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Development of a Clinical Decision Support System in Intensive Care.
BACKGROUND: Intensive care is confronted with an increasing complexity and large amounts of data provided by new technological tools. One way of assisting health care professionals is providing effective clinical decision support (CDS) systems.
OBJECTIVES: The aim is to develop a tailored model for the sustainable development of a clinical decision support system in intensive care.
METHODS: The model consists of two parts. The first part includes the interaction of the following partners: science industry and HCP. The second part comprises a three-phase process consisting of (1) the identification of clinical needs, (2) modeling and prototyping, and (3) implementation.
RESULTS: By July 2015, a government funded CDS development project started in Graz, Austria. After assigning a multi-professional and interdisciplinary team, a clinical need statement was formulated within the first six months. A prototype was developed by end of 2016 and verified using a clinical dataset.
CONCLUSION: The developed model proofed to be feasible regarding the first two phases. Additional progress needs to made to assess the performance of the model in the implementation phase.
OBJECTIVES: The aim is to develop a tailored model for the sustainable development of a clinical decision support system in intensive care.
METHODS: The model consists of two parts. The first part includes the interaction of the following partners: science industry and HCP. The second part comprises a three-phase process consisting of (1) the identification of clinical needs, (2) modeling and prototyping, and (3) implementation.
RESULTS: By July 2015, a government funded CDS development project started in Graz, Austria. After assigning a multi-professional and interdisciplinary team, a clinical need statement was formulated within the first six months. A prototype was developed by end of 2016 and verified using a clinical dataset.
CONCLUSION: The developed model proofed to be feasible regarding the first two phases. Additional progress needs to made to assess the performance of the model in the implementation phase.
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