The Five Graphs of Finance - Philip Rathle and Emil Eifrem @ GraphConnect NY 2013
GraphConnect NYC
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Transcript of GraphConnect NYC
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Graphs Opening Medical Care Information
@davefauthwww.intelliwareness.org
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About Me
• My Blog: http://www.intelliwareness.org• Find me on Twitter: @davefauth• Email me: [email protected]• GitHub: http://github.com/davidfauth
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Not talking about this….
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Or this….
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But we want to talk about this:
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Ryan Weald – isurfsoftware.com
And this:
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I’ll try not to do this…
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Or this….
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Where we are today
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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
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Examples of Bad Data
• Not enough data – More transparency without having to FOIA
• State level data is hard to get
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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
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DocGraph Dataset
• DocGraph by the numbers – Directed graph – Average total degree 52.8 – 940,492 providers (graph nodes/vertices) – 49,685,810 shared edges
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DocGraph Data
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Doctor Detail (docNPI.com)
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Doctor Detail
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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
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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
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DocGraph DataNodesOrganizationsSpecialtiesProvidersLocationsCountiesZipCensus
Relationships* Organizations -[:PARENT_OF] – Providers -[:SPECIALTY]- Specialties* Lcations-[:LOCATED_FOR]-Providers* Providers -[:REFERRED]-Providers* Counties -[:INCOME_IN]- CountiesZip* Locations – [:LOCATED_IN]-CountiesZip
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DocGraph Data
Provider refers
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DocGraph Data
Provider refers
Specialty
Specializes_in
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DocGraph Data
Provider refers
Specialty
Specializes_in
Parent Org
Parent_Of
Location
Location_In
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DocGraph Data
Provider refers
Specialty
Specializes_in
Parent Org
Parent_Of
Location
Location_In
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DocGraph Data
Provider refers
Specialty
Specializes_in
Parent Org
Parent_Of
Location
Location_For
CountiesZip
Located_In
Income
Income_In
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DocGraph RX Data
• Reinforcing Jonathan Freeman’s talk on Hadoop and Neo4J
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Time for Analysis
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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.
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Hadoop Page Rank
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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
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DocGraph RX Data
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DocGraph RX Data
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DocGraph RX Data
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DocGraphRx Data
Provider refers
Specialty
Specializes_in
Parent Org
Parent_Of
Location
Location_For
CountiesZip
Located_In
Income
Income_In
Drugs
prescribes
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DocGraph RX Data
• http://whnt.com/2013/03/27/follow-up-decatur-family-claims-prescription-drugs-from-dr-shelinder-aggarwal-killed-their-son/
• http://www.palmbeachpost.com/news/news/state-regional/doctors-booted-fom-medicaid-for-massive-oxy-doses-/nPpMf/
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DocGraph RX Data
• Back to “bad data”• http://www.albme.org/actions.html
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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
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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
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