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Graphs Opening Medical Care
Information
@davefauth
www.intelliwareness.org
About Me
•
•
•
•

My Blog: http://www.intelliwareness.org
Find me on Twitter: @davefauth
Email me: dsfauth@gmail.com
GitHub: http://github.com/davidfauth

2
Not talking about this….
Or this….
But we want to talk about this:
And this:

Ryan Weald – isurfsoftware.com
I’ll try not to do this…
Or this….
Where we are today
Healthcare Data
• Recommend watching Fred Trotter speak at
GraphConnect – SF
• Moving from no data -> bad data -> better
data -> good data
• Claims Data
– Hard to accurately describe what a doctor is
doing and how they are getting paid without
claims data
– Limited and not a good data set by any standard
Examples of Bad Data
• Not enough data – More transparency
without having to FOIA
• State level data is hard to get
Better Data Sets
• DocGraph Data
– One of the “best” available
– “Best” does not mean “good”

• DocGraph Rx
– Prescribing patterns for Medicare Part D patients

• NPPES
• NUCC
DocGraph Dataset
• DocGraph by the numbers
– Directed graph
– Average total degree 52.8
– 940,492 providers (graph nodes/vertices)
– 49,685,810 shared edges
DocGraph Data
Doctor Detail (docNPI.com)
Doctor Detail
NPPES
•
•
•
•

National Plan and Provider Enumeration System
Source of NPI (National Provider Identifier)
No cost download 
Information is entered and updated by provider
Data quality is good to poor 

• CSV file with 314 columns 
NUCC
• National Uniform Claim Committee
– Healthcare Provider Taxonomy
– No cost download 

• CSV file with 5 columns and 830 rows
– Link taxonomy to NPPES reported taxonomy
DocGraph Data
Nodes
Organizations
Specialties
Providers
Locations
CountiesZip
Census

Relationships
* Organizations -[:PARENT_OF] – Providers -[:SPECIALTY]Specialties
* Lcations-[:LOCATED_FOR]-Providers
* Providers -[:REFERRED]-Providers
* Counties -[:INCOME_IN]- CountiesZip
* Locations – [:LOCATED_IN]-CountiesZip
DocGraph Data

Provider

refers
DocGraph Data
Specialty
Specializes_in
Provider

refers
DocGraph Data
Specialty
Specializes_in
Parent_Of

Provider

Parent
Org
Location_In

Location

refers
DocGraph Data
Specialty
Specializes_in
Parent_Of

Provider

Parent
Org
Location_In

Location

refers
DocGraph Data
Specialty
Specializes_in
Parent_Of

refers

Provider

Income

Parent
Org

Income_In
Location_For
Located_In
Location

Counties
Zip
DocGraph RX Data
• Reinforcing Jonathan Freeman’s talk on
Hadoop and Neo4J
Time for Analysis
Fraud Referrals
April 2013 - The owner and another
senior executive of Sacred Heart
Hospital and four physicians
affiliated with the west side facility
were arrested today for allegedly
conspiring to pay and receive illegal
kickbacks, including more than
$225,000 in cash, along with other
forms of payment, in exchange for
the referral of patients insured by
Medicare and Medicaid to the
hospital, announced U.S. Attorney
for the Northern District of Illinois
Gary S. Shapiro.
Hadoop Page Rank
DocGraph RX Data
• Originally obtained by ProPublica
• Prescribing pattern for all physicians for
Medicare Part D – 2011
• Largest public released prescribing database
• 2 sets of data - 30M edges each
• Related to business name and NDC-9 code
– NDC 9 code allows for aggregation of drugs
DocGraph RX Data
DocGraph RX Data
DocGraph RX Data
DocGraphRx Data
Drugs
Specialty
prescribes
Specializes_in
Parent_Of

refers

Provider

Income

Parent
Org

Income_In
Location_For
Located_In
Location

Counties
Zip
DocGraph RX Data
• http://whnt.com/2013/03/27/follow-updecatur-family-claims-prescription-drugsfrom-dr-shelinder-aggarwal-killed-their-son/
• http://www.palmbeachpost.com/news/news/
state-regional/doctors-booted-fom-medicaidfor-massive-oxy-doses-/nPpMf/
DocGraph RX Data
• Back to “bad data”
• http://www.albme.org/actions.html
Combine additional datasets
• Medical data
– Doctor referral data
– Medicare doctor prescription practices
– “Dollars for Doctors” – Drug company promotional
payments

• Census Data
– Income data
– Poverty data
Recommendation Engine?
• Build a graph model of the data
• Build a recommender model from the graph
model
• Graphs can be visualized, explained, discussed
and debugged collaboratively
GraphConnect NYC

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