Real-time estimation of surgical procedure duration

Real-time estimation of surgical procedure duration

Guédon, A.C.P. (TU Delft Medical Instruments & Bio-Inspired Technology)
Paalvast, M.
Meeuwsen, F.C. (TU Delft Medical Instruments & Bio-Inspired Technology)
Tax, D.M.J. (TU Delft Pattern Recognition and Bioinformatics)
van Dijke, A.P. (TU Delft Medical Instruments & Bio-Inspired Technology)
Wauben, L.S.G.L. (TU Delft Medical Instruments & Bio-Inspired Technology)
Van Der Elst, M. (Reinier de Graaf Gasthuis)
Dankelman, J. (TU Delft Medical Instruments & Bio-Inspired Technology)
van den Dobbelsteen, J.J. (TU Delft Medical Instruments & Bio-Inspired Technology)

2015

Efficiency in the Operating Room (OR) is a topic of growing interest. Planning of care is a crucial element to ensure optimal use of the ORs. Currently, OR scheduling is considered as a complex task based on predictions of surgery duration. The latter are often based on average times, but turn out to be inaccurate in practice because of various factors (such as complexity, patient's characteristics, unexpected events, etc). The aim of this study is to develop a prediction system that estimates in real-time the remaining duration of a surgical procedure. The prediction system was based on monitoring the progress of a procedure by recording the activation of a single piece of equipment in the OR, the electrosurgical device. Support Vector Machines was then used as a classifier to predict the remaining surgical procedure duration and thereby the optimal timing to start preparing the next patient for surgery. The classifier was trained with data on the activation of the electrosurgical device during 55 laparoscopic cholecystectomies. The performance tests showed a mean error rate about 0.2, which means that about 80% of the procedures were classified correctly. The real-time prediction system is a promising tool to improve OR planning and decrease unnecessary patients' waiting times.

operating room
pattern recognition
planning
procedure duration
support vector machines
workflow

http://resolver.tudelft.nl/uuid:7dfe8f89-f915-460c-99a6-8820a7a2632a

https://doi.org/10.1109/HealthCom.2015.7454464

Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, USA

Campus only

978-1-4673-8325-7

HealthCom 2015 - 17th International Conference on E-Health Networking, Application and Services: 1st International Workshop on IOR

17th International Conference on E-Health Networking, Application and Services, HealthCom 2015, 2015-10-13 → 2015-10-17, Boston, United States

Geudon moet Guédon zijn. Krijg dat niet aangepast via master data; wel als extra naam toegevoegd aldaar. Zij staat gewoon verkeerd in PS.

Institutional Repository

conference paper

© 2015 A.C.P. Guédon, M. Paalvast, F.C. Meeuwsen, D.M.J. Tax, A.P. van Dijke, L.S.G.L. Wauben, M. Van Der Elst, J. Dankelman, J.J. van den Dobbelsteen