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Brief description

Public health is increasingly reliant on digital tools to enhance decision-making and manage health crises. This course explores the role of AI-based clinical decision support systems (CDSS) in modern healthcare, addressing the growing complexity of medical data and the need for automated solutions. CDSS augment clinicians by improving diagnostics, treatment adherence, and cost efficiency. The module aims to: (1) provide an overview of AI-driven decision tools in specialized medicine, (2) build trust in CDSS by highlighting their advantages over traditional methods, (3) upskill doctors with the latest digital innovations, and (4) identify gaps in current practices to advance CDSS applications. Topics include diagnostics, alarm systems, disease management, and cost containment, supported by case studies like antibiotic CDSS.

Target

Clinical and non-clinical staff

Objectives

• Identify the state of the art, in evidence-based decision tools for public health.
• Identify and list what decision tools could be applied to the participant professional context.
• Understand a CDSS.
• Analyse practical situations where CDSS can be implemented.
• Implement ML-based tools in CDSS.
• Carry out an implementation plan of a CDSS in a health system.

Duration

42h

Courses

These are the courses included in the pathway. To earn the pathway certificate, make sure you complete each one listed below. You can access the courses by clicking the buttons below.

4.14 Evidence based decision tools for public health
4.6 Automated decision support in healthcare and clinical settings

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Once you have completed the required courses, you will be able to download the pathway certificate from this section.

Pathways certificates