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Background Scientific researchers who wish to reuse health data pertaining to individuals can obtain consent through an opt-in procedure or opt-out procedure. The choice of procedure may have consequences for the consent rate and representativeness of the study sample, and the quality of the research, but these consequences are not well known. Therefore, this review aims to provide insight into the consequences for the consent rate and consent bias of the study sample of opt-in procedures versus opt-out procedures for the reuse of routinely recorded health data for scientific research purposes. Method A systematic review was performed, based on searches in PubMed, Embase, Cinahl, PsycInfo, Web of Science Core Collection, and the Cochrane Library. Two reviewers independently included studies based on predefined eligibility criteria and assessed whether the statistical methods used in the reviewed literature were appropriate for describing the differences between consenters and non-consenters. Statistical pooling and a narrative synthesis were conducted to report results. Results Fifteen studies were included. Of these, 13 implemented an opt-in procedure, one implemented an opt-out procedure, and one implemented both. The average weighted consent rates were 84.0% among the studies that used opt-in and 96.8% in the single study that used opt-out. In the single study that described both procedures, the consent rate was 21.0% in the opt-in group and 95.6% in the opt-out group. Opt-in procedures resulted in more consent bias compared to opt-out procedures. In studies with opt-in, consenting individuals were more likely to be men, had a higher level of education, a higher income, and a higher socioeconomic status. Conclusion Consent rates are generally lower when using an opt-in procedure compared to using an opt-out procedure. Furthermore, in studies with opt-in, participants are less representative of the study population. However, both the study populations and the way in which opt-in or opt-out was organized, varied widely between the studies, which makes it difficult to draw general conclusions regarding the desired balance between patient control over data and learning from patient data. Such further use may be hampered by administrative burdens and the risk of bias. |
