Preferences and Precision Medicine

Hadley Stevens Smith smiling at camera

The uptake and delivery of precision medicine is very sensitive to the preferences of those affected, as discussed by Hadley Stevens Smith in a recent CHDS seminar. Smith is an Assistant Professor in the Department of Population Medicine at Harvard Medical School and Harvard Pilgrim Health Care Institute.

Precision medicine interventions such as genomic sequencing are increasingly relevant for population screening and clinical diagnosis. The effects of such interventions go beyond the individual patient. The information that is generated via sequencing is heritable information – it runs in families – which means that the results of the test for the patient can have implications for relatives’ health. However, most evaluations of these interventions do not systematically account for effects on family members. Incorporating these considerations requires integrating ethical, legal, and social implications into how outcomes are defined and measured.

Smith discussed the conceptual and pragmatic aspects of eliciting and integrating preferences into evaluations of precision medicine, using pediatric genomic sequencing as a case example. She described foundational qualitative research intended to inform quantitative preference research. This work included assessing the family characteristics that shape the pediatric experience, exploring how families approach related decisions and respond to the results. Key drivers can be categorized into four domains: underlying values, perceived benefits, perceived risks, and other pragmatic considerations. Understanding these drivers aids in developing measurement approaches that better capture the value of interventions for families as well as patients.

Learn more: Read the publication, Key Drivers of Family-level Utility of Pediatric Genomic Sequencing
Learn more: Read the publication, Framing the Family: A Qualitative Exploration of Factors that Shape Family-level Experience of Pediatric Genomic Sequencing

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