Reasonhub Clinical Search

Clinical Code Search — ICD-10-CM · LOINC · RxNorm

Overview

SNOMED CT is the richest semantic model, but most clinical data lives in ICD-10-CM (diagnoses), LOINC (lab and clinical observations), and RxNorm (drugs). Each system has its own query model:

This skill walks the full workflow for each: detect the right system, run a semantic search to find the anchor concept, confirm it via lookup, and compose a ValueSet that you can expand or hand to a FHIR server.

Step 0 — Code System Selection

Signal Detection

Read the user's query for these signals to determine which system to target. Multiple strong signals → target multiple systems (cross-system ValueSet).

Disambiguation Prompt

When signals are absent or conflict, ask before proceeding:

"I can search for this concept in multiple clinical code systems. Which do you need?

• ICD-10-CM — diagnosis and condition codes (claims/encounters)
• LOINC — lab and clinical observation codes
• RxNorm — drug and medication codes
• All three — cross-system ValueSet

Or tell me your use case (e.g., CDS rule, eCQM, lab order set, formulary) and I'll recommend the best fit."

ICD-10-CM Workflow

When to use ICD-10-CM

• Building condition/diagnosis ValueSets for eCQMs, CDS rules, or claims analytics
• Enumerating all subtypes of a clinical category (e.g., all T2DM codes, all sepsis codes)
• Finding the canonical billing code for a condition

Step 1 — Semantic search for the category anchor

search_icd10(query="<clinical concept>", top_k=5)

Distance interpretation:

Pick the highest-level (shortest code) that covers the clinical domain. For a complete subtree, prefer a category code (e.g., E11) over a specific leaf code (e.g., E11.9).

Step 2 — Confirm with lookup

codesystem_lookup(code="E11", system="http://hl7.org/fhir/sid/icd-10-cm")

Check:

• display matches intent
• Review includes, inclusionTerm, excludes1, excludes2 notes to understand scope boundaries
• excludes1 entries are mutually exclusive — codes in that note cannot coexist with the selected category; be aware when combining

Step 3 — Build the ValueSet

{
  "resourceType": "ValueSet",
  "name": "Type2DiabetesMellitus",
  "title": "Type 2 Diabetes Mellitus (ICD-10-CM)",
  "status": "draft",
  "compose": {
    "include": [{
      "system": "http://hl7.org/fhir/sid/icd-10-cm",
      "version": "<from list_available_codesystem_versions>",
      "filter": [
        { "property": "parent", "op": "is-a", "value": "E11" }
      ]
    }]
  }
}

is-a includes the anchor code itself. Use descendent-of to exclude it.

Common ICD-10-CM Patterns

Tip — finding the right category code: ICD-10-CM hierarchy levels:

1. Chapter — e.g., E00-E89 Endocrine, nutritional and metabolic diseases
2. Block — e.g., E08-E13 Diabetes mellitus
3. Category — e.g., E11 Type 2 diabetes mellitus ← preferred anchor
4. Subcategory — e.g., E11.3 With ophthalmic complications
5. Code — e.g., E11.311 With unspecified retinopathy with macular edema

Use search_icd10 on the clinical domain name to land at the right level, then verify with codesystem_lookup.

ICD-10-CM Limitations

• No semantic attributes. ICD-10-CM has no "finding site", "causative agent", or "associated morphology" equivalents. For cross-organ queries (e.g., "all infarct disorders") use SNOMED CT via the snomed-semantic skill.
• Tabular hierarchy only. The parent/child structure mirrors the printed tabular list; it is a classification hierarchy, not a clinical ontology.
• Coarse granularity. ICD-10 categories are intentionally coarser than SNOMED — a single category can conflate conditions that SNOMED distinguishes precisely. For more granular or semantically filtered sets, crossmap to SNOMED via terminology-crossmap.

LOINC Workflow

When to use LOINC

• Building lab order sets, result observation ValueSets, or CDS rules on lab values
• Finding all LOINC codes for a given analyte across specimen types
• Identifying members of a panel (e.g., CMP, CBC)
• Mapping clinical observations to standard codes for interoperability

Step 1 — Semantic search for the anchor observation

search_loinc(query="<analyte or test name>", top_k=10)

LOINC semantic search distances tend to run higher than ICD-10:

Pick a representative observation that matches the user's intent. If the user named a specific analyte (e.g., "glucose"), look for the code with the best COMPONENT match.

Step 2 — Confirm and extract axes via lookup

codesystem_lookup(code="<LOINC_code>", system="http://loinc.org")

The response includes all six LOINC axes and metadata. Extract:

UCUM units: Read EXAMPLE_UCUM_UNITS from codesystem_lookup for the recommended unit on any quantitative LOINC code. To validate a composed expression (e.g., mg/dL, mmol/L) use: codesystem_verify_code(code="mg/dL", system="http://unitsofmeasure.org")

Always read COMPONENT from codesystem_lookup — do not guess LP codes, do not scrape loinc.org. The LP code is in the response.

Step 3 — Build the ValueSet

Pattern A — all observations for a given analyte (COMPONENT filter):

{
  "resourceType": "ValueSet",
  "name": "GlucoseObservations",
  "title": "Glucose Observations (LOINC)",
  "status": "draft",
  "compose": {
    "include": [{
      "system": "http://loinc.org",
      "version": "<from list_available_codesystem_versions>",
      "filter": [
        { "property": "COMPONENT", "op": "=", "value": "LP14635-4" },
        { "property": "STATUS",    "op": "=", "value": "ACTIVE" }
      ]
    }]
  }
}

Pattern B — all active orderable lab codes in a CLASS:

{
  "filter": [
    { "property": "CLASS",     "op": "=",  "value": "CHEM" },
    { "property": "CLASSTYPE", "op": "=",  "value": "1" },
    { "property": "STATUS",    "op": "=",  "value": "ACTIVE" },
    { "property": "ORDER_OBS", "op": "in", "value": "Order,Both" }
  ]
}

Pattern C — panel members:

{
  "filter": [
    { "property": "panel-parent", "op": "is-a", "value": "24323-8" }
  ]
}

Common LOINC Patterns

CLASS values for common domains:

⚠️ Do not expand SYSTEM LP codes. For common blood chemistry analytes, SYSTEM = LP7576-4 (Ser/Plas) matches 1000+ unrelated codes. COMPONENT is the discriminating axis.

LOINC Limitations

• No semantic relationships. LOINC does not have "causative agent" or IS-A clinical hierarchies beyond its component/panel structure. For semantic reasoning about what a lab result means clinically, crossmap to SNOMED.
• COMPONENT filter is exact. COMPONENT = LP14635-4 (Glucose) finds codes with that exact LP code. It does not subsume related analytes.
• search_loinc returns semantic proximity, not structural siblings. Use search_loinc only for discovery; always follow with a COMPONENT or CLASS filter for a precise, exhaustive set.

RxNorm Workflow

When to use RxNorm

• Building drug ValueSets for formularies, CDS alerts, eCQM numerators
• Finding all clinical drug products containing a given ingredient
• Enumerating branded drug names for a generic
• Linking to NDC codes via codesystem_lookup

Step 1 — Find the ingredient

search_rxnorm(query="<drug name>", top_k=5)

Select the result whose TTY is IN (Ingredient). If no IN result appears, the search returned product-level codes — search again using only the bare ingredient name stripped of dose, form, and strength (e.g., "metformin" not "metformin 500 MG oral tablet").

Step 2 — Confirm the ingredient

codesystem_lookup(code="<RxCUI>", system="http://www.nlm.nih.gov/research/umls/rxnorm")

Verify TTY includes IN (Ingredient) and inactive = false.

The response will list has_ingredient properties pointing outward to all drug products containing this ingredient — useful for previewing scope.

Step 3 — Build the ValueSet

Pattern A — all generic clinical drug products for an ingredient:

{
  "resourceType": "ValueSet",
  "name": "MetforminClinicalDrugs",
  "title": "Metformin Clinical Drug Products (RxNorm)",
  "status": "draft",
  "compose": {
    "include": [{
      "system": "http://www.nlm.nih.gov/research/umls/rxnorm",
      "version": "<from list_available_codesystem_versions>",
      "filter": [
        { "property": "has_ingredient",  "op": "=",   "value": "6809" },
        { "property": "TTY",             "op": "in",  "value": "SCD,SCDF,SCDG" },
        { "property": "inactive",        "op": "=",   "value": "false" }
      ]
    }]
  }
}

Pattern B — all branded products for an ingredient:

{
  "filter": [
    { "property": "has_ingredient", "op": "=",  "value": "<IN_RxCUI>" },
    { "property": "TTY",            "op": "in", "value": "SBD,SBDF,SBDG" },
    { "property": "inactive",       "op": "=",  "value": "false" }
  ]
}

Pattern C — all products (generic + branded) for a specific dose form group:

{
  "filter": [
    { "property": "has_ingredient",    "op": "=",  "value": "<IN_RxCUI>" },
    { "property": "TTY",               "op": "in", "value": "SCD,SBD,SCDF,SBDF" },
    { "property": "has_doseformgroup", "op": "=",  "value": "<DFG_RxCUI>" },
    { "property": "inactive",          "op": "=",  "value": "false" }
  ]
}

Use search_rxnorm("<dose form> dose form group") to find the RxCUI for any dose form group — do not hard-code these values.

TTY Selection Guide

RxNorm Expand Timeout Handling

RxNorm expansions can time out for popular ingredients (e.g., metformin, aspirin, lisinopril) that have hundreds of associated products. If valueset_expand returns a timeout error:

1. Immediately fall back to reasonhub-skills expand — do not retry valueset_expand with different parameters.
2. The ValueSet JSON is still the primary deliverable; expansion is informational only.
3. Narrow the ValueSet (add has_doseformgroup, restrict TTY) if the user needs a smaller set.

RxNorm Limitations

• Sparse hierarchy. RxNorm's parent is-a hierarchy via RB relationships is thin. Use has_ingredient + TTY filters rather than hierarchy traversal for drug product sets.
• No therapeutic class in FHIR filters. RxNorm does not expose ATC or NDF-RT drug class hierarchy as a filterable FHIR property. For drug-class ValueSets (e.g., "all beta-blockers"), enumerate ingredients individually and union them in a multi-include compose, or crossmap to SNOMED substance hierarchy.
• Combination drugs. A drug with two ingredients has two has_ingredient entries. A single-ingredient filter will match combination products too (e.g., metformin/sitagliptin). Add a second has_ingredient exclude or restrict TTY to limit scope.

Cross-System ValueSets

When the user's use case spans systems (e.g., an eCQM that needs both diagnosis codes and lab tests), compose a multi-system ValueSet:

{
  "resourceType": "ValueSet",
  "name": "DiabetesManagementBundle",
  "title": "Diabetes — Diagnoses (ICD-10-CM) + Glucose Tests (LOINC)",
  "status": "draft",
  "compose": {
    "include": [
      {
        "system": "http://hl7.org/fhir/sid/icd-10-cm",
        "version": "<icd10_version>",
        "filter": [{ "property": "parent", "op": "is-a", "value": "E11" }]
      },
      {
        "system": "http://loinc.org",
        "version": "<loinc_version>",
        "filter": [
          { "property": "COMPONENT", "op": "=", "value": "LP14635-4" },
          { "property": "STATUS",    "op": "=", "value": "ACTIVE" }
        ]
      }
    ]
  }
}

Each include section must specify version. Use list_available_codesystem_versions to get current versions for all systems.

Output

Every query delivers two things.

1. Code System Selection Summary

State which system was selected and why (or which options were offered if disambiguated by the user):

Selected ICD-10-CM — query mentions diagnosis codes for an eCQM. Anchor: E11 Type 2 diabetes mellitus.

2. FHIR ValueSet JSON (always deliver this)

Return a complete ValueSet resource with name, title, status, and a populated compose.include. This is the primary artifact.

3. Expansion (ask the user)

After delivering the ValueSet JSON, ask:

"Would you like me to expand this and show the matching codes? I can format the results as a markdown table or CSV."

If the user says yes, attempt valueset_expand once. On failure or timeout, immediately run reasonhub-skills expand — do not explain, do not offer alternatives, just run it.

If expansion returns fewer rows than total, label the output as partial and stop. Do not retry. See reasonhub-expand-mechanics for expand failures, CLI fallback, scripting, and debugging.

Markdown table (default):

CSV (when user asks to download or import):

code,display
E11,"Type 2 diabetes mellitus"
E11.9,"Type 2 diabetes mellitus without complications"

Worked Examples

ICD-10-CM: "All T2DM diagnosis codes for an eCQM denominator"

search_icd10("type 2 diabetes mellitus", top_k=5)
# → E11.6 (distance 0.063), E11 (distance 0.098)

codesystem_lookup("E11", "http://hl7.org/fhir/sid/icd-10-cm")
# display: "Type 2 diabetes mellitus"
# includes: "diabetes NOS", "insulin resistant diabetes"
# excludes1: type 1 (E10.-), gestational (O24.4-) — scope boundary confirmed

{
  "resourceType": "ValueSet",
  "name": "Type2DiabetesMellitusDx",
  "title": "Type 2 Diabetes Mellitus — All ICD-10-CM Codes",
  "status": "draft",
  "compose": {
    "include": [{
      "system": "http://hl7.org/fhir/sid/icd-10-cm",
      "version": "2026",
      "filter": [{ "property": "parent", "op": "is-a", "value": "E11" }]
    }]
  }
}

Result: 65 codes covering all T2DM subtypes.

LOINC: "All active orderable glucose lab tests"

search_loinc("glucose blood measurement quantitative", top_k=5)
# → 110939-6 "Glucose [Measurement] in Blood" (distance 0.200)
# → 2345-7  "Glucose, Blood" also in scope

codesystem_lookup("2345-7", "http://loinc.org")
# COMPONENT   = LP14635-4 (Glucose)
# CLASS       = CHEM
# CLASSTYPE   = 1
# ORDER_OBS   = Both
# SCALE_TYP   = LP7753-9 (Quantitative)
# EXAMPLE_UCUM_UNITS = mg/dL

{
  "resourceType": "ValueSet",
  "name": "GlucoseLabTests",
  "title": "Glucose Lab Observations — Active Orderable (LOINC)",
  "status": "draft",
  "compose": {
    "include": [{
      "system": "http://loinc.org",
      "version": "2.81",
      "filter": [
        { "property": "COMPONENT", "op": "=",  "value": "LP14635-4" },
        { "property": "STATUS",    "op": "=",  "value": "ACTIVE" },
        { "property": "ORDER_OBS", "op": "in", "value": "Order,Both" }
      ]
    }]
  }
}

RxNorm: "All generic metformin clinical drug products"

search_rxnorm("metformin ingredient", top_k=5)
# → 372803 "metformin Oral Tablet" (SCDF, distance 0.040)
# → ingredient is 6809

codesystem_lookup("6809", "http://www.nlm.nih.gov/research/umls/rxnorm")
# display: "Metformin"
# TTY includes: IN   ← confirmed ingredient
# inactive: false

{
  "resourceType": "ValueSet",
  "name": "MetforminGenericDrugs",
  "title": "Metformin Generic Clinical Drug Products (RxNorm)",
  "status": "draft",
  "compose": {
    "include": [{
      "system": "http://www.nlm.nih.gov/research/umls/rxnorm",
      "version": "10062025",
      "filter": [
        { "property": "has_ingredient", "op": "=",  "value": "6809" },
        { "property": "TTY",            "op": "in", "value": "SCD,SCDF,SCDG" },
        { "property": "inactive",       "op": "=",  "value": "false" }
      ]
    }]
  }
}

⚠️ Metformin is a high-volume ingredient. If valueset_expand times out, run reasonhub-skills expand with the ValueSet JSON above.

Cross-system: "Diabetes eCQM — diagnoses + glucose tests + metformin drugs"

{
  "resourceType": "ValueSet",
  "name": "DiabetesECQMBundle",
  "title": "Diabetes eCQM — ICD-10-CM + LOINC + RxNorm",
  "status": "draft",
  "compose": {
    "include": [
      {
        "system": "http://hl7.org/fhir/sid/icd-10-cm",
        "version": "2026",
        "filter": [{ "property": "parent", "op": "is-a", "value": "E11" }]
      },
      {
        "system": "http://loinc.org",
        "version": "2.81",
        "filter": [
          { "property": "COMPONENT", "op": "=", "value": "LP14635-4" },
          { "property": "STATUS",    "op": "=", "value": "ACTIVE" }
        ]
      },
      {
        "system": "http://www.nlm.nih.gov/research/umls/rxnorm",
        "version": "10062025",
        "filter": [
          { "property": "has_ingredient", "op": "=",  "value": "6809" },
          { "property": "TTY",            "op": "in", "value": "SCD,SCDF" },
          { "property": "inactive",       "op": "=",  "value": "false" }
        ]
      }
    ]
  }
}

When to Escalate to Other Skills