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Happy & Healthy
Jeremy Murphy
Insight Data Science In consultation with Quartet Health
Happy and Healthy
Goal: identify patients at risk for major depression.
Why?: When added to a chronic illness, major depression is
associated with increased cost, higher mortality, and
increased functional impairment (Katon, 2001).
2014
~71 mil de-identified
insurance claims,
~2.5 mil patients
2014
~71 mil de-identified
insurance claims,
~2.5 mil patients
~48,000 patients with at least
one diagnostic code
indicating major depression
~2mil patients with no
mental health issues
2014
~71 mil de-identified
insurance claims,
~2.5 mil patients
~48,000 patients with at least
one diagnostic code
indicating major depression
~2mil patients with no
mental health issues
random subset
of 20,000
patients
random subset
of 20,000
patients
2014
~71 mil de-identified
insurance claims,
~2.5 mil patients
~48,000 patients with at least
one diagnostic code
indicating major depression
~2mil patients with no
mental health issues
random subset
of 20,000
patients
Logistic regression,
887 diagnostic codes
& number of total
claims
random subset
of 20,000
patients
Model Outcome
Data Insights
Deliverable
• Jane Doe’s Claim history - use model to assign
probability of major depression
More info on this project can be found in blog form at:
www.jeremywmurphy.com
A bit about me
PhD in Cognitive Neuroscience @
Postdoc Bioengineering and Neuroscience @
&
Autism and
functional
connectivity
Was this guy
listening to Bon
Jovi?
Features predictive of not being depressed
Insight jmurphy presentation

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Insight jmurphy presentation

  • 1. Happy & Healthy Jeremy Murphy Insight Data Science In consultation with Quartet Health
  • 2. Happy and Healthy Goal: identify patients at risk for major depression. Why?: When added to a chronic illness, major depression is associated with increased cost, higher mortality, and increased functional impairment (Katon, 2001).
  • 3. 2014 ~71 mil de-identified insurance claims, ~2.5 mil patients
  • 4. 2014 ~71 mil de-identified insurance claims, ~2.5 mil patients ~48,000 patients with at least one diagnostic code indicating major depression ~2mil patients with no mental health issues
  • 5. 2014 ~71 mil de-identified insurance claims, ~2.5 mil patients ~48,000 patients with at least one diagnostic code indicating major depression ~2mil patients with no mental health issues random subset of 20,000 patients random subset of 20,000 patients
  • 6. 2014 ~71 mil de-identified insurance claims, ~2.5 mil patients ~48,000 patients with at least one diagnostic code indicating major depression ~2mil patients with no mental health issues random subset of 20,000 patients Logistic regression, 887 diagnostic codes & number of total claims random subset of 20,000 patients
  • 9.
  • 10. Deliverable • Jane Doe’s Claim history - use model to assign probability of major depression
  • 11. More info on this project can be found in blog form at: www.jeremywmurphy.com
  • 12. A bit about me PhD in Cognitive Neuroscience @ Postdoc Bioengineering and Neuroscience @ & Autism and functional connectivity Was this guy listening to Bon Jovi?
  • 13. Features predictive of not being depressed