Guest post by Natasha Bloodworth of Public Health England
In recent years, public health decision-making has become progressively more complex and is increasingly dependent upon relevant data analysis (Thackers, Qualter, & Lee, 2012). The proliferation of technology has led to the generation of large and complex datasets, which include data derived directly from population monitoring (e.g., clinical records, demographic data, survey data), as well as other indirect determinants of health, such as environmental factors and social behaviour (AbouZahr, Adjel, & Kanchanachitra, 2007). The analysis of such ‘big data’ has the potential to greatly extend the capacity to generate new knowledge, whilst also improving dissemination (Murdoch & Detsky, 2013). However, it does come with its pitfalls. For example, it may be possible to identify individuals based on combinations of components within these large datasets, (Wellcome Trust, 2016), although this is a conceptually complex issue. It is therefore important to explore public perceptions of data sharing and linkage, particularly with regards to potentially identifiable data.
How does the public feel about this?
Although research concerning public perceptions of data sharing and linkage is sparse, there are some issues that recur in the available literature. First, privacy is a fundamental issue surrounding the linking of data. It is expected that individual privacy would be placed above public interest (Higgins, 2003; Peto, Fletcher, & Gilham, 2004), but this does seem to be dependent on the type of information being shared. For example, the majority of the public did not perceive the use of anonymised data from the National Cancer Registry for public health research as an issue (Barrett, Cassell, Peacock, & Coleman, 2006), whereas there was more concern around the use of medical records in biobank research (although most would still consent to their use; Kaufman, Murphy-Bollinger, Scott, & Hudson, 2009).
Privacy and issues of confidentiality are key concerns which are associated with the loss of control about what others may know about an individual, which has potential to erode one’s autonomy and dignity (Institute of Medicine, 2009). Indeed, such is the desire to avoid disclosures, some individuals are willing to forgo medical treatment or participation in medical research, despite the fact that the risk of disclosure is actually very low (Forrester Research, 2005).
Second, consent is another theme that consistently emerges as being integral to the public acceptability of data sharing and linkage (European Commission, 2015; Page & Mitchell, 2006; Peto et al., 2004). U.K. data protection law makes allowances for the sharing and use of data without gaining an individual’s explicit consent (Data Protection Act, 1998). However, it has been reported that the public expect that their explicit consent be sought before their data is shared (e.g. Riordan et al., 2015). This is particularly relevant to public policy where it is not appropriate to collect individual consent due to the logistics associated with gaining access to a large number of patients to request their consent. However, whilst there is a preference for explicit consent, research demonstrates that this is not as much of an issue when anonymised data is being shared (Riordan et al., 2015) and, whilst many would have concerns about their data being shared, few would have actually refused consent had they been asked (Page & Mitchell. 2006).
Finally, the need for clear communication and transparency is another theme that has emerged across the public acceptability literature (e.g. Dogan, 2015). Many individuals cite an absence of transparency as being a cause for concern, particularly surrounding the use of their information for different purposes. An example of this would be if an individual consented for their data to be used for medical research, but it was then used to generate an online marketing profile for them. This transparency should also extend to the authority that is responsible for the data, with many reporting less concern when the data was handled by academic, medical researchers, and to a lesser extent, healthcare agencies (Kaufman et al., 2009).
Exploring public perceptions of data sharing and linkage within the MIDAS project.
Although the extant literature provides some indications as to issues that underpin public acceptability of data usage/ sharing, further work is needed to understand exactly how they relate to contexts in which heterogeneous data is linked (as in the MIDAS project). Ongoing work within the MIDAS project seeks to address these issues by investigating the perceived acceptability of the sharing of anonymised and potentially identifiable data among the general public across a range of scenarios.
Overall, the potential that MIDAS has to inform public health decision-making is great, but we also need to be mindful of some of the issues concerning public perceptions that might arise during this process. Ongoing work within the consortium will help to ensure that these issues are avoided or mitigated within the MIDAS platform.
- AbouZahr, C., Adjei, S., & Kanchanachitra, C. (2007). From data to policy: good practices and cautionary tales. The Lancet, 369(9566), 1039-1046.
Barrett, G., Cassell, J. A., Peacock, J. L., & Coleman, M. P. (2006). National survey of British Public’s views on use of identifiable medical data by the National Cancer Registry. BMJ, 332(7549), 1068-1072.
- Data Protection Act (1998). London: Stationary Office.
- Dogan, A. I. (2015). A Qualitative Study Investigating Public Attitudes Towards Health Protection Registers Established after a Major Incident. Department of Psychological Medicine. London, King’s College London. MSc: 1-65.
- Forrester Research. (2005). National consumer health privacy survey. Retrieved from http://www.chcf.org/topics/view.cfm?itemID=115694.
- Higgins, J. (2003). The Patient Information Advisory Group and the use of patient-identifiable data. J Health Serv Res Policy, 8(1), S1-11.
- Institute of Medicine (2009). Beyond the HIPAA Privacy Rule: Enhancing Privacy, Improving Health Through Research. Washington, DC: National Academy Press.
- Kaufman, D. J., Murphy-Bollinger, J., Scott, J., & Hudson, K. L. (2009). Public opinion about the importance of privacy in biobank research. The American Journal of Human Genetics, 85, 643-654.
- Murdoch, T. B., & Detsky, A. S. (2013). The inevitable application of big data to health care. Jama, 309(13), 1351-1352.
- Page, S. A., & Mitchell, I. (2006). Patients’ opinions on privacy, consent and the disclosure of health information for medical research. Chronic Dis. Can., 2, 60-67.
- Peto, J., Fletcher, O., & Gilham, C. (2004). Data protection, informed consent, and research. BMJ, 328, 1029-30.
- Riordan, F., Papoutsi, C., Reed, J. E., Marston, C., Bell, D., & Majeed, A. (2015). Patient and public attitudes towards informed consent models and levels of awareness of Electronic Health
- Records in the UK. International journal of medical informatics, 84(4), 237-247.
- Thacker, S. B., Qualters, J. R., Lee, L. M., & Centers for Disease Control and Prevention. (2012). Public health surveillance in the United States: evolution and challenges. MMWR Surveill Summ, 61(Suppl), 3-9.
- Ipsos, Mori. (2016). The One-Way Mirror: Public attitudes to commercial access to health data. London: Wellcome Trust.