From Rapid Recommendation to Online Preference-Sensitive Decision Support: The Case of Severe Aortic Stenosis.

Jack Dowie ORCID logo; Mette KjerKaltoft; (2018) From Rapid Recommendation to Online Preference-Sensitive Decision Support: The Case of Severe Aortic Stenosis. Medical Sciences, 6 (4). p. 109. DOI: 10.3390/medsci6040109
Copy

The launch of 'Rapid Recommendations' by the Grading of Recommendations Assessment, Development and Evaluation (GRADE) group, in collaboration with Making GRADE the Irresistible Choice (MAGIC) and the British Medical Journal (BMJ), is a very interesting recent development in e-healthcare. Designed to respond quickly to developments that have created new decision situations, their first project resulted from the arrival of minimally invasive Transcatheter Aortic Valve Implantation (TAVI) as an alternative to Surgical Aortic Valve Replacement (SAVR), for patients with symptomatic severe aortic stenosis. The interactive MAGIC decision aid that accompanies a Rapid Recommendation and is the main route to its clinical implementation, represents a major advance in e-health, for a cardiovascular decision in this case. However, it needs to go further in order to facilitate fully person-centred care, where the weighted preferences of the individual person are elicited at the point of decision, and transparently integrated with the best (most personalised) estimates of option performances, to produce personalised, preference-sensitive option evaluations. This can be achieved by inputting the collated GRADE evidence on the criteria relevant in the TAVI/SAVR choice into a Multi-Criteria Decision Analysis-based decision support tool, generating a personalised, preference-sensitive opinion. A demonstration version of this add-on to the MAGIC aid, divested of recommendations, is available online as proof of method.



picture_as_pdf
JD2018 Kaltoft MEDSCI RR2DST.pdf
subject
Published Version
Available under Creative Commons: NC 3.0

View Download

Explore Further

Read more research from the creator(s):

Find work associated with the faculties and division(s):

Find work associated with the research centre(s):

Find work from this publication: