Lab review

Reviews a new set of lab results against the patient's full record: trends against prior results, standard **and** functional ranges side by side, medication/supplement interference checks, systems-based pattern analysis, and a prioritized summary with red flags first. The default skill to run when any new bloodwork arrives.

MIT · v1.0.1 · by James Marin, RD, RN

Install, Comprehensive Lab Review
  1. 01Open the skill in Ena. It lands in Settings, then Skills, ready to use.
  2. 02Upload the lab PDF to the patient's documents if it is not already there.
  3. 03Type / in any patient chat and pick the skill.
Runs under a BAA

The skill pulls labs, history and medications from the patient record itself. Nothing is pasted anywhere.

Use in Ena

Using a different AI tool? A portable version with install notes lives in the GitHub repo.

For licensed healthcare professionals. Skills are decision support for clinician review, not medical advice.Read the full disclaimer

The full procedure the skill follows in Ena, as published in the open source repo.

Read the full procedure4 steps

Decision support for licensed healthcare professionals. Analysis only — the practitioner reviews, verifies, and decides.

Gather context (before interpreting anything)

  1. Call get_patient_snapshot. Use: labResults[] (testName, value, unit, referenceRange, status), medicalHistory (conditions, medications, supplements, allergies), dietAndLifestyle, vitalSigns, recentEncounters.
  2. Call get_patient_documents for structured labFindings[] from lab reports, and search_patient_documents for the raw report text — collection conditions, methodology, and interpretive commentary that extraction misses.
  3. Date every result by its specimen date (eventDate), not the report date. Identify the newest result set — that is what this review covers; everything older is trend material.
  4. Skip anything marked contradicted. If a truncation notice says history was cut off, write "history shown may be incomplete" — never "no history".
  5. If no recent labs exist, say so and stop — do not review stale results as if new.

Interpretation procedure

  1. Inventory. List every new result with its specimen date; identify the panels present and what's missing that the clinical question would normally require.
  2. Verify before interpreting. Use values exactly as recorded; if a value is implausible or units are ambiguous, flag it as a data-quality query rather than interpreting it.
  3. Trend. For each marker with priors, state direction and rate. Only call a change meaningful if it plausibly exceeds combined biological + analytical variation (TSH 2.1→2.4 is noise; ferritin 90→30 is signal).
  4. Dual-range flagging. Honor the recorded status (normal/high/low/critical) for the lab's interval, then add a functional lens, clearly labeled. Commonly used functional targets (practice conventions, not validated cutoffs): fasting glucose 75–90 mg/dL; HbA1c <5.4% (ADA prediabetes threshold is 5.7%); fasting insulin <7 µIU/mL (HOMA-IR <1.5); TSH ~1.0–2.5 µIU/mL; ferritin ~50–150 ng/mL; 25-OH vitamin D 50–80 ng/mL (guideline sufficiency is ≥30); hsCRP <1.0 mg/L (AHA low-risk tier); homocysteine <9 µmol/L; ALT <~26 U/L (M) / <~22 U/L (F); GGT <~25 U/L; triglyceride:HDL <2 (ideally <1.5); B12 >500 pg/mL with normal MMA. Where a guideline threshold and a functional target differ, state both. If the practice has its own reference ranges encoded, prefer those and say so.
  5. Adjust for who the patient is — use demographics (age, sex, dateOfBirth) and medicalHistory before flagging anything, and say in the output which adjustments applied:
    • Sex and menstrual status: ferritin and hemoglobin run lower in menstruating females; the same low-normal ferritin in an adult male or post-menopausal female is more suspicious and, with anemia, triggers GI evaluation. Lipids typically shift upward across the menopause transition — interpret a first post-menopausal panel against that, not as sudden pathology.
    • Age: TSH rises physiologically with age (tolerate higher targets in older adults); eGFR declines with age — grade CKD by guideline, but don't over-call mild age-consistent decline; be more conservative with borderline findings in elderly polypharmacy.
    • Pregnancy: trimester-specific ranges apply to thyroid and many analytes; plasma-volume expansion dilutes hemoglobin and ferritin — defer to obstetric reference sets and say so.
    • Athletes / recent hard training (check dietAndLifestyle): transient ALT/AST/CK elevations, higher plasma volume (pseudo-anemia) — recommend re-draw after 48–72 h rest before interpreting muscle/liver markers.
    • Body composition: creatinine/eGFR against muscle mass (suggest cystatin C when discordant); very low muscle mass masks renal decline.
  6. Group by system; read patterns, not single values.
    • Glycemic/metabolic: glucose + insulin + HbA1c together (normal glucose with rising insulin = early insulin resistance; HbA1c unreliable with anemia/hemoglobinopathy — cross-check fasting glucose).
    • Lipids: prefer ApoB (or non-HDL-C) over LDL-C; TG:HDL as insulin-resistance proxy; note if Lp(a) has never been measured.
    • Thyroid: TSH alone is insufficient — note if FT4/FT3/antibodies are missing.
    • Inflammation: hsCRP, ESR, ferritin (acute-phase — high ferritin with high CRP is not an iron result), fibrinogen.
    • Hematology: CBC as patterns — microcytosis + low ferritin (iron deficiency) vs macrocytosis (B12/folate, alcohol, hypothyroid); RDW rises early; interpret with iron studies.
    • Liver/kidney: isolated mild ALT rise in metabolic context suggests hepatic fat; GGT as oxidative-stress/alcohol marker; creatinine/eGFR against muscle mass; suggest cystatin C when discordant.
    • Micronutrients: B12 with MMA/homocysteine rather than serum B12 alone; RBC magnesium over serum; zinc:copper balance.
  7. Interference check against the actual med/supplement list. Biotin distorts many immunoassays (TSH, T4 — hold 48–72 h); metformin lowers B12; PPIs lower B12/magnesium; OCPs/HRT raise SHBG and binding proteins; levothyroxine timing affects FT4; recent illness elevates ferritin/CRP; intense exercise elevates ALT/AST/CK; non-fasting draws invalidate glucose/insulin/TG.
  8. Correlate with the chart. Tie each significant finding to documented conditions, symptoms, and encounters. Explicitly note discordance, and note provenance when a correlation rests on transcription- or document-sourced data.
  9. Prioritize: (a) urgent/safety, (b) primary drivers, (c) borderline/watch, (d) testing gaps worth considering.

Red flags — escalate regardless of functional interpretation

Not exhaustive. Any result with recorded status critical; hemoglobin <10 g/dL or rapid unexplained drop; new iron-deficiency anemia in an adult male or post-menopausal female (GI evaluation); platelets <100 or neutropenia; potassium/sodium/calcium outside safe bounds; eGFR newly <45 or rapidly declining; transaminases >3× ULN or bilirubin rise with enzyme elevation; suppressed TSH with elevated FT4/FT3; glucose >250 mg/dL or HbA1c ≥9%; unexplained ferritin >1000; monoclonal protein or unexplained cytopenias. Put these first in the output and recommend conventional workup or urgent referral for the practitioner's consideration.

Output format

  1. Snapshot — one short paragraph: overall picture and the single most important finding.
  2. Findings table — Marker | Value | Lab range | Functional lens | Flag | Trend (with specimen dates).
  3. Pattern analysis by system — prose, patterns over single values.
  4. Correlations with history — what fits, what doesn't, sourced from the chart.
  5. Red flags — or an explicit "none identified against the checked list".
  6. Considerations for the practitioner — possible further testing, monitoring intervals, referral considerations. Options, never directives.
  7. Patient-friendly summary — only if asked.

If the practitioner wants it saved, save with create_note (a lab review is not a clinical note or care plan).

End with: "Decision support only — for review by the treating clinician."

Conventional flagging always uses the performing lab's reference interval. Guideline-tier anchors used: ADA *Standards of Care* (glycemic thresholds), AHA/ACC and EAS lipid guidance (ApoB/non-HDL-C preference, Lp(a) once-in-a-lifetime measurement, hsCRP risk tiers), KDIGO (CKD grading), Endocrine Society (vitamin D sufficiency ≥30 ng/mL). Functional targets (glucose 75–90, insulin <7, ferritin ~50–150, homocysteine <9, ALT/GGT optima, vitamin D 50–80) are practice conventions as taught in IFM-style training and codified in blood-chemistry analysis references (e.g. Weatherby & Ferguson; Optimal DX), labeled as such in the body, never presented as validated cutoffs. Interference facts (biotin, FDA safety communication; metformin–B12; PPI–B12/Mg) are established pharmacology.

  • 1.0.1Added patient-context adjustment step (sex, menopausal status, age, pregnancy, athletes) and provenance labeling of thresholds.
  • 1.0.0Initial version.

PlatformHIPAA statusWhat you may use
EnaBAA signedHIPAA compliant. BAA available (privacy@meelio.ai).Real patient data. The skill runs against the chart.
Claude (Free / Pro / Team)No BAANo BAA. Not HIPAA compliant.De-identified data only. Never paste PHI.
Claude Enterprise / APIBAA possibleBAA possible via Anthropic sales.PHI only if your organization has an executed BAA.
ChatGPT (Free / Plus / Team)No BAANo BAA. Not HIPAA compliant.De-identified data only. Never paste PHI.
ChatGPT Enterprise / OpenAI APIBAA possibleBAA possible via OpenAI sales.PHI only if your organization has an executed BAA.

De-identification means removing all 18 HIPAA identifiers, not just the name. Read the full disclaimer.

It reviews new laboratory results against the patient history: builds trends from prior results, flags values against standard and functional ranges side by side, checks medications and supplements for interference, groups findings by body system, and puts red flags first in a prioritized clinician-facing summary.

In Ena the same skill pulls the labs, history and medications itself. Nothing pasted, nothing de-identified, HIPAA compliant.

  • HIPAA compliant
  • GDPR compliant
  • PIPEDA compliant