Abstract
BackgroundAdvancing the use of genomic data with routinely collected health data holds great promise for health care and research. Increasing the use of these data is a high priority to understand and address the causes of disease.ObjectiveThis study aims to provide an outline of the use of genomic data alongside routinely collected data in health research to date. As this field prepares to move forward, it is important to take stock of the current state of play in order to highlight new avenues for development, identify challenges, and ensure that adequate data governance models are in place for safe and socially acceptable progress.MethodsWe conducted a literature review to draw information from past studies that have used genomic and routinely collected data and conducted interviews with individuals who use these data for health research. We collected data on the following: the rationale of using genomic data in conjunction with routinely collected data, types of genomic and routinely collected data used, data sources, project approvals, governance and access models, and challenges encountered.ResultsThe main purpose of using genomic and routinely collected data was to conduct genome-wide and phenome-wide association studies. Routine data sources included electronic health records, disease and death registries, health insurance systems, and deprivation indices. The types of genomic data included polygenic risk scores, single nucleotide polymorphisms, and measures of genetic activity, and biobanks generally provided these data. Although the literature search showed that biobanks released data to researchers, the case studies revealed a growing tendency for use within a data safe haven. Challenges of working with these data revolved around data collection, data storage, technical, and data privacy issues.ConclusionsUsing genomic and routinely collected data holds great promise for progressing health research. Several challenges are involved, particularly in terms of privacy. Overcoming these barriers will ensure that the use of these data to progress health research can be exploited to its full potential.
Highlights
BackgroundThe progression of genomics in the last few decades has been remarkable
We developed interview questions with our advisory board: a group of UK geneticists and data scientists who were interested in using genomic data and our discussions centered around these: 1. What is the purpose of integrating the genetic data with health data?
The genomic data we identified in our literature review included single nucleotide polymorphisms (SNPs), polygenic risk scores, and gene activity scores
Summary
BackgroundThe progression of genomics in the last few decades has been remarkable. Since 2001, when the Human Genome Project mapped and sequenced virtually every gene in the human genome, genetic sequencing technology has advanced rapidly in both the public and private domains. A simple search in the medical database, PubMed, shows that research on genomics has more than quadrupled since 2000, from around 340,000 published articles on this topic growing to 1.5 million by 2020. This increase has translated into quicker diagnoses, better outcomes, and more effective health care for patients [2,3,4]. Great strides have been made in cancer research, for example, where patients are being treated according to their own or the tumor’s genomic data [5]. Advancing the use of genomic data with routinely collected health data holds great promise for health care and research.
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