Natasha Gulati

The goal of big data is to understand the complete patient, not the condition

February 03, 2017
By Natasha Gulati

Voltaire once said, “Doctors are men who prescribe medicines of which they know little, to cure diseases of which they know less, in human beings of whom they know nothing.” Unfortunately, over 300 years of science, technology and discovery have done little to disprove this statement, especially the last part. Delivering high-quality, educated care entails a granular understanding of the problem, all people affected, possible solutions and related expected outcomes. The health care industry rightfully boasts of countless milestones from the discovery of cells, development of breakthrough drugs and vaccines, advances in genomics and the politicization of health care in the interest of populations. Throughout this evolution, our knowledge of health and disease has been the most important factor, and this knowledge has shown clear stages of development. is recognized as a key organizational asset and data is increasingly being seen as a resource, almost as a currency. Data is being used by industry participants to innovate new products, discover nontraditional revenue streams and transform their organizations.

From a knowledge evolution perspective, the health care industry is at a juncture where it shifts focus from understanding diseases and finding cures to understanding the consumer. Big data is the single most important enabler of this paradigm shift. Big data refers to electronic datasets so large and complex that they are difficult (or even impossible) to manage using traditional software and hardware. Big data can be physical, virtual or a combination of both.

To help fathom the size of big data, typical discussions on the subject generally revolve around the yottabyte, which is equal to a quadrillion gigabytes. The scan of a single organ in one second captures about 10 gigabytes of raw data. The health care industry is creating and accumulating data at an explosive rate. With all the digital information created, plus the advances in Internet penetration, decreasing cost of computing and increasing ubiquity of data-capturing sensors, it is estimated that the world generated over 100 zettabytes of relevant health data by the end of 2014.

Frost & Sullivan estimates that health care big data and analytics generated revenue of $4.44 billion in 2015, and this number will increase to $7.5 billion in 2020. The opportunity is huge, but the market is confused. Burning questions that clients ask revolve around identification of the most profitable, socially impactful and sustainable big data initiatives in health care. To identify the most relevant big data opportunities in health care, Frost & Sullivan developed a framework based on case studies of over 50 big data initiatives globally, conducted by governments, payers, providers, suppliers (pharmaceuticals and medical technology companies) and consumers (open-source projects or funded programs). The framework analyzed the frequency, goals, outcomes, participating organizations and long-term potential of the initiatives, and was validated by industry opinion leaders. In this framework, various big data applications were assessed on two major criteria:

• Market readiness — Indicates the current stage of technological and business development of specific market segments.
• Future industry value — Indicates the level of strategic need that listed market segments will have for big data solutions in 2020.

Parameters constituting the criteria are included in the following chart: The analysis revealed that current big data investments are focused on serving immediate needs of the investing stakeholders, which often makes them siloed and incrementally beneficial, as opposed to investing in a strategic organizational redesign. Health care big data applications in the public domain — initiatives deployed by government agencies for various purposes — are still predominantly in pilot stages.

On the other hand, big data investments by providers and suppliers show better market readiness as indicated by the larger number of initiatives around the world, types of vendors and currently available solutions. While big data investments in clinical research are important, they will be overshadowed by the need for the health care industry to show actual improvements in quality of life, and all industries will eventually move toward generating actionable insights from health care big data.

This brings us to the aforementioned evolution of knowledge in health care. Data generated in health care from medical records, “omics” research, health and wellness devices, clinical trials, transactions and web and social media are used for understanding health and disease better with the goal of finding a cure. Ten years from now, the industry will truly move toward predictive and prescriptive care, which allows consumers to wholly understand their physiological conditions and their future impact early.

This requires a far more granular understanding of the consumers themselves, rather than health and disease alone. Industry participants are moving toward intuitive, patient-centric, consumerist health care services, which means they need to understand consumers in terms of their day-to-day behaviors, social habits, personal and emotional preferences, financial obligations and future aspirations. Big data is playing a monumental role in this by enabling value creation from real-world data. Never before has data generated by consumers been so important in health care. Stakeholders are only just opening the Pandora’s box that is the data generated from mobile devices, ubiquitous sensors, interactive web, unstructured behavioral data from blogs and forums and consumer-provided health information in real-world trials. All of this leads to one goal in health care big data — understanding the patient/consumer beyond his or her pathological condition. As a step in the direction of understanding people better, The Dunedin Multidisciplinary Health & Development Study in New Zealand has tracked participants born between 1972-73 since 1985, and has published groundbreaking research in the areas of child health, injury prevention, infertility, drug abuse and psychosis through real-world data. Now, as the subjects enter the final project phase, it will explore aging in detail. Such a study of aging will be unique, in that it will be able to correlate early-stage life incidents with conditions experienced in aging, a complex data research and management exercise powered by big data tools.

About the author: Natasha Gulati is an industry manager with the Frost & Sullivan Asia-Pacific Healthcare Practice.