Automated decision support in healthcare and clinical settings

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WARNING Please be aware that the content on this page is currently under construction and is not finalized. The information presented here is provisional and subject to change.

DESCRIPTION

More and more the healthcare complexity demands automated decision-supporting systems leveraging the information included in the EHR. Computerized clinical decision support systems, or CDSS, represent a paradigm shift in healthcare today. CDSS are used to augment clinicians in their complex decision-making processes (Sutton, et al., Digital Medicine 3:17, 2020). The main aim of this module is (I) to provide an overview on the main decision support tools based on AI, that can be applied in specialized medicine, (ii) building trust on CDSS explaining the benefits compared with low-tech or no-tech methods (iii) up-skilling specialized doctors with latest innovative and digital advances regarding their discipline (iii) brainstorming the adaptation of the current methods applied to the CDSS to identify in a practical way the gaps and contribute to the advances.

THE MODULE WILL INCLUDE

Overview on the main functions provided by CDSS including diagnostics, alarm systems, disease management, prescription, drug control. A set of case studies will be developed (e.g. antibiotic CDSS).
Clinical management based on CDSS: adherence to clinical guidelines, follow-up and treatment reminders
Cost containment with CDSS: reducing test and order duplication, suggesting treatment options, automatization of tedious steps to reduce the workload and support personnel shortage
Diagnostic support based on CDSS: providing diagnostic suggestions based on patient data, automatic outputs from test results (e.g., imaging, laboratory and pathology augmenting the extraction visualization and interpretation of medical images and laboratory results).

TRAINING METHODOLOGIES

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TARGETED TO

Specialized Medical Doctors and their assistants (To be defined)
Laboratory staff and personnel

SPEAKERS

JANE DOE, EH4FUTURE PROJECT COORDINATOR

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