Abstract
Clinical data is a primary source of health data, presenting both opportunities and challenges for biomedical research. Privacy protection, informed consent rules, distribution of interests, research ethics, and regulations need to be reshaped.
Regulation of data collection should focus on the rule of informed consent. Clinical data in biomedical research challenges informed consent rules in the following ways: The philosophy of clinical data in biomedical research is to collect and integrate as much health-related data as possible, while patients hope that their personal data will be protected to the greatest extent possible. And individuals' privacy is affected by the decisions of others and could be beyond their control. Besides, there is a conflict between the patient's one-time consent and the ongoing nature of the research. Thus, blanket consent, broad consent, dynamic consent, and tiered consent should be accepted. In what conditions and ways can patients change or withdraw their consent also need to be reconsidered.
Regulation of data processing should focus on the de-identification of data. Specificity of clinical data is important in biomedical research, especially during data processing. Some identifying features are personal privacy, which is valuable for research. Thus, clinical data should be classified and processed appropriately, while retaining necessary identification features. Researchers can use de-identified clinical data without consent and must manage residual risks. At the same time, the re-identification system for clinical data needs to be constructed.
Regulation of data applications should focus on the disposition of rights and the distribution of interests. In clinical data biomedical research, researchers are subject to both biomedical research regulations and data governance rules. Biomedical research combines clinical data with privacy and publicity, serving both public welfare and commercial purposes. The focus of rights in clinical data biomedical research should shift from health to privacy. The approach to regulation should shift from control to sharing.
Ethical review for clinical data in biomedical research needs to be revised. Application of clinical data poses problems in ethical review, such as multiple research subjects, data updates, and algorithm black boxes. Ethical review of clinical data in biomedical research should focus on data utilization, and the review process can be simplified.
The tort liability system in clinical data biomedical research needs to be reformed. The harm in clinical data biomedical research is latent and intangible. Causation is difficult to determine due to the lengthy chain of data circulation. Thus, the rules for clinical data in biomedical research may vary. The scope of harm should be expanded. The causal chain needs to be extended. The principles of imputation need to be reconsidered. Besides, a data security insurance system and a data benefit compensation system need to be constructed.
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