Simon Geller, Sebastian Müller, S. Scheider, C. Woopen, S. Meister
{"title":"Value-based Consent Model: A Design Thinking Approach for Enabling Informed Consent in Medical Data Research","authors":"Simon Geller, Sebastian Müller, S. Scheider, C. Woopen, S. Meister","doi":"10.5220/0010828000003123","DOIUrl":null,"url":null,"abstract":": Due to new technological innovations, the increase in lifestyle products, and the digitalisation of healthcare the volume of personal health data is constantly growing. However, in order to use, re-use, and link personalised health data and, thus, unlock their potential benefits in health research, the authors of the data need to voluntarily give their informed consent. That is a major challenge to health data research, because the classic informed consent process requires the immense administrative burden to ask for consent, every time personal health data is accessed. In this paper we argue that all alternative consent models that have been developed to tackle this problem, either do not reduce administrative burdens significantly or do not conform to the informed consent ideal. That is why we used the design thinking approach to develop an alternative consent model that we call the value-based consent model . This model has the potential to reduce administrative burdens while empowering research subjects to autonomously translate their values into consent decisions.","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"3 1","pages":"81-92"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0010828000003123","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
: Due to new technological innovations, the increase in lifestyle products, and the digitalisation of healthcare the volume of personal health data is constantly growing. However, in order to use, re-use, and link personalised health data and, thus, unlock their potential benefits in health research, the authors of the data need to voluntarily give their informed consent. That is a major challenge to health data research, because the classic informed consent process requires the immense administrative burden to ask for consent, every time personal health data is accessed. In this paper we argue that all alternative consent models that have been developed to tackle this problem, either do not reduce administrative burdens significantly or do not conform to the informed consent ideal. That is why we used the design thinking approach to develop an alternative consent model that we call the value-based consent model . This model has the potential to reduce administrative burdens while empowering research subjects to autonomously translate their values into consent decisions.