More Efficient File Structure and Data Accessibility
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eric_...@jsi.com
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Mar 7, 2014, 1:51:53 PM3/7/14
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File Structure:
The taxonomy code info and
the Other Provider Identifier info should be in separate tables that link
via the NPI#. The current structure
is very inefficient and requires lengthy duplicate logic to locate the
records with the desired profile.
Data Accessibility:
Create a query
interface on the web to limit the downloads by state and perhaps also basic
provider characteristics/taxonomies rather than downloading the entire
file.
GIS: Even better/ in addition
would be to create a shared GIS data layer (ArcGIS online, IMS server, etc.) with the records geocoded and all of the
associated attribute data available behind the records. This would allow the data to be easily
added to GIS enabled projects and extracted for a particular area. The HRSA Geospatial Data Warehouse is a
good example of using an IMS layer in this way and ArcGIS online is
increasingly becoming the norm for sharing such data.
Alan Viars
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Mar 10, 2014, 2:44:13 PM3/10/14
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I'm working on doing what you are asking here. Yes the current file structure is difficult to parse. Multiple tables needed for sure.
Alan Viars
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Mar 10, 2014, 2:44:49 PM3/10/14
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would you like to give the API a dry run? Email me for credentials and instructions.
Alan
On Friday, March 7, 2014 1:51:53 PM UTC-5, eric_...@jsi.com wrote:
Chad Kopcak
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Mar 19, 2014, 12:57:01 PM3/19/14
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Hi Alan... so is the NPPES data not in a relational format currently? I sort of figured it was, and then was just pulled into a flat file. The number of columns that the file contains is a bit daunting at first, as well as the column headers (field names) being so verbose. Thankfully I was able to develop a process to bring the file in and deal with just the columns that were applicable, and making it somewhat relational and normalized for my purposes.
Alan Viars
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Mar 25, 2014, 12:31:50 PM3/25/14
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Hi Chad:
I too have built a process for "flattening" certain data from the public file. For example one taxonomy per row instead of _1, _2, _3, etc.
If you are interested in these flattened CSV files let me know.
Alan
Alan Viars
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May 8, 2014, 3:52:15 PM5/8/14
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No question this is needed and good that Alan is working on. I think we have about 10 normalized tables to hold the data (address, phone, other ids, name, etc.)
On Friday, March 7, 2014 1:51:53 PM UTC-5, eric_...@jsi.com wrote:
Alan Viars
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Jun 2, 2014, 12:00:51 PM6/2/14
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Current NPPES system uses a relational database. The new NPPES also uses a relational database. You can see the tables in the files "models.py" in the source code. I've also built up a read-only data dissemination API using MongoDB.