mapper-npi

Overview

The npi_mapper.py python script converts the NPPES NPI Registry located here. It is a free directory of all active National Provider Identifier (NPI) records provided by US government.

Loading this data into Senzing requires additional features and configurations. These are contained in the npi_config_updates.g2c file.

Usage:

python npi_mapper.py --help
usage: npi_mapper.py [-h] -i SOURCEDIR -f FILEPERIOD -o OUTPUTFILEPATH [-l LOGFILENAME]

optional arguments:
  -h, --help            show this help message and exit
  -i SOURCEDIR, --sourceDir SOURCEDIR
                        directory in which the source files are located
  -f FILEPERIOD, --filePeriod FILEPERIOD
                        the period portion of the NPPES file naming convention such as "20050523-20201108"
  -o OUTPUTFILEPATH, --outFileDir OUTPUTFILEPATH
                        the file or directory to write the JSON files to
  -l LOGFILENAME, --logFileName LOGFILENAME
                        optional statistics output file name

Contents

1. Prerequisites
2. Installation
3. Configuring Senzing
4. Running the mapper
5. Loading into Senzing
6. Mapping other data sources

Prerequisites

• python 3.6 or higher
• Senzing API version 2.1 or higher
• pandas (pip3 install pandas)

Installation

Place the following files on a directory of your choice ...

• npi_mapper.py
• npi_config_updates.g2c

Configuring Senzing

Note: This only needs to be performed one time! In fact you may want to add these configuration updates to a master configuration file for all your data sources.

From your Senzing project directory:

python3 G2ConfigTool.py <path-to-file>/npi_config_updates.g2c

This will step you through the process of adding the data sources, features, attributes and any other settings needed to load this watch list data into Senzing. After each command you will see a status message saying "success" or "already exists". For instance, if you run the script twice, the second time through they will all say "already exists" which is OK.

Running the mapper

Download the raw files from: https://download.cms.gov/nppes/NPI_Files.html

The full monthly download contains many files. These are the ones actually used by this mapper ...

• npidata_pfile_20050523-20201108.csv main provider file
• othername_pfile_20050523-20201108.csv additional names providers are known by
• endpoint_pfile_20050523-20201108.csv emails and websites for providers as well as their affiliated entities
• pl_pfile_20050523-20201108.csv additional locations for each provider

Note the period date range "20050523-20201108" will be based on the date you download the zip file.

Then run the mapper. Example usage:

python3 npi_mapper.py -i ./NPPES_Data_Dissemination_November_2020/ -f 20050523-20201108 -o ./output 

Because, the -o parameter only specifies a directory, the following 4 output files will be created:

• NPI_LOCATIONS_20050523-20201108.json
• NPI_OFFICIALS_20050523-20201108.json
• NPI_PROVIDERS_20050523-20201108.json
• NPI_AFFILIATIONS_20050523-20201108.json

or to create one file with all the records, specify the path and file name in the -o paramter like so ...

python3 npi_mapper.py -i ./NPPES_Data_Dissemination_November_2020/ -f 20050523-20201108 -o ./output/npi-yyyy-mm-dd.json

Finally, specifying the -l logFileName writes out the stats and examples of what gets mapped into Senzing. It can be quite useful during development and debugging of mapping issues.

Loading into Senzing

If you use the G2Loader program to load your data, from your project directory:

python3 G2Loader.py -f ./output/NPI_LOCATIONS_20050523-20201108.json
python3 G2Loader.py -f ./output/NPI_OFFICIALS_20050523-20201108.json
python3 G2Loader.py -f ./output/NPI_PROVIDERS_20050523-20201108.json
python3 G2Loader.py -f ./output/NPI_AFFILIATIONS_20050523-20201108.json

or if those are the only files in the output directory you can use a wild card like so ...

python3 G2Loader.py -f ./output/NPI*.json

This data set currently contains about 7 million providers and yields a total of 8.5 million records with the additional entities created for officials, locations and affiliations. It may take a few hours to load depending on your harware.

If you use the API directly, then you just need to perform an addRecord() for each line of each file.

Mapping other data sources

While not required, look for the following identifiers in your other data sets:

• NPI number
• Other provider licenses issued by states
• Medicare provider IDs
• Any other provider IDs