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: dsfauth@gmail.com• GitHub: http://github.com/davidfauth

Not talking about this….

Or this….

But we want to talk about this:

Ryan Weald – isurfsoftware.com

And this:

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 DataNodesOrganizationsSpecialtiesProvidersLocationsCountiesZipCensus

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

Provider refers

Specialty

Specializes_in

DocGraph Data

Provider refers

Specialty

Specializes_in

Parent Org

Parent_Of

Location

Location_In

DocGraph Data

Provider refers

Specialty

Specializes_in

Parent Org

Parent_Of

Location

Location_In

DocGraph Data

Provider refers

Specialty

Specializes_in

Parent Org

Parent_Of

Location

Location_For

CountiesZip

Located_In

Income

Income_In

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

Provider refers

Specialty

Specializes_in

Parent Org

Parent_Of

Location

Location_For

CountiesZip

Located_In

Income

Income_In

Drugs

prescribes

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/

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