TY - GEN
T1 - Using clinical decision support and dashboard technology to improve heart team efficiency and accuracy in a transcatheter aortic valve implantation (TAVI) program
AU - Clarke, Sarah
AU - Wilson, Marisa L.
AU - Terhaar, Mary
N1 - Publisher Copyright:
© 2016 IMIA and IOS Press.
PY - 2016
Y1 - 2016
N2 - Heart Team meetings are becoming the model of care for patients undergoing transcatheter aortic valve implantations (TAVI) worldwide. While Heart Teams have potential to improve the quality of patient care, the volume of patient data processed during the meeting is large, variable, and comes from different sources. Thus, consolidation is difficult. Also, meetings impose substantial time constraints on the members and financial pressure on the institution. We describe a clinical decision support system (CDSS) designed to assist the experts in treatment selection decisions in the Heart Team. Development of the algorithms and visualization strategy required a multifaceted approach and end-user involvement. An innovative feature is its ability to utilize algorithms to consolidate data and provide clinically useful information to inform the treatment decision. The data are integrated using algorithms and rule-based alert systems to improve efficiency, accuracy, and usability. Future research should focus on determining if this CDSS improves patient selection and patient outcomes.
AB - Heart Team meetings are becoming the model of care for patients undergoing transcatheter aortic valve implantations (TAVI) worldwide. While Heart Teams have potential to improve the quality of patient care, the volume of patient data processed during the meeting is large, variable, and comes from different sources. Thus, consolidation is difficult. Also, meetings impose substantial time constraints on the members and financial pressure on the institution. We describe a clinical decision support system (CDSS) designed to assist the experts in treatment selection decisions in the Heart Team. Development of the algorithms and visualization strategy required a multifaceted approach and end-user involvement. An innovative feature is its ability to utilize algorithms to consolidate data and provide clinically useful information to inform the treatment decision. The data are integrated using algorithms and rule-based alert systems to improve efficiency, accuracy, and usability. Future research should focus on determining if this CDSS improves patient selection and patient outcomes.
KW - Computerized decision support
KW - Heart Team
KW - Medical informatics
KW - TAVI
KW - User-computer interface
UR - http://www.scopus.com/inward/record.url?scp=84978628157&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84978628157&partnerID=8YFLogxK
U2 - 10.3233/978-1-61499-658-3-98
DO - 10.3233/978-1-61499-658-3-98
M3 - Conference contribution
C2 - 27332170
AN - SCOPUS:84978628157
T3 - Studies in Health Technology and Informatics
SP - 98
EP - 102
BT - Nursing Informatics 2016 - eHealth for All
A2 - Sermeus, Walter
A2 - Weber, Patrick
A2 - Procter, Paula M.
PB - IOS Press
T2 - 13th International Conference on Nursing Informatics, NI 2016
Y2 - 25 June 2016 through 29 June 2016
ER -