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The Practice of Health Analytics

The Business Analytics Institute will once again be hosting its Summer School in Data Science for Management in Bayonne, France from July 2 to 11 2018.  In this exclusive five-part series on Why Future Managers Should Invest in Data Science, we will explore the BAI’s unique value proposition around improving managerial decision-making.
Michel Foucault once argued that the only viable yardstick for measuring the value of technology is its contribution to developing human well-being. The near future of Health Analytics may provide substantive proof of this vision. Each day, the human body produces two terabytes of usable data on an individual’s heart rate, sleep patterns, blood glucose, stress levels and brain activity.[i] By 2020, roughly 25,000 petabytes of patient data will be available to the industry.[ii]  As healthcare organizations invest heavily in technology and analytics to take advantage of these opportunities, what are the opportunities for aspiring data scientists?

What is Health Analytics?

Health Analytics involves deriving insights from patterns and correlations in the data that can fuel better decision making in the Health and Life Sciences. KPMG’s recent survey of healthcare professionals reveals that fifty-six percent of the participants surveyed believe that analytics will largely contribute to health care processes, while 35 percent cite lowering healthcare costs, and 32 percent suggest improved health outcomes.[iii]
According to the recent study by Research and Markets, this market is expected to reach USD 24.55 Billion by 2021 from USD 7.39 Billion in 2016, which represents a CAGR of 27.1%.[iv] This exceptional market growth is driven by factors including a multiplication of government initiatives to enhance the adoption of electronic health records, rising pressure to curb healthcare spending, the perceived need to improve patient outcomes, the increase of venture capital investments in the industry, and advancements in analytics and big data technologies.

Can Data Science make a difference?

How will the development of Data Science impact the delivery of health care?  There is a panoply of areas in which a better use of patient and clinical data can make a measurable impact on the industry. Because administrative costs make up about 15% of all healthcare expenditures- providing better patient and physician level data allow clinicians make quicker and more cost-efficient choices. The National Healthcare Anti-Fraud Association estimates the loss to health care fraud in the US alone to be about $80 billion annually, yet current data practices recover less than 5 percent of these losses are recovered.[v] Most importantly, data science can facilitate the transition for “cost care” to “health care” by allowing the industry to identify at-risk patients and encourage them to make lifestyle changes to their future well-being.

In an increasingly competitive healthcare market, eighty-nine percent of industrial executives interviewed by Accenture believe that implementing big data analytics will be the key to maintaining market share.[vi] Partnerships between the medical providers and the pharmaceutical profession, like DataSphere, HealthConnect, and PPC/HealthCore, have provided frameworks for the future of Health Analytics. European and national initiatives, including the Directive 2011/24/EU and the national health card scheme in France are already providing tremendous amounts of data on industry costs, practices across demographics. Local attempts to pool resources in the form of “groupements médicaux territoriaux” have allowed local practitioners to share resources, knowledge, and best practices.

Where are the opportunities for Data Scientists?

The boom of the Quantified Self movement is also fueling the market. Constant streams of Little Data on individuals physical and mental states from a multitude of connected devices capture the quality of our mindfulness, exercise, and diet. The proponents of the Quantified Self claim that this data can potentially improve the quality of our sleep, the way work, and the way we play. Applications of Little Data, like those of Asthmapolis, Quadio, and Zepher are particularly promising both for populations who face specific health challenges (allergies, asthma, heart conditions, etc.), as well as athletes looking for a competitive edge.

A recent study by Stitch concluded that of the approximately 6,000 data scientists in the United States, only 180 are estimated to work in the hospital and health care field.[vii] The industry is far behind other sectors in terms of adopting the latest technology and analytics. NEJM estimates that the health care sector employs 6 times fewer data scientists than the finance sector, 18 times fewer data science than IT, and 60 times fewer specialists than management consulting.[viii]  In spite of a certain number of perceptual and economic barriers, there are multiple opportunities for data scientists to leverage descriptive, predictive, and prescriptive analytics.

What can you learn about Health Analytics from the BAI ?

Aspiring data scientists would do well to learn more about the field and its opportunities. As a prelude to the the BAI Summer School, Profs. Davy Cielen and I will be exploring the evolution of the health care landscape in a free webinar this May 17th . We will review how process mining can be applied to nuture and improve the impact of Data Science in this industry. Finally, we will review how private and public organizations are transforming this data into action to improve our physical and mental well-being for generations to come.
Using real-life examples and case studies in the health and life sciences, participants in this year’s BAI Summer School will discuss the opportunities for Data Science in Management. You will examine how Little and Big Data data sets can be used to improve individual and organizational decision-making. You will apply the models and tools for creating, collecting, and codifying organizational information.  You will learn how to choose and apply the appropriate decision models based on the challenges at hand. You will explore how analytics can enhance decision-making by converting data into actionable insights. Finally, you will analyze the ethical issues inherent in data-driven decision-making.

The BAI Summer School on Data Science for Management

The Business Analytics Institute Summer School in Data Science for Management in Bayonne, France will be held from July 2 to 11 2018. This university and corporate accredited program targets senior and graduate management students who want to understand how data science can enhance both their jobs and their future careers. The session will be facilitated by internationally recognized professors and practitioners on digital economics, managerial decision-making, machine learning and artificial intelligence, and data storytelling. Detailed information on the program, social activities, student testimony, and university accreditation/professional certification can be found at
Lee Schlenker is a Professor of Business Analytics and Community Management, and a Principal in the Business Analytics Institute His LinkedIn profile can be viewed at You can follow us on Twitter at
Previous installments of this five-part series:
Part I : Why Future Managers Should Invest in Data Science
Part II : Machines don’t take great decisions, people do
[i] Eastwood, B., (2016), Patients Key to Making Sense of Medical Data, MIT Sloan
[ii] Dhamdhere, et. al., (2016), Big Data for Health Care
[iii] Walker, T., (2015), Just 10% of healthcare organizations using data, analytics, Managed Health Care Executive
[iv] Markets and Markets (2016), Healthcare Analytics/ Medical Analytics Market by Application
[v] Hitchcock, E. (2018),The Role of Big Data in Preventing Healthcare Fraud
[vi] Bresnick, J.,(2014), 89% of Execs Say Big Data Analytics is Key to Market Share, HealthIT Analytics
[vii] Stitch, (2016), The State of Data Science
[viii] Nemj, (2017),  Using It or Losing It? The Case for Data Scientists Inside Health Care

Yann Gourvennec
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Yann Gourvennec

Yann Gourvennec created in 1996. He is a speaker and author of 6 books. In 2014 he went from intrapreneur to entrepreneur, when he created his digital marketing agency. ———————————————————— Yann Gourvennec a créé en 1996. Il est conférencier et auteur de 6 livres. En 2014, il est passé d'intrapreneur à entrepreneur en créant son agence de marketing numérique. More »
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