How Big Data revolutionizes the Healthcare Industry

The last hope for many patients often comes in the form of a revolutionary treatment being developed by Big Pharma suppliers like Roche, Novartis, Merck or Pfizer. One that, in most cases, will also take a big amount of time to come to market. It is not uncommon for their development to take up to 15 years. This is due to many reasons, such as the time-consuming clinical studies which are needed for the verification of safety and effectiveness, the declining success rate and stagnant pipelines.

Moreover, the growing and aging population, market expansion and advances in medical treatments lead to higher expenditures in the healthcare sector. Deloitte projects the global healthcare spending to be USD 8.73 trillion in 2020. Compared to 1.3% in 2012–2016, the growth in global healthcare expenditures in 2017–2021 is predicted to reach 4.1%.

Fortunately, Big Data is now extending its reach from marketing and sales over to other parts of the industry, such as research and development and patient care. It is starting to be used to optimize innovation, to build new tools, and to improve the efficiency of research and clinical trials. In this article we will explore how.

Faster market maturity: Through efficient data usage trial costs and length can be reduced.

Using sensors and devices

Healthcare expenditures are increasingly being spent on Smart Healthcare also referred to as eHealth. In their industry report, Deloitte describes that eHealth “is delivering solutions to tackle the increasing need for better diagnostics and more personalized therapeutic tools”. This includes the use of technology to diagnose and cure illnesses more accurately. It is also simplifying the process of keeping patients informed about their status as well as enabling self-treatment at home.

Devices like health apps, fitness trackers, health monitors, medical sensors are already used today and the development in this field will increase. These devices produce a vast amount of data. And this data can be used to prevent medical errors, improve the patient’s experience and ease health insurance & medical billing operations.

Optimizing clinical drug development

Through efficient data usage, costs and length for pipelines could see a signification reduction. New technologies and processes in systems biology and next-generation sequencing continue to improve and produce evermore data. Thus, integrating the vast amount of data that is being produced with the right analytical capabilities will have a vast impact on pharmaceutical R&D. Some of the rewards include: acceleration of trials and lower likelihood of data errors, faster responses to emerging insights from clinical data and improved safety and risk management.

Likewise, it will be possible to replace placebo control groups by virtual control groups by filtering and analyzing the flood of data collected in studies over the years. In fact, the first project with data driven virtual control groups has already been successfully executed by Roche.

Integrating and collaborating

The orientation towards data driven healthcare can also be seen if we look at examples of partnerships and acquisitions inside the healthcare market:

1. Since spring of this year Novartis partners with the data management provider Science 37. With their help Novartis will execute up to 10 studies in the next 3 years combining traditional and digital methods.

2. The data analytics company Medidata based in New York does clinical studies for 18 out of the 25 biggest healthcare companies. They have collected more than 14000 studies and more than 4 million patient data which can be used to e.g. enable virtual control groups and reduce time and costs of clinical studies.

3. To improve their data analytics and develop data driven clinical studies Roche acquired the healthcare technology and services company Flatiron for USD 1.9 billion in the beginning of this year.

A challenge and a solution

The growing involvement of Big Data in the healthcare industry brings up issues that stakeholders have to deal with. These include: reliability of data from personal and/or other systems, data ownership and responsibility, confidentiality amidst today’s cybersecurity challenges (keeping the data safe), and data monetization. MADANA aims to help stakeholders in the healthcare industry to cope with these challenges. To get to know more about MADANA and the eHealth use case, take a look at our white paper.

Be part of the Big Data Revolution!

Martin Picard

Written by

Business Developer @ MADANA | Entrepreneurship Enthusiast

The MADANA Blog

Securely bridging the gap between data and insights.

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