METADATA 0007 CASE STUDIES IN BIG BIODATA. The Innovators: CASE STUDIES IN BIG BIODATA

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1 METADATA 0007 CASE STUDIES IN BIG BIODATA The Innovators: CASE STUDIES IN BIG BIODATA AUTHOR KAREEM AYOUB, EMANUEL BROWN CM0007.SA.2014.BBD005

2 INTRODUCTION. Throughout the Big BioData white paper series, there is an undercurrent of optimism underlying the challenges and complexities of refactoring healthcare in the 21st century. As reviewed in our first white paper, value creation in big data applications is surrounded by streams of hype. 1 Recent articles express distrust in large datasets, disbelief in the power of analytics engines, and quandary over privacy and ethical issues. 2 Success in Big BioData (and big data, more broadly) does not have to befall a lucky few. Rather, by following structured guidelines that allow for creative innovation, value creation in Big BioData is not only possible but becomes a process flow. Building from this process, it is possible to drive widespread adherence to value creation in Big BioData which in turn can precipitate concrete success metrics today and into the future. There are some data innovators in the industry working diligently in this direction; but, much like in Big BioData itself, their value may be obscured by lack of awareness of their efforts or potential benefit. This paper acknowledges several of these individuals and groups actively working to bring the future of medicine into the present. This white paper explores: - What success in Big BioData means today and how the notion of success will change tomorrow; - Which companies have found documented success in the field and what they did; and - How unlocking innovation within individuals and companies can evolve Big BioData practices and outcomes. Copyright, 2014 Citizen, Inc. CM0007.SA.2014.BBD005 2

3 WHAT DOES SUCCESS IN BIG BIODATA MEAN TODAY? Reactive Healthcare Innovation. The first success achievable by today s standard of innovation includes reliably insightful and powerful reactive healthcare technologies. According to the US FDA, there are 32,000 health and medical apps available. 3 By Apple s account in 2014, over 6,800 health and fitness (not medical) applications are available in its App Store alone. Unfortunately, the majority of these applications are not downloaded or used extensively and only handfuls have achieved popularity with the public. Perhaps, consumers do not find sufficient value added to their lives with the use of THERE IS GREAT VALUE IN THE WEARABLE HEALTHCARE MARKET, WHICH IS MEASURED AT $2.2B. these apps. Furthermore, over 70% of all big data applications (not only in healthcare) do not use analytics but simply implement data visualization techniques. Although the software arm of Big BioData innovation lags, there is great value in the wearable healthcare market, which is measured at $2.2B. 4 Wearables only represent a fraction of the market size in health and medical applications, but elucidate the need for more powerful products to command available resources. As reviewed in the second white paper of the Big BioData series, 5 basic analytics engines are capable of extracting powerful insights from the complex datasets that these mhealth applications utilize. Therefore, early success in Big BioData involves the implementation of analytics engines to drive value creation of products with powerful insights into the data that consumers, patients, and other entities produce. Risk-sharing. The current healthcare infrastructure of the United States is modeled around a fee-for-service system where the majority of American greater than 75% use healthcare insurance to help cover these costs. Unfortunately, this means that doctors, Copyright, 2014 Citizen, Inc. CM0007.SA.2014.BBD005 3

4 providers, businesses, and patients enter into a system that breeds an excessive, and oftentimes unneeded, administration of tests, treatments, medicines, and products. 6 The current system focuses on volume rather than value. In order to establish future success, the current infrastructure must shift towards evidence-based medical (EBM) practices. Unfortunately, a fully EBM-based system is not possible to implement ubiquitously. However, the movement towards risk sharing models in healthcare are not only possible but are currently being explored. Risk sharing in healthcare assesses patient outcome and 2011 SAW OVER 75% OF ALL US-BASED HOSPITALS USING EMRS TO TRACK AND LOG SECURE PATIENT INFORMATION. not patient volume. This means that the healthcare ecosystem and its constituents enter an agreement to bear a burden of risk in order to maximize unrealized benefits, which include: lower insurance premiums, less wasteful administration of medical treatments, and outcome-based rewards for clinicians. Government promotion of BBD. The third metric of success achievable by today s progress is the widespread promotion of Big BioData by the government to lower the activation barrier to innovation. Important initiatives include implementing electronic medical records (EMRs) and releasing data for use by innovators. Previously, 30% of doctors used EMRs in However, through active promotion, 2011 saw an increase to over 50% of doctors and over 75% of all US-based hospitals using EMRs to track and log secure patient information. Furthermore, over the last 10 years, governments in countries like the US and the UK have gradually made more data free and available for download and use thereby helping push along innovation in various big data sectors. 7 Copyright, 2014 Citizen, Inc. CM0007.SA.2014.BBD005 4

5 THE SILHOUETTE OF FUTURE SUCCESS. Infrastructural changes. In order to achieve success with Big BioData in the future, the healthcare infrastructure must be reinvented. In the United States, this level of revolutionary change in healthcare has not been seen since the introduction of Medicare in Since then, the last half-century has teetered along the aging tracks of a postmodern healthcare system in an increasingly technology-infused environment. For instance, once the benefits of today s successes in reactive healthcare innovation are realized, the dominant fee-for-service or treatment-based system will become a vestigial structure without any place in the face of outcomes reporting and patient-centric medicine. Unfortunately, this level of infrastructural change will take time to develop. Agents in the healthcare ecosystem including practitioners, consumers, and even innovators are currently resistant to significant change. For example, practitioners make most of their treatment decisions independently and subjectively as they have done for centuries. Moving to an ecosystem which uses the best possible evidence alongside clinical judgment sometimes counter to our intuition requires a higher level of trust and understanding not yet seen in the healthcare industry. Reactive to Preventative. The other major success metric to shoot for in the future is moving from reactive to preventative medicine and healthcare innovation. Preventative healthcare refers to proactively fighting for disease prevention and lifestyle wellbeing rather than reactive disease treatment. A fully preventative system requires the paradigm shift in healthcare infrastructure to mature parallel to the shift from reactive to preventative. Two reasons for this are: 1) A fully preventative healthcare ecosystem is inherently one that is evidence-based and requires full trust in advanced analytics and insights from complex datasets. Unlike reactive healthcare, the disease or lifestyle condition or complication has yet to occur and therefore doesn t yet exist. Copyright, 2014 Citizen, Inc. CM0007.SA.2014.BBD005 5

6 Preventative innovation requires trust that something could happen, but that proactive steps are taken to prevent ailments from maturing, and 2) Innovators have yet to harness to full power of Big BioData insights. As described above, very few applications are made with powerful analytics to drive even more powerful insights. As such, until consistently high value can be unlocked from data, at best we have strong reactive healthcare potential and very basic preventative measures to implement. There is an early push in this direction from entities like Flatiron that hope to unlock useful oncological information from large sets of data made available to doctors and patients through targeted application of advanced analytics. 9 Startups like Flatiron leverage software as a service (SaaS) models more commonly found in business solutions. The novelty of such data service integrations AT BEST WE HAVE STRONG REACTIVE HEALTHCARE POTENTIAL AND VERY BASIC PREVENTATIVE MEASURES TO raises questions of efficacy, reliability and security even as they lean forward into areas in healthcare where fresh thinking and dynamic approaches are desperately needed. A LONG ROAD AHEAD, BUT WE RE MAKING PROGRESS. IMPLEMENT. Given the above targets, the path to success might be muddled by uncertainty as to where to begin. The following section will explore current players in the healthcare ecosystem and examine their accomplishments that lead us towards success. The US Government. An unlikely protagonist, the US Government has taken great strides towards harnessing the real value of Big BioData. In 2009, as part of the Open Government Initiative to increase government transparency, the US Government has matured their open data initiatives into a federally run site with further subdivisions for states and cities in the United States. 10 This site is a warehouse for online datasets Copyright, 2014 Citizen, Inc. CM0007.SA.2014.BBD005 6

7 ranging from healthcare and law to business and agriculture. All the data is open access, free to download, and easy to index. The site promotes these datasets in the hope that innovators, who have easy access to large collections of information, can produce platforms and technologies with powerful analytics. The open data initiative in the US has now inspired 44 other countries to launch similar websites to promote innovation in big data. 11 As a continuation to the open data portal, the federal government has also promoted the proliferation of data acquired under the Affordable Health Care Act in markets related to healthcare and healthcare insurance with the aim of better understanding modern US healthcare consumers. In an effort to promote bottom up proliferation of data, the US Government also passed the Health Information Technology for Economic and Clinical Health (HITECH) Act in 2009, which releases nearly $40B in incentives for the healthcare ecosystem to promote THE EXPLICIT GOAL IS MEANT TO ACHIEVE AROUND 90% ADOPTION OF EMRS BY and adopt the use of electronic medical records (EMRs) with up to $2B in funds available for developing HITECH-related skillsets. 12 The explicit goal is meant to achieve around 90% adoption of EMRs by There has been significant progress made to this goal, as over 75% of hospitals and over 50% of practitioners currently use EMRs. Private Companies, Basic Analytics. As mentioned earlier in this white paper, even basic analytics can have a powerful impact. In the healthcare provider sphere, Kaiser Permanente has implemented its HealthConnect platform to connect and push EMRs to healthcare providers and consumers. HealthConnect has both seamlessly linked treatments specific to a patient from doctor to doctor, as well as lowered clinical visits for subscribers by 25%. Of course, Kaiser Permanente is just one example of companies starting to use patient datasets to advise medical practices. Another company in this category includes Acxiom. This company uses big data to analyze consumer behavior with applications to several fields. 13 As an unsuspecting giant in Big BioData, Google has entered the playing field with powerful artificial intelligence algorithms to drive value creation across multiple fields Copyright, 2014 Citizen, Inc. CM0007.SA.2014.BBD005 7

8 including healthcare. As part of the core of this arsenal of machine learning, its recent $500M acquisition of DeepMind uses systems neuroscience to build powerful learning algorithms that tackle cross-disciplinary challenges in Big BioData and big data more broadly. 14 Google s DeepMind is beginning to turn its powerful toolset towards solving some of the greatest challenges in Big BioData to improve upon existing Google innovations, such as its famous Flu Trends application. 15 Other Big BioData innovators are taking advantage of pre-existing big datasets to build applications that drive powerful insights with advanced analytics. For example, ginger.io is a company that specializes in using machine learning to drive care provision for patients with chronic conditions who desire a purportedly more tailored care experience. 16 CROSSING BOUNDARIES FOR REAL INNOVATION. The key to the success of these small case examples is the ability to collaborate in a multidisciplinary setting. For example, TransCelerate BioPharma represents a collaboration between leading pharmaceutical companies, leading research universities, and innovators in Big BioData who are coming together to share data and methodologies that answer common research and development goals. The aim of this non-profit organization is to deliver high quality medicines with a higher throughput through the combined resources of giants and clever analytics. Even within the healthcare ecosystem, individual nodes must work together to create seamless innovation. This means connecting governments, providers, practitioners, consumers, and corporations. Each node comes with different roles and responsibilities to contribute that dynamically change and evolve parallel to the progression of Big BioData. For example, the US Government s role in the last five years has shown effective Copyright, 2014 Citizen, Inc. CM0007.SA.2014.BBD005 8

9 involvement by making data openly available and easily accessible for other nodes to understand and create innovative products. Interconnectedness, although a strength, is the greatest weakness now plaguing progress in innovation of Big BioData. THE TIP OF THE ICEBERG. Bearing in mind the infrastructure of analytics, healthcare, nodes in the ecosystem, money flow, and goals, we must applaud how far innovation in Big BioData has come. But on the opposite side, we need to acknowledge that this success is really the tip of the iceberg. We will outline three key aspects that need to be matured if we wish to achieve success: 1. Transparency and Dynamic Regulation. In order to innovate, data must be easily accessible to innovators. The more boundaries to data that exist, the greater the activation barrier to driving great products. However, too much open data can be a dangerous tool for those with malicious intent particularly as Big BioData can often deal with consumer s WE NEED TO ACKNOWLEDGE THAT THIS SUCCESS IS REALLY JUST THE TIP OF THE ICEBERG. private information. For example, Barnaby Jack, gray hat hacker, unlocked a rather simple method to hack pacemakers through local access points and stop them from working. 17 Therefore, regulations should be in place and recognize the need to make data accessible to those with innovative ideas. 2. Data Standards. As discussed earlier in this white paper series, Big BioData does involve (but is not limited to) large datasets that are accumulated from several sources. For data to combine and value to be created, the datasets must come from sources with standardized policies on data format and quality; otherwise, we risk inhomogeneity in the data and failure to apply analytics therein. 3. Future Skills. As elucidated above, data analytics are lacking skill in the US and around the world as most applications in big data are data visualization in disguise. In Copyright, 2014 Citizen, Inc. CM0007.SA.2014.BBD005 9

10 order to achieve future success in Big BioData, proper skills must be developed in data science, data management, and design innovation. The combination of these three skills is the missing toolset needed today to push us towards tomorrow where even newer skills might be needed. CONCLUSION. By acknowledging a few key agents in this space, this white paper points to a macro trend that can be witnessed in other highly complex, technical fields where big data is paying a transformational role. For these innovators, finding success with Big BioData means driving mature solutions into the market that bring enhanced levels of benefit to the ecosystem. At the same time, innovators need to break free of the hype cycle the industry is currently immersed in. Governments today are also working towards active regulatory policies that increase access to Big BioData whilst the entire healthcare infrastructure is being strained and pushed towards more of a risk-sharing model. Although there are giant steps to be taken into tomorrow, several key players from government, private sector, and consumer market are making resources available and lowering the innovation activation barrier. In order for this maturation to continue to build, the field must realize infrastructural changes to healthcare will accommodate evidence-based medical practices more broadly as it shifts from reactive to preventative healthcare. Copyright, 2014 Citizen, Inc. CM0007.SA.2014.BBD005 10

11 BIBLIOGRAPHY. 1 Citizen. (2014). Advanced Analytics: Moving Beyond the Big BioData Hype. 2 Daconta, M. (2013). Does the big data hype hold water? 3 Deloitte. (2013). pdf. 4 Forbes. (2014). 5 Citizen. (2014). 6 Deloitte. (2013). 7 UK-big-data. (2014). data.gov.uk; US-big-data. (2014). data.gov. 8 Senate, U. (1964). Medicare. Signed_Into_Law.htm. 9 Flatiron. 10 US-big-data. (2014). 11 US-Gov. (2009b). https//http://www.data.gov//open-gov. Copyright, 2014 Citizen, Inc. CM0007.SA.2014.BBD005 11

12 12 US-Gov. (2009a). 13 Acxiom. (2014). 14 Deepmind. 15 Google. Google Flu Trends. 16 GingerIO. ginger.io. 17 Peterson, A. (2013). RIP Barnaby Jack: The hacker who wanted to save your life. ingtonpost.com/blogs/the-switch/wp/2013/07/29/rip-barnaby-jack-the-hacker-who-wanted-to-save- your-life/. Copyright, 2014 Citizen, Inc. CM0007.SA.2014.BBD005 12

13 KAREEM AYOUB, RESEARCH LEAD Kareem is a Marshall Scholar and doctoral candidate at the University of Oxford and is pursuing his medical degree at Washington University in St. Louis. His research interests lie in using artificial intelligence to decode brain signals to build new technologies that treat neurological disorders. Kareem is a Strategic Consultant for Citizen, working together to help drive innovative products and services to fruition by deriving value from Big Data in various industries. EMANUEL BROWN, PROGRAM DIRECTOR Emanuel is the Director of Design Strategy at Citizen where he leads the effort to define Metadata, a research program that utilizes Citizen s Connected Thinking as a means to surface analysis and insight within emerging market segments, industrial transformations and technology shifts. Copyright, 2014 Citizen, Inc. CM0007.SR.2014.BBD005 13

14 Thank You. KAREEM AYOUB EMANUEL BROWN CITIZEN, INC NW 19TH AVENUE, SUITE 105 PORTLAND, OREGON PLUSCITIZEN.COM

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