Big Data and Health. Google Maps: Satellite View. Four Characteristics of Big Data. Personalized Medicine 2/5/2016. Health Big Data Ecosystem

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1 Big Data and Health Google Maps: Satellite View CLS&I Study Group January 28, 2016 Gary Marchant 3 Years Ago Today Four Characteristics of Big Data Cost efficiently processing the growing Volume x ZB Responding to the increasing Velocity 30 Billion RFID sensors and counting Collectively Analyzing the broadening Variety 80% of the worlds data is unstructured Establishing the Veracity of big data sources 1 in 3 business leaders don t trust the information they use to make decisions Source: IBM Health Big Data Ecosystem Personalized Medicine G. M. Weber et al. JAMA. 2014;311(24):

2 Source: Stephens et al., PLOS Biology (2015) Precision Medicine Initiative 2

3 The analysis reveals that the outbreak in Sierra Leone was sparked by at least two distinct viruses, introduced from Guinea at about the same time. It is unclear whether the herbalist was infected with both variants, or whether perhaps another funeral attendee was independently infected. One Ebola virus lineage disappears from patient samples taken later in the outbreak, while a third lineage appears. That lineage tied to a nurse who was traveling to reach a hospital but died along the way seems to have originated when one of the lineages present at the funeral gained a new mutation. This third lineage was spread, Garry says, via a truck driver who transported the nurse, as well as others who cared for her in the town where she died. Killer Bug is Traced at NIH Hospital WSJ 8/22/12 Genetic sequencing used to track deadly strain of antibiotic resistant Klebsiella pneumonia strain through 18 patients at NIH hospital ( 6 of whom died) Mutation profiling permitted identification of who passed the bug to whom, where, and how (e.g., spray from sink) This level of certainty is going to change the concept of hospitals responsibility. 1 in 20 hospitalized patients picks up infection, kills 100,000 people per year 3

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5 Sewage Monitoring Since its launch, FoodBorne Chicago classified more than 3,700 tweets related to food poisoning in Chicago, which led to 722 food poisoning reports submitted to CDPH through FoodBorneChicago.org. Based on these reports, 526 inspections were conducted which led to critical or serious violations being found at 112 food establishments, violations which would not have been identified as quickly without the use of data from Twitter. 5

6 Louisville: Asthma Tracker More than 500 Louisville asthma sufferers are being equipped with special, high tech inhalers ones that collect data about where and under what circumstances the inhaler is used. By GPS plotting that information along with data from other sources about air quality neighborhood risk factors, school conditions, etc. we hope to get new insight into what prompts an asthma attack. Greg Fischer, Mayor Discussion Questions 1. What are the most promising applications of big data in the health care context? How will such big data applications improve health care quality and/or costs? 2. How big a problem will false positives be for big data in health care? Will the incidentalomas overwhelm our health care system and increase health care costs? 3. Much of the health big data will be predictive of future disease and problems rather than about an existing health problem. How much do you want to know about your risks and predispositions to future disease? 4. How will people respond to more predictive and diagnostic data about their health? Indifference? Feeling helpless? Anxiety? Take helpful actions in response to data? 5. Who should have access to health big data, and how would they obtain access? Given that the power of the data is proportional to the size of the data base, should there be a national health data base? What other policies can or should encourage sharing and access to data by researchers, providers, and policymakers? 6. What are the privacy, liability and regulatory implications of the big data era in health care? 6