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Enhancing emergency department safety, efficacy and cost-effectiveness by artificial intelligence

CORDIS · observation · Publication date unknown

Enhancing emergency department safety, efficacy and cost-effectiveness by artificial intelligence * Background: Emergency care costs are increasing in developed societies, both in rates of emergency department (ED) visits per person and in costs per visit, and are growing faster than other areas of healthcare spending. With limited and unstructured data, ED staff make quick decisions about probabilities for multiple diagnoses and risks. Both underestimation and overestimation of these probabilities lead to increased costs and patient harm. Hence, there is desperate need for clinical decision-support systems in the ED. * Aim: To develop a clinical decision support system for emergency medicine doctors, using sensor data, health records data and patient-reported data, validated in a randomized clinical trial, in order to improve the safety, efficacy and cost-effectiveness of emergency care. * Objectives: We will: Develop machine learning (ML)-powered diagnos

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recordType

award

status

SIGNED

region

EU

value

2497200

unit

EUR