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Medical-necessity reviews handled
RN review time redirected to clinical judgment
CMS prior authorization timelines met
A national payor was processing 2.1M utilization management cases annually across high-volume prior authorization and medical-necessity review workflows. Nurse reviewers, medical directors, appeals teams, and supervisors needed to evaluate large clinical record packets while meeting increasingly visible CMS prior authorization timelines.
The problem was clinical evidence readiness. RN reviewers were spending too much time navigating 150–200-page record packets, finding diagnoses, locating procedure details, checking ICD/CPT codes, and mapping evidence to medical-necessity criteria before they could apply clinical judgment.
The business impact was material. Manual document navigation consumed RN capacity, slowed case movement, increased review cost, and contributed to inconsistent first-pass determinations. For a payor operating at national scale, even small delays per case created major labor, backlog, and compliance exposure.
The executive trigger was the need to improve throughput before UM volume and regulatory pressure outpaced clinical staffing. Leadership needed an AI co-pilot that could pre-process medical records, surface relevant clinical findings, track urgent and standard deadlines, and let nurses focus on validation and medical-necessity decisions.
Novacis Digital deployed iMRR (intelligent Medical Record Review), a production-grade AI co-pilot for high-volume payor medical-necessity review.
The solution interpreted medical records as connected clinical evidence rather than isolated documents. It ingested multi-format records, classified document types, extracted clinical indicators, organized the case chronology, and mapped relevant findings to medical-necessity criteria for nurse reviewer validation.
The technical differentiation was governed clinical summarization with page-level traceability, criteria alignment, case-priority routing, and reviewer annotation support.
iMRR did not make medical-necessity determinations; it prepared the evidence, tracked deadlines, and preserved human review before any decision moved forward. This shifted the operating model from manual evidence hunting to validation-driven UM review with clinical accountability intact.
iMRR Clinical Review Capabilities
Utilization Management Features
Novacis Digital implemented iMRR in two stages: a 6-week pilot for priority prior authorization categories, followed by a 10–12 week enterprise expansion across the payor’s utilization management environment. The initial rollout focused on cases where record length, clinical evidence extraction, and criteria mapping consumed the most nurse-reviewer time.
Early wins included AI-prepared clinical summaries, automated code extraction, criteria-linked findings, missing-document flags, and deadline-aware case routing. This gave clinical operations leadership proof that review throughput could improve while keeping determinations, annotations, and rationale validation under nurse control.
Recovered material RN capacity by removing document-navigation work at 2.1M-case scale, converting clinical reviewer time into higher-value medical-necessity judgment.
Reduced review effort from 30–90 minutes to 16–48 minutes per case, giving teams faster movement from intake to determination.
Improved CMS SLA performance from ~71% on-time to above 97%, strengthening standard and urgent prior authorization readiness.
Cut appeal reversal rate from 7% to under 3%, showing stronger first-pass review quality and fewer downstream corrections.
Raised cases handled per RN per day from 12–18 to 22–32, reducing operating pressure in a constrained clinical staffing environment.
