Big Data & Digital platforms: removing barriers to boost adoption in Europe

Transcription

1 Big Data & Digital platforms: removing barriers to boost adoption in Europe Laurent Probst Partner

2 Presentation of Digital Entrepreneurship program & Strategic Policy Forum What Europe can do to take maximum advantage from the opportunities presented by a new wave of digital technologies and to see how that advantage can be used to create good jobs (not in cotton mills), bring economic benefit and help create a better society.

3 The benefits for Europe of Digital Transformation 3

4 Recommendations to boost digital transformation

5 The Challenge for the industry: lack of a common access point to data Scientists cultivate deep expertise in specific subfields. While competing teams are incentivised to protect their data until they can publish or patent their findings. Companies lose data through frequent mergers and acquisitions and a bias against negative results. Healthcare & Pharmaceutical IT architecture and systems are not structured to manage and enhance data exploitation: Within health systems, Big Data will play a critical role in the move from volume-based care to value-based, accountable care supported by flexible technologies. challenges - technical, institutional, operational, and legal. In many cases, the evolution of the law has not kept up with technology, resulting in a governing framework that is challenging to navigate. 5

6 Big Data sets in healthcare Web and social media data: Clickstream and interaction data from Facebook, Twitter, LinkedIn, blogs, and the like. It can also include health plan websites, smartphone apps, etc. [6]. Machine to machine data: readings from remote sensors, meters, and other vital sign devices [6]. Big transaction data: health care claims and other billing records increasingly available in semi-structured and unstructured formats [6]. Biometric data: finger prints, genetics, handwriting, retinal scans, x-ray and other medical images, blood pressure, pulse and pulse-oximetry readings, and other similar types of data [6]. Human-generated data: unstructured and semi-structured data such as EMRs, physicians notes, , and paper documents [6]. 6

7 89% of Ceos of healthcare organisations consider Big data as strategic 7

8 87% of Ceos of healthcare organisations think big data create value 8

9 Philips and salesforce.com team up to reshape healthcare delivery and shape new standards 9

10 Big data: the expected tool for Value Based Healthcare - a concrete case on cancer One of the world s leading research & treatment cancer initiated an aggressive program to reduce the mortality and suffering due to cancer. The program was focused on: the potential of processing massive amounts of clinical data, medical records and physicians dictation/notes to identify the most effective treatment protocols use of cognitive decision-support technology to ingest and learn from the most effective clinical practices at the centers, as well as those published in peer-reviewed journals the design of the technology architecture, the ability of the center to capture the value of the technology, and its ability to operate the technology in compliance with applicable regulations and restrictions. In order to realise the bold vision of reducing the mortality and suffering due to cancer, the client needed to implement dramatic changes to their clinical, technical and financial operations. 10

11 Flatiron: World s Largest Single Source of Structured Real-World Oncology Data and Intelligence. Founded in 2012 and have raised in m $ with Google Ventures Software connects community practices and cancer centers on a common technology infrastructure to address key healthcare challenges. The goal is to power a national benchmarking and research network to transform how cancer care is delivered. For providers, the first application is OncoAnalytics, a web-based software package that seamlessly integrates a cancer center s disparate data systems, and provides real-time business and clinical intelligence with benchmarking. In the near future, providers will be able to leverage de-identified data from other cancer centers on the platform in a HIPAA-compliant manner. 11

12 Big data companies valuations are skyrocketting: Company Name Last Financing Deal Class Last Financing Size (M) Pentaho Corporate Applied Predictive Technologies Corporate Palantir Technologies Venture Capital data Corporate Comscore (SCOR) Corporate Panaya Corporate Caspida Corporate Medallia Venture Capital VoloMetrix Corporate RetailNext Venture Capital Mirantis Venture Capital CrowdStrike Venture Capital

13 Key success factors Store and share data in a secure and legally compliant environment Companies are sprouting up to develop data-driven solutions for supporting providers and population health management institutions. Expanding Data Access and Scaling Data Use. 4Vs: Volume, variety, Velocity, Veracity. Menu-driven, user-friendly and transparent. Real time : fix the lag between data collection and processing. National Health organisation leadership and initiative - NIH B2K. FDA-EMA bi-lateral discussions relating to the ISO IDMP data standards From Proof of concept to Proof of Value 13

14 Key challenges Ownership/copyright. Governance. Data collection/usage. Data quality and cleansing. Digital ID Management. Open source. Flexibility. Interoperability. Standards. TRUST Investment. Business model. Connectivity. Digital ID Management. 14

15 Conclusion What would you recommend to EU policy makers to make EU industry successful and competitive in adopting Big data? 15

16 Conclusion: Building Trust and enabling 16

17 The new technology stack Identity and security Tools that manage user authentication and system access, as well as secure the product, connectivity, and product cloud layers. Product cloud Smart product applications Rules/analytics engine Application Platform Product data database Connectivity Product data database Product External Information sources A gateway for information from external sources - such as weather, traffic, commodity and energy prices, social media, and geomapping - that informs product capabilities. Integration with business systems Tools that integrate data from smart, connected products with core enterprise business systems such as ERP, CRM, and PLM. Product software Product hardware 17

18 Creating new value with data External Data Sources Smart, connected products Enterprise Basic insights Raw data Data Lake Aggregated raw data in multiple formats Control and optimisation Analytics Descriptive Diagnostic Predictive Prescriptive Capture products condition environment, and operation. Raw data Examine the causes of reduced product performance of failure. Deeper insights Detect patterns that signal impending events. Business Customer Partner Identify measures to improve outcomes or correct problems. 18

19 This publication has been prepared for general guidance on matters of interest only, and does not constitute professional advice. You should not act upon the information contained in this publication without obtaining specific professional advice. No representation or warranty (express or implied) is given as to the accuracy or completeness of the information contained in this publication, and, to the extent permitted by law, PricewaterhouseCoopers, Société coopérative, its members, employees and agents do not accept or assume any liability, responsibility or duty of care for any consequences of you or anyone else acting, or refraining to act, in reliance on the information contained in this publication or for any decision based on it PricewaterhouseCoopers, Société coopérative. All rights reserved. In this document, refers to PricewaterhouseCoopers, Société coopérative, which is a member firm of PricewaterhouseCoopers International Limited, each member firm of which is a separate legal entity.