Utilization Management at Scale: Verified Extraction for Clinical Review and Appeals

Utilization management (UM) is where documentation meets deadlines.

Teams must assess:

• medical necessity,
• level of care,
• length of stay,
• and coverage alignment,

often under tight time windows and with incomplete or inconsistent documentation.

The work is less about “understanding medicine” and more about:

• extracting the right facts from the chart,
• aligning them to criteria,
• and documenting the rationale.

Citation-backed extraction is high value here because it makes the review loop faster:

• reviewers can click a field and see the supporting line highlighted,
• ambiguity is surfaced explicitly,
• and appeals become evidence-driven records rather than scrambled rework.

Note: This post describes document workflow patterns, not medical advice.

The UM document pack

A UM case review commonly involves:

• admission notes / H&P
• progress notes
• consult notes
• operative notes (if applicable)
• labs/imaging summaries
• discharge summary (for retrospective review)
• authorization request forms
• denial letters and criteria references (for appeals)

Treat the case as a packet and extract canonical fields across it.

What to extract (decision-critical anchors)

Administrative anchors

• patient identifier (internal)
• payer/plan identifiers (internal)
• facility and provider identifiers (where documented)
• dates: admission, service start, discharge (as applicable)

Clinical anchors (as stated in the record)

• primary diagnosis / reason for admission (as text)
• procedures performed (as text; codes if present)
• severity indicators and key findings (as text)
• therapy attempts / prior treatment (when documented)
• functional status statements (where documented)
• discharge disposition (when present)

Denial/appeal anchors

• denial reason text
• deadlines (if stated)
• criteria cited (if included)
• requested documentation callouts

Citations matter because a “clinical fact” that can’t be shown is hard to defend.

Workflow: speed review by making proof the default

1) Extract fields + citations

For each extracted anchor, store:

• value (often text)
• citation (page + region + snippet pointer)
• confidence (for routing)

2) Present a reviewer-first UI

Reviewers should see:

• a structured checklist of anchors
• “present / ambiguous / not present” statuses
• one-click evidence highlights

UM doesn’t need summaries that may drift. It needs fast verification of documented facts.

3) Route by uncertainty and risk

• Auto-accept clear administrative fields (still reviewable)
• Route ambiguous clinical statements for review
• Flag conflicts across documents (e.g., differing dates or reasons)

4) Generate an appeals-ready evidence record

When a denial is appealed, your system should already have:

• cited anchors
• reviewer verification actions
• a clean trail of what was used and where it was found

That reduces appeal prep time dramatically.

Schema sketch: UM case anchors

{
  "schema": {
    "admission_date": { "type": "date" },
    "discharge_date": { "type": "date" },

    "reason_for_admission_text": { "type": "string" },
    "primary_diagnosis_text": { "type": "string" },
    "procedures_text": { "type": "string" },

    "key_clinical_findings": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "finding_type": { "type": "string", "description": "e.g., symptom_severity, imaging, labs, functional_status" },
          "finding_text": { "type": "string", "description": "Short extracted statement; must be cited" }
        }
      }
    },

    "prior_treatments_text": { "type": "string" },

    "denial_reason_text": { "type": "string" },
    "appeal_deadline_date": { "type": "date" },
    "requested_missing_info_text": { "type": "string" }
  },
  "options": { "confidence_threshold": 0.85 }
}

KPIs worth tracking

• reviewer time-to-verify key anchors
• % cases flagged “incomplete packet” before submission
• denial rework time (hours saved per case)
• appeal preparation time
• exception rate by document type (where ambiguity concentrates)