Version: 0.8.4
This repository contains a number of command-line utilities and related code libraries for parsing, creating, and validating US-based health provider data. These tools are:
Parsing Scripts
- chop_nppes_public.py - Parse the npi public data dissemination into flattened files.
- csv2pjson_public.py - Parse the npi public data dissemination into ProviderJSON files.
- csv2fhir.py - Parse the npi public data dissemination to FHIR Practitioner and Organization Resources.
- validate_pjson - Parse a Provider JSON document and output errors and warnings as JSON.
- validate_pjson_dir - Bulk validation of the output of csv2pjson-public.py.
- makepecosdocs.py - Creates affiliations from initial PECOS data sets within MongoDB.
- combine_nppes_pecos_org_fhir.py - Combines NPPES and PECOS organization data within MongoDB, based on NPI's.
- combine_nppes_pecos_pract_fhir.py - Combines NPPES and PECOS practitioner data within MongoDB, based on NPI's.
Indexing Scripts
Note: These scripts are only meant to be run after the data/files to be indexed have already been loaded into MongoDB.
-
create_provider_indexes.py - Create default MongoDB indexes on Provider JSON data to support public search on common fields.
-
create_pecos_indexes.py - Create default MongoDB indexes on PECOS data (Base, Reassignments, Addresses)
-
create_pecos_compiled_indexes.py - Create default MongoDB indexes on PECOS compiled data (after running makepecosdocs.py)
-
create_combined_indexes.py - Create default MongoDB indexes on combined PECOS and NPPES data (after running the combine* scripts)
Pulling/Loading Scripts
- pull_pecos.py - Download all or pieces of the PECOS Database in CSV format.
- loadnppes.py - Download public NPPES file, parse to JSON, and load to MongoDB in one step.
- load_pecos.py - Download public PECOS csv file(s) and NPPES data, parse, load and combine in MongoDB in one step.
- load_nppes_and_pecos.py - loadnppes.py and load_pecos.py in one step.
Utility Scripts
- json_schema_check_fhir.py - A FHIR resource specific JSON schema validator.
- json_schema_check.py - Generic JSON schema validation against a JSON file.
Please note the utilities csv2json, json2mongo, and jsondir2mongo have been
moved from pdt and placed in their own package called jdt. These tools are generic
and have utility outside health provider data.
These scripts require Python >= 3.3
In order to utilize all of the scripts that Provider Data Tools provides, you will need to have MongoDB Installed and running. See MongoDB Docs for reference on installation.
You can install the tool using pip.
To install with pip just type:
~$ sudo pip install pdt
Note: If you use sudo, the scripts will be installed at the system level and used by all users.
Add --upgrade to the above install instructions to ensure you fetch the newest version.
To make use of this script you need first fecth the "NPPES Data Dissemination" file.
To obtain the "NPPES Data Dissemination", go to http://download.cms.gov/nppes/NPI_Files.html. Get the "Full Replacement Monthly" zip file. Unzip the file with the unzip tool of your choice.
To run the utility simply call it on a command line and provide one command line argument, the csv file to parse:
~$ chop_nppes_public.py npidata_20050523-20220404.csv
The file name npidata_20050523-20220404.csv will vary depending on the date.
The script make take a few minutes to complete. When it completes you will have more files in your current directory. Everything is still indexed by NPI. These files are described below.
- _basic.csv - Contains basic demographic info.
- _addresses_flat.csv - one address per line identifier as practice or mailing.
- _identifiers_flat.csv - one identifier per line.
- _licenses_flat.csv - one license per line.
- _taxonomy_flat.csv - one taxonomy code per line and identified as primary or not.
Convert the NPPES Public Data Dissemination CSV file format to a directory of files in ProviderJSON format.
Usage:
csv2pjson_public.py [CSV_FILE] [OUTPUT_DIR]
Example:
csv2pjson_public.py public_csvfile.csv output
Output:
One file is created per line in the CSV file file inside the directoryoutput. Files are fanned out
into a directory structure so as not to create millions of files in one directory.
Convert the NPPES Public Data Dissemination CSV file format to a directory of files in ProviderJSON format.
Usage:
csv2fhir.py [CSV_FILE] [OUTPUT_DIR]
Example:
csv2fhir_public.py public_csvfile.csv output
Output:
One file is created per line in the CSV file file inside the directoryoutput. Files are fanned out
into a directory structure so as not to create millions of files in one directory.
Validate the PJSON for compliance with a create/update request. It returns errors and warnings in JSON to stdout.
Usage:
validate_pjson [ProivderJSON] [update|create]
Example:
validate_pjson 1003819723.json update
Example Output:
{
"errors": [
"authorized_official_telephone_number must be in XXX-XXX-XXXX format.",
"EIN is required for a type-2 organization provider."
],
"warnings": [
"Enumeration date is generated by CMS. The provided value will be ignored.",
"Last updated date is generated by CMS. The provided value will be ignored.",
"status is determined by CMS. The provided value will be ignored."
]
}
The script will download all or individual Public Provider Enrollment Files
from https://data.cms.gov/public-provider-enrollment in CSV format. Note that
wget is a requirement for this script.
Usage:
pull_pecos.py [DOWNLOAD ALL Y/N] [DOWNLOAD BASE Y/N] [DOWNLOAD REASSIGNMENT Y/N] [DOWNLOAD ADDRESS Y/N]
Example:
pull_pecos.py y n n n
Example Output:
Downloading Address CSV file
--2016-07-12 10:39:00-- https://data.cms.gov/api/views/je57-c47h/rows.csv?accessType=DOWNLOAD
Resolving data.cms.gov (data.cms.gov)... 216.227.229.148
Connecting to data.cms.gov (data.cms.gov)|216.227.229.148|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: unspecified [text/csv]
Saving to: ‘pecos_address.csv’
pecos_address.csv
[ <=> ] 3.14M 914KB/s
By streamlining several of the pdt utilities, the script loadnppes.py combines functionalty
for automatic setup. The script will download public data, parse to JProvider SON, and load
to MongoDB in one step. Note this script requires unzip and wget to be installed.
Usage:
loadnppes.py [PROCESS_FULL Y/N] [DOWNLOAD_FROM_PUBLIC_FILE Y/N] [DELETE FILES AFTER UPLOADED TO MONGO?]"
Example:
loadnppes.py y y
Example Output:
Downloading http://nppes.viva-it.com/NPPES_Data_Dissemination_March_2015.zip
--2015-04-13 14:14:57-- http://nppes.viva-it.com/NPPES_Data_Dissemination_March_2015.zip
Resolving nppes.viva-it.com (nppes.viva-it.com)... 68.142.118.4, 68.142.118.254
Connecting to nppes.viva-it.com (nppes.viva-it.com)|68.142.118.4|:80... connected.
HTTP request sent, awaiting response... 200 OK
Length: 514406694 (491M) [application/zip]
Saving to: `NPPES_Data_Dissemination_March_2015.zip'
0% [ ] 2,691,064 58.1K/s eta 3h 38m
.
.
.