ICD-10-CM

Column	Data Type	Description

Download CSV

Maintenance Instructions

1. Navigate to the CMS ICD 10 website
2. Go to the ICD-10 Files section, click the section for ICD-10-CM & PCS files of the current fiscal year (e.g. 2025 ICD-10 CM & PCS)
3. Within the ICD-10-CM Files section, select the hyperlink titled "Code Descriptions in Tabular Order" to download the associated ZIP file
4. Unzip the downloaded file and open "icd10cm_order_{year}"
5. Save the "icd10cm_order_{year}" as a text file
6. Load the text file into the below python script and run:

Since the text file contains fixed-length fields, the following Python script can be used to convert it into a CSV file.

import pandas as pd

#This function converts the text file into a dataframe with single field 'Text'
def text_to_dataframe(input_file):
    with open(input_file, 'r', encoding='utf-8') as file:
        lines = file.readlines()
    
    df = pd.DataFrame({'Text': lines})
    df['Text'] = df['Text'].str.strip('\n')
    
    return df


def main():
    input_filename = "your text file path"
    output_filename = "output csv file path"   
    
    df = text_to_dataframe(input_filename)
    print(df.head())

    #Slices the single column dataframe into dataframe with required columns
    df['SN'] = df['Text'].str.slice(0,6)
    df['icd_10_cm'] = df['Text'].str.slice(6,14)
    df['header_flag'] = df['Text'].str.slice(14,16)
    df['short_description'] = df['Text'].str.slice(16, 77)
    df['long_description'] = df['Text'].str.slice(77, )

    df2 = df[['icd_10_cm', 'header_flag', 'short_description',    'long_description']]
    # Remove leading/trailing whitespace from all string columns
    df2 = df2.apply(lambda x: x.str.strip() if x.dtype == "object" else x)
    
    print(df2.head())
    #save the final dataframe as a csv file
    df2.to_csv(output_filename, index=False)

if __name__ == "__main__":
    main()

Note: You might need to adjust the slicing indexes according to the length of your data field

7. Import the CSV file into any data warehouse and upload the CSV file from the data warehouse to S3 (credentials with write permissions to the S3 bucket are required)

-- example code for Snowflake
copy into s3://tuva-public-resources/terminology/icd_10_cm.csv
from [table_created_in_step_7]
file_format = (type = csv field_optionally_enclosed_by = '"')
storage_integration = [integration_with_s3_write_permissions]
OVERWRITE = TRUE;

8. Create a branch in docs. Update the last_updated column in the table above with the current date
9. Submit a pull request

The below steps are only required if the headers of the file need to be changed. The Tuva Project does not store the contents of the ICD-10-CM file in GitHub.

1. Create a branch in The Tuva Project
2. Alter the headers as needed in ICD-10-CM file
3. Submit a pull request