In Defence of informed consent for health record research - why arguments from ‘easy rescue’, ‘no harm’ and ‘consent bias’ fail

Abstract

Background Health data holds great potential for improved treatments. Big data research and machine learning models have been shown to hold great promise for improved diagnostics and treatment planning. The potential is tied, however, to the availability of personal health data. In recent years, it has been argued that data from health records should be available for health research, and that individuals have a duty to make the data available for such research. A central point of debate is whether such secondary use of health data requires informed consent. Main body In response to recent writings this paper argues that a requirement of informed consent for health record research must be upheld. It does so by exploring different contrasting notions of the duty of easy rescue and arguing that none of them entail a perfect duty to participate in health record research. In part because the costs of participation cannot be limited to 1) the threat of privacy breaches, but includes 2) the risk of reduced trust and 3) suboptimal treatment, 4) stigmatization and 5) medicalisation, 6) further stratification of solidarity and 7) increased inequality in access to treatment and medicine. And finally, it defends the requirement of informed consent by arguing that the mere possibility of consent bias provides a rather weak reason for making research participation mandatory, and that there are strong, independent reasons for making. Conclusion Arguments from the duty of easy rescue in combination with claims about little risk of harm and potential consent bias fail to establish not only a perfect duty to participate in health record research, but also that participation in such research should be mandatory. On the contrary, an analysis of these arguments indicates that the duty to participate in research is most adequately construed as an imperfect duty, and reveals a number of strong reasons for insisting that participation in health records research is based on informed consent.

Evaluating models of consent in changing health research environments

“…In addition, the claim that informational risks are the only relevant risks of biobank and data registry research appears false. Ploug, for example, invoking relational concerns, points out that anxiety and insecurity about the use of data may reduce trust in health care professionals, leading to patients withholding information, and thus decreasing quality of treatment (Ploug 2020).…”

“…It is argued that in this model individual rights and interests are respected as comprehensively as in the model of Dynamic Specific Consent, since research subjects can choose the specific consent option. As the model does allow for broader consent options as well, it is at the same time better suited to prevent consent fatigue (Ploug andHolm 2015, 2019). Broad Consent becomes acceptable in this framework as an option chosen by the participants themselves, ongoing information ensures awareness of the scope of research, and participants can change preference settings at any time (Ploug andHolm 2019, 2020).…”

Waving away waivers: an obligation to contribute to ‘herd knowledge’ for data linkage research?

“…However, there are two criticisms of applying this principle to the duty to contribute data. First, unlike some potentially life-saving interventional research, data linkage research is not 'an instrument for rescuing sudden victims of accident' (Ploug, 2020). Instead, its aim is to prevent harm to potential future patients.…”

“…Second, there is no guarantee that data linkage research will uncover useful information that will prevent future harm. Even if the information is useful, there is often a ‘lengthy, complex and unpredictable path’ (Ploug, 2020) from scientific discovery to improvements in healthcare.…”

Developing Future Human-Centered Smart Cities: Critical Analysis of Smart City Security, Interpretability, and Ethical Challenges

“…Challenges/Issues Discussed [263] Healthcare Security and privacy [264] Healthcare Data intrepretation and fusion [265] Healthcare Security and privacy [266] Healthcare Informed consent [267] Healthcare Informed consent and confidentiality [268] Surveillance Privacy [269] Surveillance Security and privacy [270] Surveillance Privacy [271] Recruitment Privacy and informed consent [272] Generic Security, privacy, bias, and informed consent [273] Generic Informed consent [274] Recruitment Bias [275] Generic Bias [276] Generic Bias [62] Generic Open data, intrepretation, and annotation…”