesn’t solve the problem either. Even if budgets allowed unlimited hiring, there simply aren’t enough qualified UM nurses to meet demand. National RN shortages are projected to climb into the hundreds of thousands in the coming years, and UM roles require specialized expertise that takes months to recruit and train.

Every decision a UM nurse makes—“inpatient or observation,” “extend or discharge”, “appeal or write off”—can shift $5,000 to $6,000 per encounter. That margin exposure is too large to leave unsupported.

The Answer? Supporting UM Workflows with AI-Enhanced Solutions

The only sustainable way forward is to treat utilization management as core financial infrastructure, supported by technology that can scale alongside payer systems. That means moving beyond manual reviews to real-time decision support, automated prioritization of high-risk cases, and tools that surface payer-specific requirements before they become denials.

Want more details on what to look for to know if your UM workflows are under strain?

If you’re ready to upgrade your UM workflows…