Moving from Bench to Bedside: A Social History of Actionability in Biomedicine

Background: As medicine grows increasingly technological and scientific, biomedical researchers working to bring new knowledge to bear on clinical practice face a key question: when is a new intervention or treatment ready for clinical use? Because this is both a technical and ethical dilemma, it is crucial to examine the social history of how different approaches to this question emerge and the values or assumptions they embed. Methods: We examine the rise and proliferation of an increasingly common framework for assessing the value of new biomedical data or technology, "actionability," through a computational analysis of published scientific literature referencing this and related terms, including topic modeling and Medical Subject Headings (MeSH) term analysis of over 7000 scientific abstracts indexed in PubMed. Results: We find that actionability, as a term, began appearing more commonly in published literature in the mid-2000s, and proliferated throughout the 2010s and into the 20s. While originally used primarily in research on healthcare quality and implementation, the concept's rise in popularity is ultimately driven by uptake in the fields of clinical genetics and oncology. Conclusions: The adoption of actionability in these fields suggests that actionability as a conceptual framework may be most valuable to areas of translational medicine seeking to make sense of increasing amounts of data and technological innovation with differing levels of scientific validity and clinical utility. Recognizing this value, we also caution that actionability drives our attention primarily towards whether a test or piece of information can lead to action, not whether that action has proven benefits. As clinicians and researchers face difficult questions about how to sort through growing amounts of data to generate knowledge that can have a real impact on patient health, empirical bioethics should play a key role in analyzing the trade-offs and impacts of different approaches.