medicaid_utils.adapted_algorithms.py_betos package

Submodules

medicaid_utils.adapted_algorithms.py_betos.betos_proc_codes module

Python module to apply Berenson-Eggers Type of Service (BETOS) categorization for claims

class medicaid_utils.adapted_algorithms.py_betos.betos_proc_codes.BetosProcCodes[source]

Bases: object

data_folder = '/home/runner/work/medicaid-utils/medicaid-utils/medicaid_utils/adapted_algorithms/py_betos/data'
filename = 'betos_proc_codes.py'
classmethod get_betos_cat(df: DataFrame, pdf_crosswalk: DataFrame, claim_type: str = 'medicaid', proc_code_prefix: str = 'PRCDR_CD') → DataFrame[source]

Get claimwise Betos codes & categories related to CPT procedure codes in claim

Parameters:

  • df (dask.DataFrame) – Claim dask dataframe

  • pdf_crosswalk (pandas.DataFrame) – CPT x Betos code crosswalk, with betos code and betos category information

  • claim_type ({'medicaid', 'medicare'}) – Medicaid or Medicare claim type

  • proc_code_prefix (str, default='PRCDR_CD') – Column name prefix for procedure code columns

Return type:

dask.DataFrame

Examples

>>> # Requires BETOS crosswalk data and claim data
>>> BetosProcCodes.get_betos_cat(df, pdf_crosswalk)
classmethod get_betos_cpt_crosswalk(year: int) → DataFrame[source]

Get CPT x Betos code crosswalk, with betos code and betos category information. The returned CPT x Betos code crosswalk dataframe has the below columns:

  • cpt_code - HCPCS codes A0010-V9999 AMA/CPT-4 codes 00100-99999

  • betos_code - BETOS codes D1A-Z2

  • betos_code_name - BETOS code description

  • betos_cat - BETOS category abbrevation, with the below 7 values:

    • EVALUATION AND MANAGEMENT - betos_eval

    • PROCEDURES - betos_proc

    • IMAGING - betos_img

    • TESTS - betos_test

    • DURABLE MEDICAL EQUIPMENT - betos_dme

    • OTHER - betos_oth

    • EXCEPTIONS/UNCLASSIFIED - betos_uncla

Parameters:

year (type) – Public use file year

Return type:

pandas.DataFrame

Examples

>>> # Requires BETOS public use crosswalk files on disk
>>> pdf = BetosProcCodes.get_betos_cpt_crosswalk(2018)
>>> 'cpt_code' in pdf.columns
True
package_folder = '/home/runner/work/medicaid-utils/medicaid-utils/medicaid_utils/adapted_algorithms/py_betos'
medicaid_utils.adapted_algorithms.py_betos.betos_proc_codes.assign_betos_cat(df: DataFrame, year: int, claim_type: str = 'medicaid', proc_code_prefix: str = 'PRCDR_CD') → DataFrame[source]

Get claimwise BETOS codes & categories related to CPT procedure codes in claim. Columns in output dataframe:

  • If concat_codes_to_list=True,

    • lst_betos_code - Comma separated BETOS codes

    • lst_betos_cat - Comma separated BETOS cat

  • Else,

    • One boolean column each for all BETOS codes & BETOS categories

Parameters:

  • df (dask.DataFrame) – Claim dask dataframe

  • year (int) – Public use file year

  • claim_type ({'medicaid', 'medicare}) – Medicaid or Medicare claim type

  • proc_code_prefix (str, default='PRCDR_CD') – Column name prefix for procedure code columns

Return type:

dask.DataFrame

Examples

>>> # Requires BETOS public use files and claim data
>>> assign_betos_cat(df, 2018)