Mapping HCPCS Codes with Corresponding National Drug Codes (NDC) and Drug Brand Names

Description

This pretrained model establishes connections between HCPCS codes and their corresponding National Drug Codes (NDC) along with associated drug brand names. Trained on the PDAC NDC/HCPCS Crosswalk (release pdac-2026-07-05).

Open in Colab Copy S3 URI

How to use


document_assembler = DocumentAssembler()\
    .setInputCol("text")\
    .setOutputCol("document")

doc2chunk = Doc2Chunk()\
    .setInputCols(["document"])\
    .setOutputCol("chunk")

chunkerMapper = ChunkMapperModel.pretrained("hcpcs_ndc_mapper", "en", "clinical/models")\
    .setInputCols(["chunk"])\
    .setOutputCol("mappings")\
    .setRels(["ndc_code", "brand_name"])

pipeline = Pipeline(stages=[
    document_assembler,
    doc2chunk,
    chunkerMapper
])

data = spark.createDataFrame([["Q5106"], ["J9211"], ["J7508"]]).toDF("text")
result = pipeline.fit(data).transform(data)


document_assembler = nlp.DocumentAssembler()\
    .setInputCol("text")\
    .setOutputCol("document")

doc2chunk = nlp.Doc2Chunk()\
    .setInputCols(["document"])\
    .setOutputCol("chunk")

chunkerMapper = medical.ChunkMapperModel.pretrained("hcpcs_ndc_mapper", "en", "clinical/models")\
    .setInputCols(["chunk"])\
    .setOutputCol("mappings")\
    .setRels(["ndc_code", "brand_name"])

pipeline = nlp.Pipeline(stages=[
    document_assembler,
    doc2chunk,
    chunkerMapper
])

data = spark.createDataFrame([["Q5106"], ["J9211"], ["J7508"]]).toDF("text")
result = pipeline.fit(data).transform(data)


val documentAssembler = new DocumentAssembler()
    .setInputCol("text")
    .setOutputCol("document")

val doc2chunk = new Doc2Chunk()
    .setInputCols("document")
    .setOutputCol("chunk")

val chunkerMapper = ChunkMapperModel
    .pretrained("hcpcs_ndc_mapper", "en", "clinical/models")
    .setInputCols(Array("chunk"))
    .setOutputCol("mappings")
    .setRels(Array("ndc_code", "brand_name"))

val pipeline = new Pipeline().setStages(Array(
    documentAssembler,
    doc2chunk,
    chunkerMapper
))

val data = Seq("Q5106", "J9211", "J7508").toDF("text")
val result = pipeline.fit(data).transform(data)

Results

| HCPCS Code   | NDC Code      | Brand Name                                 | All NDC Codes                                                                                                                                                                                                                                                                 | All Brand Names                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
|:-------------|:--------------|:-------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Q5106        | 00069-1305-10 | RETACRIT (PF) 2000 U/1 ML                  | 00069-1305-10:::00069-1306-10:::00069-1307-10:::00069-1308-10:::00069-1309-04:::00069-1318-10:::59353-0002-01:::59353-0002-10:::59353-0003-01:::59353-0003-10:::59353-0004-01:::59353-0004-10:::59353-0010-01:::59353-0010-10:::59353-0220-01:::59353-0220-10                 | RETACRIT (PF) 2000 U/1 ML:::RETACRIT (PF) 3000 U/1 ML:::RETACRIT (PF) 4000 U/1 ML:::RETACRIT (PF) 10000 U/1 ML:::RETACRIT (PF) 40000 U/1 ML:::RETACRIT (10X2ML;MDV,LATEX-FREE) 10000 U/1 ML:::RETACRIT (PF) 2000 U/1 ML:::RETACRIT (PF) 2000 U/1 ML:::RETACRIT (PF) 3000 U/1 ML:::RETACRIT (PF) 3000 U/1 ML:::RETACRIT (PF) 4000 U/1 ML:::RETACRIT (PF) 4000 U/1 ML:::RETACRIT (PF) 10000 U/1 ML:::RETACRIT (PF) 10000 U/1 ML:::RETACRIT  10000 U/1 ML:::RETACRIT  10000 U/1 ML                                                                                                                                                                                                                                                                                            |
| J9211        | 00013-2576-05 | IDAMYCIN PFS (SDV,PF,LATEX-FREE) 1 MG/1 ML | 00013-2576-05:::00013-2576-91:::00013-2586-10:::00013-2586-91:::00013-2596-20:::00143-9217-01:::00143-9218-01:::00143-9219-01:::00143-9306-01:::00143-9307-01:::00143-9308-01:::59762-2576-01:::59762-2586-01:::59762-2596-01:::71288-0184-05:::71288-0185-10:::71288-0186-20 | IDAMYCIN PFS (SDV,PF,LATEX-FREE) 1 MG/1 ML:::IDAMYCIN PFS (SDV,PF,CYTOSAFE VIAL,PF) 1 MG/ML:::IDAMYCIN PFS (GLASS SDV,PF,LATEX-FREE) 1 MG/1 ML:::IDAMYCIN PFS (SDV.PF,CYTOSAFE VIAL,PF) 1 MG/ML:::IDAMYCIN PFS (GLASS SDV,PF,LATEX-FREE) 1 MG/1 ML:::IDARUBICIN HYDROCHLORIDE (PF) 1 MG/1 ML:::IDARUBICIN HYDROCHLORIDE (PF) 1 MG/1 ML:::IDARUBICIN HYDROCHLORIDE (PF) 1 MG/1 ML:::IDARUBICIN HCL NOVAPLUS (SDV,PF) 1 MG/1 ML:::IDARUBICIN HCL NOVAPLUS (SDV,PF) 1 MG/1 ML:::IDARUBICIN HCL NOVAPLUS (SDV,PF) 1 MG/1 ML:::IDARUBICIN HYDROCHLORIDE (PF) 1 MG/ML:::IDARUBICIN HYDROCHLORIDE (PF) 1 MG/ML:::IDARUBICIN HYDROCHLORIDE (PF) 1 MG/ML:::IDARUBICIN HYDROCHLORIDE SDV 1 MG/1 ML:::IDARUBICIN HYDROCHLORIDE SDV 1 MG/1 ML:::IDARUBICIN HYDROCHLORIDE SDV 1 MG/1 ML |
| J7508        | 00469-0647-73 | ASTAGRAF XL 0.5 MG                         | 00469-0647-73:::00469-0677-73:::00469-0687-73:::69238-2780-03:::69238-2781-03:::69238-2782-03                                                                                                                                                                                 | ASTAGRAF XL 0.5 MG:::ASTAGRAF XL 1 MG:::ASTAGRAF XL 5 MG:::TACROLIMUS HARD GELATIN 0.5 MG:::TACROLIMUS HARD GELATIN 1 MG:::TACROLIMUS HARD GELATIN 5 MG                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    |

Model Information

Model Name: hcpcs_ndc_mapper
Compatibility: Healthcare NLP 6.4.0+
License: Licensed
Edition: Official
Input Labels: [ner_chunk]
Output Labels: [mappings]
Language: en
Size: 99.1 KB