Adaptive business intelligence in healthcare - A platform for optimising surgeries

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Abstract

Adaptive Business Intelligence (ABI) combines predictive with prospective analytics in order to give support to the decision making process. Surgery scheduling in hospital operating rooms is a high complex task due to huge volume of surgeries and the variety of combinations and constraints. This type of activity is critical and is often associated to constant delays and significant rescheduling. The main task of this work is to provide an ABI based platform capable of estimating the time of the surgeries and then optimising the scheduling (minimizing the waste of resources). Combining operational data with analytical tools this platform is able to present complex and competitive information to streamline surgery scheduling. A case study was explored using data from a portuguese hospital. The best achieved relative absolute error attained was 6.22%. The paper also shows that the approach can be used in more general applications.

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Ferreira, J., Portela, F., Machado, J., & Santos, M. F. (2019). Adaptive business intelligence in healthcare - A platform for optimising surgeries. In Advances in Intelligent Systems and Computing (Vol. 932, pp. 611–620). Springer Verlag. https://doi.org/10.1007/978-3-030-16187-3_59

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