Aim and scope
This project aims to develop decision support for resource estimation and allocation, mainly but not exclusively, for the secondary care at the hospital. The general approach is to explore automatic methods that can predict and analyse future (healthcare) demand for resource allocation problems. The aim of this general approach is to reduce underestimation and overestimation of demand and further to develop decision support for specified resource allocation problems.
Initially, we are going to explore various data sources and the corresponding treatment and efficiency outcome in terms of patient processes/paths. The motivation behind this method is that the exploration may lead to the discovery of treatment indicators, that is, patterns in the various systems such as patient records and similar, that indicate the suitability and impact for various forms of treatment and/or treatment path. Medical researchers use the method to manually establish formal treatment indicators that help healthcare professionals in determining the most appropriate form of treatment or treatment path to directly improve the quality and efficiency of care. In contrast, we will explore the automatic execution of the method to discover treatment indicators that improve the estimation accuracy of future demand. In combination with simulation and optimization modelling technique, various types of decision support systems will be developed.
The data mining approaches to patient demand estimation will be evaluated in collaboration with researches from sub-project 4. The decision support system will be developed and validated in collaboration with industrial partners and specialists at one of our associated hospitals (located in Karlskrona and Stockholm)