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In a study published in the AMA Journal of Ethics, researchers explored the role of social and behavioral data in precision medicine research.
Electronic health records (EHRs) can offer information on social and behavioral data, which can aid research investigating genetic and social factors across health disparities; for example, factors such as substance use and eating habits inform some of the risk associated with preventable premature deaths in the United States. Brittany Hollister, PhD, and Vence L. Bonham, JD, from the National Human Genome Research Institute at the National Institutes of Health, discussed potential biases in collecting, using, and interpreting EHR-based data in precision medicine research.
Current collection of behavioral and social data by precision medicine researchers is increasingly done using EHR data, as opposed to self-report methods such as surveys. However, extraction and use of EHR data poses challenges of inconsistencies or inaccuracies. Another challenge is determining what data are included or excluded from EHRs, and the consequences of using data collected through biased methodologies. The National Academy of Medicine addressed some of this in recommendations for the systematic capture of behavioral and social measures.2 They recommended intentional collection of structured social environment data, as well as the development of a plan by the National Institutes of Health to include social and behavioral data in EHRs. The current inconsistencies in collecting social and behavioral data pose difficulties to use in precision medicine research, but with improved collection methods these difficulties could be amended.
more at https://www.medicalbag.com/ethics/precision-medicine-research-ehr-data/article/808747/
Via nrip
