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1000
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Abstract/Summary
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Digitization offers considerable potential for strengthening prevention in the healthcare system. Data from various clinical and nonclinical sources can be collected in a structured way and systematically processed using algorithms. Prevention needs can thus be identified more quickly and precisely, and interventions can be planned, implemented, and evaluated for specific target groups. At the same time, however, it is necessary that data processing not only meets high technical but also ethical standards and legal data protection regulations in order to avoid or minimize risks.This discussion article examines the potentials and risks of digital prevention first from a 'data perspective,' which deals with the use of health-related data for the purpose of prevention, and second from an 'algorithm perspective,' which focuses on the use of algorithmic systems, including artificial intelligence, for the assessment of needs and evaluation of preventive measures, from an ethical and legal point of view. Finally, recommendations are formulated for framework conditions that should be created to strengthen the further development of prevention in the healthcare system.
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1000
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Hinweis
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DeepGreen-ID: e3ce7b9ceb79416c8a32910fdead1319 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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