In Utilization Management (UM), nurses often spend hours reviewing lengthy clinical records to identify the small subset of information needed for a medical necessity determination. These files—sometimes exceeding dozens or even hundreds of pages—contain physician notes, lab results, imaging reports, and discharge summaries scattered throughout, with no standardized structure or clear prioritization of relevance. Extracting the critical details requires reading line-by-line, cross-referencing across sections, and manually piecing together the patient’s clinical story.
This process is not only labor-intensive but also misaligned with the role of skilled clinicians. Instead of applying their expertise to complex medical decision-making, UM nurses are forced into the role of document synthesizers. Across thousands of cases, this leads to slower review cycles, increased administrative costs, elevated burnout risk, and unnecessary delays in care. According to the American Journal of Managed Care, prior authorization processes already contribute billions in wasted administrative time annually1 — inefficient record summarization is a major driver of that burden.2
As case volumes rise and the complexity of medical documentation grows, the challenge is accelerating. Without tools that can rapidly distill large records into clear, accurate summaries, UM operations will remain constrained by a bottleneck that limits both efficiency and clinical focus.
In addition to navigating lengthy records, UM nurses must also manually cross-check clinical details against InterQual, MCG, or CMS criteria to determine medical necessity. This process often requires flipping between multiple systems or documents—matching diagnosis codes, lab values, imaging findings, and treatment history against guideline requirements. It is a time-consuming and error-prone task that diverts focus from clinical judgment to administrative box-checking. Without automated assistance to align extracted data with the appropriate guidelines, even straightforward cases can take far longer than necessary, delaying care and increasing the risk of inconsistencies in determinations.
AI-Powered Tools That Empower Clinical Reviewers
The next generation of AI offers a powerful set of tools designed to address the core inefficiencies in Utilization Management. Rather than replacing the nurse’s clinical judgment, these technologies support it—streamlining routine tasks, improving information access, and accelerating decision-making while maintaining compliance and auditability. Some examples of how health plans can harness AI in their clinical review workflows are:
- Automatically summarize complex clinical records, distilling hundreds of pages into structured briefs that highlight only the clinically relevant information tied to medical necessity criteria.
- Contextualize clinical details within InterQual, MCG, or CMS guidelines, using large language models (LLMs) trained to understand and map patient data directly to the applicable authorization framework—eliminating the need for constant manual reference.
- Intelligently route cases based on urgency, flagging high-priority or time-sensitive cases for immediate review, while categorizing lower-risk cases accordingly to optimize nurse workload distribution.
- Enable real-time support through clinical chat assistants, which can answer reviewer questions about documentation, summarize patient history on request, or locate specific data points in the medical record—saving time and reducing cognitive load.
- Standardize case outputs across reviewers and case types, ensuring consistency in how data is presented, interpreted, and acted upon.
The impact is immediate and measurable. Nurses begin reviews with the essential information already organized, supported by tools that minimize administrative overhead and reinforce clinical accuracy. What once took hours now takes minutes. Teams can handle higher case volumes without increasing staffing—and nurses are empowered to focus on clinical determinations, not paperwork.
A Call to Action for Health Plan Leaders
The reality is clear: manual summarization of complex medical records is one of the most persistent inefficiencies in UM. It consumes valuable clinical resources, slows authorizations, and increases the risk of burnout among nurses. The cost—both operational and human—will only rise as case volumes increase and medical documentation grows in length and complexity.
Health plan leaders have a choice: continue absorbing the costs of manual summarization or adopt AI solutions that deliver ready-to-review summaries while preserving full compliance and audit integrity. The technology is ready, the ROI is clear, and the benefits extend beyond efficiency to workforce well-being and member satisfaction.
It is time to remove the bottleneck that forces nurses to act as document compilers. Let AI handle the paperwork, intake complexity, and information retrieval. Let nurses focus on what they do best—making informed clinical determinations that ensure appropriate care and efficient use of healthcare resources.
Reach out to discover how Mizzeto is helping plans modernize their UM workflows – book time with our team here!
Sources
1. Prior Authorizations and the Adverse Impact on Continuity of Care
2. Influence of Prior Authorization Requirements on Provider Clinical Decision-Making