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Surveys suggest that there is a dichotomy in how citizens view research for public good and research for commercial gain. As a consequence, the idea that a research initiative, such as a learning health system, for both public and commercial benefit may be controversial and reduce public trust.
Objectives and Approach
This study aims to investigate what informed citizens considered to be appropriate uses of health data in a learning health system. Two paired four-day juries were run, with different jurors but the same purpose, expert witnesses and facilitators. Overall, 694 people applied to be jurors; 36 were selected to match criteria based on national demographics and their prior privacy views. Jurors considered whether and why eight exemplar data uses of depersonalised patient data were acceptable. The exemplars were data uses planned by the learning health system initiative to improve care pathways (planned uses), and possible unplanned data uses.
All planned uses were considered appropriate by most, but not all, jurors, as they had the potential of benefitting the public through improving care. Positive health outcomes were more acceptable than improved efficiency of services, given jurors prior beliefs about how the NHS operates raising concerns about whether improving efficiency would lead to inequitable distribution or closure of services. The potential uses were considered appropriate where there were improvements in drugs, treatments, or lower NHS costs. Some jurors became more accepting of commercial uses as they understood them better. Commercial uses that prioritised generating profit and did not produce health benefits for the public were unacceptable, regardless of any safeguards for the data. Commercial gain that occurred secondary to achieving public benefit were generally accepted.
Juries elicit more informed and nuanced judgement from citizens than surveys. Jurors tended to be more accepting of data sharing to both private and public sector after the jury process. Many jurors accept commercial gain if public benefit is achieved. Some were suspicious of data sharing for efficiency gains.
A recent article in The Lancet establishing the principles of inclusion health, highlighted substantial gaps in our understanding of the drivers of health inequalities in socially excluded groups such as people with a history of incarceration, people who experience homelessness, sex workers, people with mental illness, and people who inject drugs1. Cross-sectoral data linkage of electronic health records with services working with socially excluded groups was one of the key recommendations of this article. The magnitude of health disparities observed in people that experience social exclusion necessitates an international public health response and addressing the determinants of social exclusion has been identified as a key component of closing the gap of Indigenous disadvantage2. This symposium will establish data linkage as a key component of the inclusion health and will complement the efforts of the Pan American Health Oranization's (PAHO) Commission on Equity and Health Inequalities in the Americas. Traditional survey methodology is costly and often results in studies that are highly parochial in nature. Due to difficulties recruiting and retaining marginalized groups, these studies are commonly forced to adopt methodological concessions, often selecting the most convenient participants (i.e., selection bias) or incurring increased rates of loss-to-follow-up (i.e., attrition bias). Conversely, global studies aimed at modelling the burden of disease are often not sufficiently nuanced to answer specific inferential research questions. Data-linkage has the potential to overcome these common biases and limitations. Thus, harmonised international data-linkage studies are an important component of the inclusion health response to identify the determinants of health inequalities in socially excluded groups and inform the global inclusion health agenda. This symposium will bring together facilitators from three countries with extensive experience conducting data linkage studies that generate evidence on health and social inequality in socially excluded groups. Using a current multinational study as an example, barriers to international data-linkage studies, methodological solutions, and distributed approaches to generating international comparative evidence will be presented. Innovative examples of cross-sectoral approaches to linkage with social service, correctional and national survey data will be discussed. The development of a novel framework for identifying social exclusion exposures and determinants of health inequalities typically not captured in administrative health data will also be discussed. The session will conclude with a discussion aimed at forming the foundation of an international data linkage project to address these current gaps identified in the inclusion health series and best practice for translation to policy and practice to address health disparities in socially excluded groups.
Aldridge et al. Morbidity and mortality in homeless individuals, prisoners, sex workers, and individuals with substance use disorders in high-income countries: a systematic review and meta-analysis. The Lancet. 2017;391(10117):241-250. 10.1016/S0140-6736(17)31869-Xhttps://doi.org/10.1016/S0140-6736(17)31869-X
Greenwood M et al. Challenges in health equity for Indigenous peoples in Canada. The Lancet. 2018;Epub ahead of print. 10.1016/S0140-6736(18)30177-6https://doi.org/10.1016/S0140-6736(18)30177-6
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