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NPI validation made easy with Pandas.

Project description

pandas-npi

NPI validation made easy with Pandas

Installation

pip install pandas-npi

Basic Usage

Update definitions

import pandas_npi

pandas_npi.update_definitions()

#------------------------------additional details------------------------------

#CMS updates the NPPES dataset about once per month. Running the above code
#on a monthly basis will ensure that you are using the most up-to-date information.

#Note that the function above has no parameters. Just run the function, and it will
#notify you when the update is complete.

Validate NPI

import pandas as pd
import pandas_npi

df = pd.read_csv("your_dataset_here.csv")

df = pandas_npi.validate(df, "npi_field_here")

#------------------------------additional details------------------------------

#The validate function takes care of cleaning/standardizing your npi. No need to
#preprocess on your end! Even special characters and letters are removed.

#Your dataset will be compared against the NPPES dataset. Four new fields will
#be added to your dataset: nppes_name, nppes_type, nppes_status, and nppes_deactivation_date.
#For full description of new fields, see below:
  • nppes_name - gives the provider or facility name for the given NPI
  • nppes_type - shows whether the NPI is a provider or facility NPI. Be aware that sole proprietors are not required to bill under a facility NPI
  • nppes_status - shows whether an NPI is active or deactivated
  • nppes_deactivation_date - If the NPI has been deactivated, lists the deactivation date. Else is NaN.
  • A final note - If an NPI does not exist now, and has never existed, nppes_name, nppes_type, and nppes_status will all be labeled "invalid".

Project details


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