The Quantified Human – Big Data and Health
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When
Thu, 21. May 2015, 10:00
Where
Venue
Topic
The amount of data circulating worldwide doubles every year. This trend is also reflected in the health sector, where more and more researchers, companies and physicians are working with “big data”. Health data is collected via social networks, mobile apps or online patient diaries. At the same time, it is becoming increasingly possible to evaluate such data quickly and effectively and to link it with other data, for example on shopping behavior. Such analyses provide deep insights into individual health and lifestyle and entail various ethical and legal challenges for different areas of society:
For individuals, so-called lifelogging enables comprehensive self-monitoring, with which users may increasingly and unaware restrict their own freedom and self-determination.
As part of the open data trend, international research and participatory medicine are making ever greater amounts of raw data available online. This, along with new data linking possibilities, increases the risks of misuse and of loss of confidence in research.
There are many new opportunities for diagnostics, therapy and research in healthcare. However, the new wealth of data also poses new challenges to data interpretation. In addition, there is the concern that data analysis and interpretation could increasingly displace the personal doctor-patient relationship.
In view of these developments, the German Ethics Council will discuss the following questions, among others:
- What effects does the interconnection of data have on the doctor-patient relationship?
- What are the consequences of an increasingly cohesive and often hardly noticeable collection of health data for individual self-perception and freedom?
- How can individuals, researchers and companies handle these data responsibly?
- How can the quality and reliability of complex data analyses be ensured?
- How can trust in research be maintained when participant data can be decrypted?
- How can legislators contribute to effective protection of health data under big-data conditions?
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