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Better LivingThrough Data   Science        Scott                Nicholson                            @scootrous           ...
Helping peopleand businesses make better  decisions
Does big data help people make better decisions?No, insights do.BD is a realization that we can do more with data than we ...
What is data        science?        Project phasesToday        Where do you find        people who can do        it?
/Hila         “Data Scientist”         means different        things to different             people
/Hila                               “Data Scientist”                               means different                        ...
/Hila                                “Data Scientist”                                means different                      ...
“Data Scientist” means differentthings to different     people
My definition of a data scientist:Someone who uses data to solveproblems end-to-end, from asking  the right questions to m...
End-to-end data science: five stages Ask the     Choose    Extract &             Deploy,                                  ...
One of the hardest                things to find in a                data scientist  Phase 1Ask the Right Questions
Do we always            need to build a            model? Phase 2Choose anApproach
Leverage otherdisciplines and   intuition
Is building a                    model the first                   thing you should                          do?Credit: Sa...
The g(l)ory of data              science: most of              the work is here Phase 3Extract andClean Data
dddddd      In the trenches, dirty jobs, porta-potty      Vs      Luxury, rocket science, fast cars
Health Care  EHR is not designed fordata extraction
LinkedInOn the frontier,but still difficultto do agile data  Grab better/new logos
For most           problems, a wheel           has already been           invented…Phase 4           …just recognize Model...
Always use                                                 workhorse                                                 model...
LinkedInSkills universe
LinkedInSkills universe
Health CareNetworked data also common
Focus on quick solutions to identify bogeys and get feedbackThink like Eric Ries                                          ...
Deployment and                 execution of                 predictive models                 is crucial  Phase 5   Deploy...
LinkedInSubscriber churnprevention emails
Health CarePopulation health management & quality of care
LinkedIn                        Build a viewer                             appPicture of viewmaster
Well that’s great but who is going to do all of that woWho is good at this stuff?
Just as physicists moved toWall Street to be quants andthen on to online advertisingand consumer web, there will   be a si...
But hugeopportunities
One of the fundamentalproblems of our time18% of GDP! 0.01% is giantrevenue potentialData availability andrichness only in...
Take-aways
Data science isindustry-agnostic
There are manychallenges, but this is just the   beginning.
EHR data extraction and                    updates difficult                    Implementation barriersThere are many     ...
What can we do about these challenges?
Daily/hourly decisionsupport?Communicate valueof data mining topatients                        What can we doSMART, roll-y...
bit.ly/accretive-data-science-jobThank you! (we’re hiring)                        Scott                      Nicholson    ...
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Accretive Health - Quality Management in Health Care

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Accretive Health - Quality Management in Health Care

  1. 1. Better LivingThrough Data Science Scott Nicholson @scootrous snicholson@ accretivehealth.com lnkd.in/scott
  2. 2. Helping peopleand businesses make better decisions
  3. 3. Does big data help people make better decisions?No, insights do.BD is a realization that we can do more with data than we previouslythought, just as much as it is about more data being availableCompanies in 2000 who didn’t know what to do with their “small”data won’t be any better off with big/huge/fat data today.It’s about insights, and data scientists are well-suited to createthem.I’d prefer an brilliant Excel/SQL guru who asks the right questionsthan a deeply technical ‘big data’ engineer who focuses on eleganceand algorithms.
  4. 4. What is data science? Project phasesToday Where do you find people who can do it?
  5. 5. /Hila “Data Scientist” means different things to different people
  6. 6. /Hila “Data Scientist” means different things to different peopleCredit: Drew Conway
  7. 7. /Hila “Data Scientist” means different things to different peopleCredit: Hilary Mason
  8. 8. “Data Scientist” means differentthings to different people
  9. 9. My definition of a data scientist:Someone who uses data to solveproblems end-to-end, from asking the right questions to making insights actionable.
  10. 10. End-to-end data science: five stages Ask the Choose Extract & Deploy, Build a right your clean learn, modelquestions approach your data iterate
  11. 11. One of the hardest things to find in a data scientist Phase 1Ask the Right Questions
  12. 12. Do we always need to build a model? Phase 2Choose anApproach
  13. 13. Leverage otherdisciplines and intuition
  14. 14. Is building a model the first thing you should do?Credit: Sam Shah
  15. 15. The g(l)ory of data science: most of the work is here Phase 3Extract andClean Data
  16. 16. dddddd In the trenches, dirty jobs, porta-potty Vs Luxury, rocket science, fast cars
  17. 17. Health Care EHR is not designed fordata extraction
  18. 18. LinkedInOn the frontier,but still difficultto do agile data Grab better/new logos
  19. 19. For most problems, a wheel has already been invented…Phase 4 …just recognize Model the wheel!Building Example: missing charges on bill
  20. 20. Always use workhorse models firstOnline advertising: logistic regression in production at Yahoo for a long time
  21. 21. LinkedInSkills universe
  22. 22. LinkedInSkills universe
  23. 23. Health CareNetworked data also common
  24. 24. Focus on quick solutions to identify bogeys and get feedbackThink like Eric Ries Agile DataPhoto of sand trap? dd
  25. 25. Deployment and execution of predictive models is crucial Phase 5 Deploy,Learn, Iterate Iteration is key, especially in an agile analytics framework
  26. 26. LinkedInSubscriber churnprevention emails
  27. 27. Health CarePopulation health management & quality of care
  28. 28. LinkedIn Build a viewer appPicture of viewmaster
  29. 29. Well that’s great but who is going to do all of that woWho is good at this stuff?
  30. 30. Just as physicists moved toWall Street to be quants andthen on to online advertisingand consumer web, there will be a significant talentmigration into health care in the next few years.
  31. 31. But hugeopportunities
  32. 32. One of the fundamentalproblems of our time18% of GDP! 0.01% is giantrevenue potentialData availability andrichness only increasing But hugeThe right people are opportunitiesrealizing data and datascience are core to thesolution.
  33. 33. Take-aways
  34. 34. Data science isindustry-agnostic
  35. 35. There are manychallenges, but this is just the beginning.
  36. 36. EHR data extraction and updates difficult Implementation barriersThere are many Nothing scaleschallenges, but Privacy issues this is just the beginning. Data aggregation difficult Not all hospitals are Stanford, Vanderbilt, etc.
  37. 37. What can we do about these challenges?
  38. 38. Daily/hourly decisionsupport?Communicate valueof data mining topatients What can we doSMART, roll-your-ownEHRs about these challenges?
  39. 39. bit.ly/accretive-data-science-jobThank you! (we’re hiring) Scott Nicholson @scootrous snicholson@ accretivehealth.com lnkd.in/scott

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