Big Data Analytics in Health Care

Transcription

1 Big Data Analytics in Health Care Alex J Mair Canada Health Infoway Emerging Technology Group Acadia University March 21 st, 2014

2 Infoway has the exclusive right to make copies of this document. No alterations, deletions or substitutions may be made in it without the prior written consent of the owner. No part of it may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, or any information storage and retrieval system, without the prior written consent of the owner.

3 3 Big Data in Health Care Agenda Canada Health Infoway Background Trends Definition and Characteristics Economics Opportunities and Challenges Call to Action Summary

4 4 Canada Health Infoway Created in 2001 $2.1 billion in federal funding Independent, not-for-profit corporation Accountable to 14 federal/provincial/territorial governments Mission: Fostering and accelerating the development and adoption of electronic health record information systems with compatible standards and communications technologies on a pan- Canadian basis with tangible benefits to Canadians.

5 5 Enabled by EHR Solutions Blueprint A common technical conceptual architecture Depicts shared data locally, jurisdictionally and regionally Enables cost effective & re-useable data integration Point-of-service applications can be added, are extensible & scalable

6 6 Emerging Technology Group Mission Emerging and disruptive information and communication technologies. Vision Appropriately and effectively used

7 7 Nexus of Forces

8 8 The digital world the Internet and the cloud and supercomputing and social networking is breaking medicine out of its cocoon. It s a super convergence we ve seen in other walks of life but not in the health and medical sphere. Eric Topol, MD quote from Wired Magazine Feb 2012

9 9 The Paper Era Clinical Applications

10 The e-health Era 10 Specialist Office Other Family Practice Clinic Emergency Service EHR Data and Services Pharmacy Home Care Lab Health Consumer Medical Imaging Department

11 11 Clinician must stay on top of 10,000+ diseases & syndromes 3,000+ Rx 1,100+ lab tests 80% of data is unstructured The Digital Health Era EHR Data and Services Clinical Applications Devices Social Analytics Mobile Apps Genomics

12 12 The Digital Health Era EHR Data and Services PubMed has over 22.6 million records 1 million: annual rate at which articles are indexed 13% of articles, published in NEJM in 2009, were reversals of previous findings 50% (half) of clinical guidelines become outdated in < 6 yrs Clinical Applications Devices Social Analytics Mobile Apps Genomics

13 13 The Digital Health Era EHR Data and Services Each minute of the day 2 million searches generated on Google 100,000 twitter messages 700,000 pieces of content shared on facebook Clinical Applications Devices Social Analytics Mobile Apps Genomics

14 14 The Digital Health Era EHR Data and Services Clinical Applications Devices Social Human genome 3 billion base pairs, 6 billion DNA letters 4 million variants per patient s genome Gene sequencing can: Be created in 7 days Analytics Produce 600Gb of data per run Mobile Apps Genomics

15 15 The Digital Health Era EHR Data and Services Clinical Applications Smart phones and apps Nearly four billion smartphones sold (4 years) 40,000 mobile health apps and hundreds of devices allow consumers to track indicators in real time. Consumers downloaded 24 million health apps in 2012 Each minute of the day 50,000 apps downloaded Devices Social Analytics Mobile Apps Genomics

16 16 The Digital Health Era EHR Data and Services Number of patients monitored over mobile networks will reach three million globally. Clinical Applications Devices Social Analytics Mobile Apps Genomics

17 17 BDA Defined Big data characteristics include: high volume, high velocity and variety of types of information that demand cost-effective and innovative forms of information processing Analytics is the process of examining large amounts of big data to deliver new insights that can enable decisions in real or near real time

18 18 BDA in Health Care Characteristics include four aspects Value Value Value Veracity Veracity Visibility Visualization Visualization Visualization Visibility

19 19 Collection Process Differences Big Data Exabytes, real-time Distributed Unknown, unstructured and not necessarily modeled Exploratory, dynamic and discovery based External data Traditional Data Terabytes (limited near real-time, traditionally retrospective) Centralized Modeled and stable Transactional, established and known requirements In-house Copyright 2013 Canada Health Infoway

20 20 BDA Functions Differently Big Data Analytics Experimental type of analytics Open ended "how and why" type questions Processes unstructured data to find patterns Automated, mines and flags data relevant for other use and analytics Traditional Analytics Are based on answering known questions or hypotheses Are designed to query specific "what and where Processes structured and aggregated data End user initiated Copyright 2013 Canada Health Infoway

21 21 Sources of Big Data Existing data now available for new uses Health publication and clinical reference data Clinical data Business, organizational and external data

22 22 Sources of Big Data New data available for use by health system Web and social networking-based data Streamed data Genomic data

23 23 New Analytics Concepts Make innovative uses of: Data mining Natural language processing Artificial intelligence Predictive analytics Integrate vast amounts of data from different sources Recognize patterns, correlations and anomalies Analyze, contextualize and visualize data

24 24 Trends in consumer digital health Internet is main channel for researching health information Individuals are connecting with others who may share their condition A new generation of health destinations, through social networking has emerged Smartphones with fitness, and medical devices, real-time observations deliver new possibilities for personal and patient health monitoring and analytics

25 25 Genomics is Already Here Pharmaco-genomic data for drug and dosage selection Availability of over 1500 genetic tests, and several targeted therapies Pre-symptomatic diagnosis BRCA gene mutation testing for breast cancer Personalized therapy Herceptin for breast cancer Personalized drug dosage reduced dosage for treatments for colon cancer based on gene

26 26 Economics of BDA in Health Care Note: Figure used with permission of McKinsey Global Institute

27 27 Economics of BDA in Health Care Note: Figure used with permission of McKinsey Global Institute

28 Capability 28 What are the Opportunities Identifying opportunities to tailor and optimize care Predictive models, learning models, data mining discovery, benchmarking Understanding implications resulting from changes to the underlying data or analytics Drill down, slice and dice of the data to understand root cause Standardized, static views into the data Clinical and business value 28

29 Capability 29 Types of Analytics Identifying opportunities to tailor and optimize care Predictive models, learning models, data mining discovery, benchmarking Understanding implications resulting from changes to the underlying data or analytics Drill down, slice and dice of the data to understand root cause Standardized, static views into the data Clinical and business value 29

30 Capability 30 Insights that create value Identifying opportunities to tailor and optimize care Predictive models, learning models, data mining discovery, benchmarking Understanding implications resulting from changes to the underlying data or analytics Drill down, slice and dice of the data to understand root cause Standardized, static views into the data Clinical and business value These three dimensions of analytics provide the framework for a transition to a more mature state of analytics where as information is actioned by decision makers, value increases significantly 30

31 31 Toronto Sick Kids Artemis Big Data more than 1,000 recordings per second of physiological measures such as body temperature, heart rate, respiratory rate and blood pressure Functionality or Scope hospital-acquired infections are a serious issue, for premature babies (immune systems that are both immature and inexperienced), late onset neonatal sepsis (LONS) can be deadly unless doctors and nurses act fast Analytics real-time analytics and algorithms predict when a baby is at risk of infection by detecting subtle changes in physiological measures Outcomes physicians are alerted of a life-threatening infection before child shows signs of illness, by intervening hours earlier, improving outcomes dramatically, such as shorter hospital stays and reduced costs

32 32 Global Public Health Intelligence Network Big Data - 24/7 near 'real-time', over 15,000 media sources filtered for relevancy and categorizing of information, complemented by human analysis Functionality or Scope system gathers preliminary reports on relevant unverified and verified information on disease outbreaks and other public health events by monitoring global media sources (in English, French, Arabic, Spanish, Portuguese, Russian, Farsi, Traditional Chinese and Simplified Chinese) Analytics - tracks events such as disease outbreaks, infectious diseases, contaminated food and water, bioterrorism and exposure to chemicals, natural disasters, and issues related to the safety of products, drugs and medical devices and radioactive agents Outcomes reports allow users to respond to potential health threats in a timely manner

33 33 Seton Healthcare Family Natural Language Processing Big Data 80% of healthcare data is unstructured, consisting of physician notes, registration forms, discharge summaries, echocardiograms and other medical documents Functionality or Scope 500,000 new cases of congestive health failure (CHF) are diagnosed every year and more than half of CHF patients need to be readmitted within six months after treatment Analytics mines unstructured data using natural language processing and search technologies to predict which patients are most at risk for readmission, based on risk factors such as smoking Outcomes combined with structured data, provides a more accurate picture of trends, patterns and deviations, allowing clinicians to make better treatment decisions and predict the probability of a person's readmission to the hospital

34 34 Google.org Flu Big Data - weekly, millions of users search Internet for health information online Functionality or Scope how can search data be leveraged for predicting disease outbreaks Analytics - gathers data from Google search, estimates how much flu is circulating in different countries and regions across the world, determines flu activity levels Outcomes - detects regional outbreaks of influenza weekly - gets smarter, producing higher-quality predictions, and faster, as it ingests more data

35 35 Mount Sinai Medical Center of NYC - Personalized Care (Genomics) Big Data largest set of data on human genetic variation is freely available on the Amazon Web Services (AWS) cloud and researchers only pay for the computing services that they use Functionality and Scope BioMe program - 25,000 people participating in DNA sequencing and longitudinal studies linked to data embedded in their electronic medical records Analytics identification and development of biomarkers which can predict individual disease risk, enable early detection of disease, and improve diagnostic classification to better inform individualized treatment Outcomes clinical decision support engine delivers guidelines with genetic variants of clinical significance informed by the patients geotype data and other longitudinal clinical data sourced from their electronic health record

36 36 Infoway predictions & Challenges Larger HDOs Incremental and slow sophistication Key application areas Skilled resources mathematics, statistics, machine learning, research, technical tools Privacy and security PHI protection, use, legal, policy, legislation interpretation

37 37 Call to Action Communications Collaborate Leadership Cautious Execution Identify champions Understand BDA Don t go it alone Use cases, business cases Culture, processes, staffing for BDA Combine several emerging technologies Limited scope pilots Evaluate and measure benefits

38 38 In Summary Big Data can improve patient outcomes and represents significant economic value and opportunities across healthcare Use cases exist, with practical guidance to discover value from big data: Clinical research (cancer) Real time remote patient monitoring Personalized medicine

39 Clinical Analytics 39 Traditional Data Analytics Traditional data = everything except volume and velocity Health Analytics

40 40 Big Data vs Small Traditional Data Data Analytics Analytics (SDA) (TDA) Collection and functions different Big data analytics = Traditional data analytics BDA and TDA will co-exist Continue to do traditional data analytics (TDA)

41 41 Some Additional Resources Website: ETG Resources & BDA White paper: Copyright Canada Canada Health Health Infoway Infoway

42 42 Questions?

43 43 Thank you