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![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](https://image.slidesharecdn.com/graphconnectnyc-131106161447-phpapp02/85/GraphConnect-NYC-19-320.jpg)
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GraphConnect NYC
- 1. Graphs Opening MedicalCare Information @davefauth www.intelliwareness.org
- 2. About Me • • • • My Blog:http://www.intelliwareness.org Find me on Twitter: @davefauth Email me: dsfauth@gmail.com GitHub: http://github.com/davidfauth 2
- 3. Not talking aboutthis….
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- 5. But we wantto talk about this:
- 6. And this: Ryan Weald– isurfsoftware.com
- 7. I’ll try notto do this…
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- 9. Where we aretoday
- 10. Healthcare Data • Recommendwatching 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
- 11. Examples of BadData • Not enough data – More transparency without having to FOIA • State level data is hard to get
- 12. 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
- 13. DocGraph Dataset • DocGraphby the numbers – Directed graph – Average total degree 52.8 – 940,492 providers (graph nodes/vertices) – 49,685,810 shared edges
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- 17. NPPES • • • • National Plan andProvider 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
- 18. NUCC • National UniformClaim Committee – Healthcare Provider Taxonomy – No cost download • CSV file with 5 columns and 830 rows – Link taxonomy to NPPES reported taxonomy
- 19. 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
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- 26. DocGraph RX Data •Reinforcing Jonathan Freeman’s talk on Hadoop and Neo4J
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- 30. 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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- 32. 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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- 38. 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/
- 39. DocGraph RX Data •Back to “bad data” • http://www.albme.org/actions.html
- 41. 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
- 42. Recommendation Engine? • Builda graph model of the data • Build a recommender model from the graph model • Graphs can be visualized, explained, discussed and debugged collaboratively