Decision support in cardiac surgery : early exploration of requirements with cardiac anesthetists and surgeons
Lapp, Linda and Bouamrane, Matt-Mouley and Roper, Marc and Kavanagh, Kimberley and Schraag, Stefan; Mantas, John and Hasman, Arie and Demiris, George and Saranto, Kaija and Marschollek, Michael and Arvanitis, Theodoros N. and Ognjanović, Ivana and Benis, Arriel and Gallos, Parisis and Zoulias, Emmanouil and Andrikopoulou, Elisavet, eds. (2024) Decision support in cardiac surgery : early exploration of requirements with cardiac anesthetists and surgeons. In: Digital Health and Informatics Innovations for Sustainable Health Care Systems. Studies in Health Technology and Informatics, 316 . IOS Press, GRC, pp. 1827-1831. ISBN 9781643685335 (https://doi.org/10.3233/shti240786)
Preview |
Text.
Filename: Lapp-etal-2024-Decision-support-in-cardiac-surgery.pdf
Final Published Version License: Download (164kB)| Preview |
Abstract
Successful implementation of clinical decision support tools is rare, the key barrier being the lack of user involvement during development. Following the idea, development, exploration, assessment, long-term follow-up (IDEAL) framework, this study aims to provide early insights into the current challenges, clinical processes, and priorities when developing new decision support tools in cardiac surgery. Using a qualitative approach, semi-structured interviews were conducted with cardiac anesthetists and surgeons from three Scottish cardiac centers. Thematic analysis identified adverse postoperative outcomes, ageing cardiac patient population and changing surgical procedures to be the main challenges in cardiac surgery. Existing risk prediction tools were largely not used due to a perceived lack of utility and validation. This study underscores the need to shift focus towards predicting postoperative complications, instead of mortality. It emphasizes the importance of early collaboration with clinical experts and stakeholders in developing decision support systems that are fit for purpose. By identifying the priorities of cardiac clinicians, the study lays the groundwork for developing clinically meaningful prediction models.
ORCID iDs
Lapp, Linda, Bouamrane, Matt-Mouley ORCID: https://orcid.org/0000-0002-1416-751X, Roper, Marc ORCID: https://orcid.org/0000-0001-6794-4637, Kavanagh, Kimberley ORCID: https://orcid.org/0000-0002-2679-5409 and Schraag, Stefan; Mantas, John, Hasman, Arie, Demiris, George, Saranto, Kaija, Marschollek, Michael, Arvanitis, Theodoros N., Ognjanović, Ivana, Benis, Arriel, Gallos, Parisis, Zoulias, Emmanouil and Andrikopoulou, Elisavet-
-
Item type: Book Section ID code: 90489 Dates: DateEvent22 August 2024PublishedSubjects: Medicine > Surgery Department: Faculty of Science > Computer and Information Sciences
Faculty of Science > Mathematics and Statistics > MathematicsDepositing user: Pure Administrator Date deposited: 05 Sep 2024 13:56 Last modified: 01 Oct 2024 13:29 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/90489