This document discusses using data to help patients find a good doctor. It suggests looking at data on whether a doctor has financial relationships with pharmaceutical companies, how their prescribing habits compare to others, and the services and treatments they provide most often. The document presents an example of a doctor in Tennessee who earned over $1 million from seven drug companies for promotional talks and consulting. It also discusses tools that can provide data on a doctor's prescribing patterns compared to peers and payments received from drug companies. The goal is to arm patients with more useful information to make informed healthcare decisions.

1. HELP ME FIND A ‘GOOD’
DOCTOR
Charles Ornstein
@charlesornstein @ProPublica
#MedX

2. How did you pick your doctor?
@charlesornstein

3. We all want the “Top Doctor”
@charlesornstein

4. But…
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5. Can we use data to solve this?
YES!*
* With sufficient caveats + context
@charlesornstein

6. What data can tell us
• Whether our doctor has financial relationships
with pharmaceutical companies that make the
drugs we take.
• How our doctor’s prescribing habits compares
to other doctors in the same specialty and state.
• What services and treatments our doctor
performs most and how those compare.
• Who is in our doctor’s referral network.
@charlesornstein

7. Dollars for Docs
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8. Searching for a doctor
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9. What we found
Dr. Jon W. Draud, the medical director of
psychiatric and addiction medicine at two
Tennessee hospitals, earned more than $1
million for delivering promotional talks
and consulting for seven drug companies
in less than four years.
@charlesornstein

10. Personalized checklist for patients
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11. More of the checklist
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12. OK, so my doctor gets pharma $$...
Is he/she prescribing me
drugs based on that?
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13. Prescriber Checkup
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14. @charlesornstein

15. @charlesornstein

16. @charlesornstein

17. Treatment Tracker
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18. How your doctor compares
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19. What we need
•Data on all payments from drug/device
companies to doctors.
•Characteristics of each provider’s
practice (age range/gender of patients,
illnesses, dual eligible status)
@charlesornstein

20. What we need
•Opportunities for meaningful physician
comments with the data—both to
correct errors and provide context.
•Meaningful patient interaction and
questions.
•What am I missing?
@charlesornstein

21. Final thoughts
•Industry data sets are intended for
industry audiences. But why stop
there? @ProPublica makes the data
*useful* for everyone. #medx
•Consumers trying to get the best
health care for themselves and their
loved ones need better data. #medx
@charlesornstein