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Fig. 2 | Patient Safety in Surgery

Fig. 2

From: The role of big data management, data registries, and machine learning algorithms for optimizing safe definitive surgery in trauma: a review

Fig. 2

Example for the IBM Watson Health TRAUMA explorer, developed according to a data base of 3650 patients. The IBM Watson Health TRAUMA explorer can have access to the hospital data base system. Explanation: Level A: On the left side, the patient status can be assessed and the background of underlying patients can be selected (geriatric versus young). Then the surgical tactic can be selected and the system will provide information about the outcome seen in the selected patient group. Level B: The underlying patient population can be changed according to the expectations, such as age range, ISS range etc. This will determine the initial data of the pathway. Level C (visualization and Sankey diagram): According to different treatment options (resuscitation, surgical strategy etc.), the outcome can vary. Currently, the options for endpoints have been set to mortality, Sepsis and SIRS

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Patient Safety in Surgery

ISSN: 1754-9493