How to avoid Random Association Syndrome: Getting value from Big Health Data.

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My presentation at Big Data Science meetup May 25. The Big Picture for Big Health Data. Differences between big health data and others, sources of big health data and uses for it, analytical methods, algorithms/prize competitions, and opportunities for data scientists.

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  • Men whose index finger was longer than their ring finger were significantly less likely to develop prostate cancer. Researchers made the discovery after comparing the hands of 1,500 prostate cancer patients with 3,000 healthy men. The length of the fingers is fixed before birth and is thought to relate to sex hormone levels in the womb. Being exposed to less testosterone before birth results in a longer index finger and may protect against prostate cancer later in life, http://www.bbc.co.uk/news/health-11880415
  • Mobile apps might need FDA approval as a medical device (!)
  • U of Pittsburgh – billions $$$
  • What it feels like
  • Partnerships ammounced weekly – cleveland clinic, intermountain etc
  • Winner being announced june 3 at Healhapalooza
  • Winner being announced june 3 at Healhapalooza
  • Graphs not scatter plots
  • pilot, deploy, share, and validate new ways to measure diseases – not even close to knowing how to measure outcomes espec with CER or PRO
  • RFID tags on cigarettes, location on phone GPS – Don’t buy things that are bad for yo
  • How to avoid Random Association Syndrome: Getting value from Big Health Data.

    1. 1. What‟s the Big Picturefor Big Health Data?25-May-2013Tracy Allison Altman, PhDPepperSlice
    2. 2. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhD
    3. 3. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhD
    4. 4. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhD
    5. 5. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhD
    6. 6. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDprostatecancer
    7. 7. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDprostatecancertestosteronelevels inwomb
    8. 8. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDWhy study big health data?• Correlation• Association• Inference• Cause & effect• Explanation
    9. 9. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDA little philosophy.What does “cause” mean?What’s a “satisfactory”explanation?
    10. 10. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhD• Diagnosis• Treatment• Quality of care• Cost of care• Patient outcomesIt’s about outcomes.
    11. 11. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDHealth data is the same.• Rigorous scientific research• Predictive analytics• Social influences: Adherence,behavioral, marketing• Business pressure: Accountability
    12. 12. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhD• Human lives at stake• Institutional barriers, incentives• Public policy issues• Findings are closely scrutinizedHealth data is different.
    13. 13. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhD• Diagnosis precision• Treatment precision• Quality, satisfaction• Cost, operational efficiency• Patient QOL, function, lifespanIt’s not easy measuring outcomes.
    14. 14. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhD• Bird flu outbreaks• Drug-resistantbacteria• CommunicablediseasesPublic Health vs. Medicine.• Population health• Personalizedmedicine
    15. 15. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDBig data is changing Medicine.Payment models are shifting:• Away from fee-for-service• Toward accountable care: How todefine & measure success?
    16. 16. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDPopulation: Health by numbers.Accountable Care Organizations (ACOs)manage population health.• Predictive analytics to prioritize care• Analysis showing what affects outcomes• EHR and claims are crucial
    17. 17. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDWe need a Single Patient Identifier.Big data analytics are handcuffed.• Need to follow a patient’s progress• US has no single patient identifier• Difficult to identify success
    18. 18. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDIt’s all about me:Personalized medicine.• Big $ investments now• Individual profiles(genetic, behavioral,social, spatial, etc.)• Pinpoint diseases,conditions, responses,
    19. 19. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDTraditional vs. Modern.• Research question• Deterministic• Proprietary• RCTs• Structured• Clinical• Discovery• Probabilistic• Open• Algorithms• Unstructured• Real-world
    20. 20. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDSources of health data: Big & small.• Genetic info• Insurance claims, EHR, clinical notes• Real-time monitoring (ICU)• Patient-reported outcomes• Peer-reviewed research, gray literature• Order sets, knowledge assets
    21. 21. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDAnalytical methods for health data.• De-identifying records & claims• Aggregating massive data sets• Developing statistics, algorithms• Applying machine learning, semantics• Ingesting ontologies
    22. 22. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDNot all research is created equal.• Prospective better than retrospective?• Interventional vs. observational?• Comparative effectiveness reliable?• Are core outcome sets the future?
    23. 23. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDExample: Watson.Answering questions:• Precision of diagnosis andtreatment• Insurance pre-authorizations• Ontologies, structured data, andunstructured evidence
    24. 24. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDExample: IBM is setting the pace.AI, analytics, integration.
    25. 25. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDExample: Apixio.Big data healthcare platform.• Risk management & revenue cycle• Analyzing text, scanned, coded data
    26. 26. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDExample: Treato.Mining social networks for pharma info.“See what millions ofpatients are saying.”
    27. 27. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhD• Taking trial-and-error out of RX• The ‘Wanamaker’ problem: Whatworks, and for whom?Example: GNS Healthcare.„Big Data Is BS in Healthcare.When Will It Become Real?‟
    28. 28. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhD• Develop breakthrough algorithm• Use patient data to predict and preventunnecessary hospitalizations (howmeasuring outcomes?)Example: $3M Heritage Prize.
    29. 29. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDExample: 23andMe.Precisely targeted, patient-centered.• Estimate likelihood of disease• Take preventive steps
    30. 30. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDExample: Ayasdi.
    31. 31. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDAyasdi: Topological data analysis.• Characterize patients based on geneexpression levels, biological properties,clinical data• Discover without asking researchquestions or running queries
    32. 32. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhD• Aggregates patient-reported data,shares with R&D companies• New Open Research Exchange forvalidating ways to measure healthoutcomesExample: Patients Like Me.
    33. 33. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDExample: Text messaging.• Rock Health: SF startup incubator• Several focus on adherence & education• Predicting who won’t seek care, who willbe a no-show, who needs follow-upIt appears you are at 7-11.Don’t buy things that arebad for you!
    34. 34. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDExample: CMS $1B.• US Centers for Medicare, MedicaidServices• Up to $1B for innovations that couldreduce costs and improve outcomes• Non-hospital care
    35. 35. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhD• Diagnosis• Treatment• Quality of care• Cost of care• Patient outcomesIt’s (still) all about outcomes.
    36. 36. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDSome practical advice.• Don’t get lost in data• Aggregate data that supportsprioritized improvement efforts• Measure specific outcomes• Prepare for close scrutiny
    37. 37. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDAvoid random association syndrome.• Big data means lots ofcorrelation• Random associationswith health outcomesare a distraction
    38. 38. Big Data Science Meetup 25-May-2013 Tracy Allison Altman, PhDPepperSliceHealth analytics startup.Visualize, analyze, and optimizeinformation assets (medical evidence,outcomes research, clinical/EHRanalytics, operational data).
    39. 39. Tracy Allison Altman, PhDemail: tracy@pepperslice.comtwitter: @EvidenceSoup

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