TY - GEN
T1 - Decision support in cardiac surgery
T2 - 34th Medical Informatics Europe Conference
AU - Lapp, Linda
AU - Bouamrane, Matt-Mouley
AU - Roper, Marc
AU - Kavanagh, Kimberley
AU - Schraag, Stefan
PY - 2024/8/22
Y1 - 2024/8/22
N2 - 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.
AB - 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.
KW - decision support
KW - stakeholder engagement
KW - cardiac surgery
KW - postoperative complications
KW - risk prediction
UR - http://www.scopus.com/inward/record.url?scp=85202006887&partnerID=8YFLogxK
U2 - 10.3233/shti240786
DO - 10.3233/shti240786
M3 - Conference contribution book
VL - 316
T3 - Studies in Health Technology and Informatics
SP - 1827
EP - 1831
BT - Digital Health and Informatics Innovations for Sustainable Health Care Systems
A2 - Mantas, John
A2 - Hasman, Arie
A2 - Demiris, George
A2 - Saranto, Kaija
A2 - Marschollek, Michael
A2 - Arvanitis, Theodoros N.
A2 - Ognjanović, Ivana
A2 - Benis, Arriel
A2 - Gallos, Parisis
A2 - Zoulias, Emmanouil
A2 - Andrikopoulou, Elisavet
PB - IOS Press
CY - Amsterdam
Y2 - 25 August 2024 through 29 August 2024
ER -