Early Diagnosis linking Big Data – hope or nightmare? (L4)

Big Data and the number five.

Big data has been seen during the last years as one of the most promising fields in health. By having access to large amounts of information, which might have been originally collected for other purposes, and using computer science and statistics, it could be possible to extract valuable and unexpected information. This could provide new treatments and new diagnosis tools for patients.

During the session, Dietmar Berger (Genetech) and Marc Wortmann (Alzheimer’s Disease International) discussed Breast Cancer and Alzheimer’s Disease, respectively. These two diseases were presented as examples where Big Data could have a big impact. These are two conditions where early diagnosis has a crucial importance on the treatment. But the impact could go as far as the support provided for patients during their life. So, Big Data could have a tremendous influence, by discovering new risk factors, new ways to diagnose and new ways to follow-up patients.

However, while Big Data can look trivial to some, it is quite the opposite from that. In Big Data, five is a very important number, we have learned from Reinhard Riedl (BFH Center Digital Society). So, we should never forget both the 5 pillars and the 5 challenges that follow:

Five pillars:

  1. Data quality and access – Data should be relevant and there should be an authorization to use it.
  2. Algorithms – We have to improve the algorithms since this is the magic ingredient for Big Data. A new profession could be created for this (algorithm analyst), as suggested by Ricardo Baptista Leite (Member of Portuguese Parliament).
  3. Having the right skillset – Keep on learning!
  4. Knowledge and understating – Grasping the big picture from the dots.
  5. Ethics – Think about personalisation versus discrimination.

Five challenges

  1. Accessibility of data – We need to make sure that personal data is available for personal health and research.
  2. Big data skills – New forms of education and the need to educate professionals on this area.
  3. Awareness of policy makers – Engagement for data usage and investment in research and willingness to use facts.
  4. Transdisciplinary collaboration – We need even more collaboration than what is known so far. Clinical and preclinical health experts, biologists, molecular biologists, computer scientists, mathematicians have to work together.
  5. Ethics beyond bureaucracy – Make it easy for researchers to reflect on the ethical dimension that they are using. Using big data without ethics is unethical. And not using big data is unethical. Think about this!
    With the five challenges and the five pillars in mind, we should face Big Data more realisticly. It will unravel a great new world of knowledge, but the path will be hard. But you know…with big risks come big rewards.

This article was written by the Young Gasteiners Luís Guedes, Durdica Morosevic and Ramona Ludolph and originally published on the blog of the European Health Forum Gastein

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