Key result
Novel risk pathways, pre-hospital devices, and AI can improve acute chest pain care efficiency.
Why the study?
Existing assessment pathways for acute chest pain are often resource-intensive, prolonged, and expensive.
Improving the speed and accuracy of chest pain diagnosis and management through novel care models is likely to translate to substantive benefits for patients and health systems.
May streamline acute chest pain evaluation; leaves open whether novel pathways improve outcomes or reduce costs in practice.
Existing assessment pathways for acute chest pain are often resource-intensive, prolonged, and expensive. In this review, the authors describe existing chest pain pathways and current issues at the patient and system level, and provide an overview of recent advances in chest pain research that could inform improved outcomes for both patients and health systems. There are multiple avenues to improve existing models of chest pain care, including novel risk stratification pathways incorporating highly sensitive point-of-care troponin assays; new devices available before first medical contact that could allow clinicians to access vital signs and electrocardiogram data; artificial intelligence and precision medicine tools that may guide indications for further testing; and strategies to improve hospital benchmarking and performance monitoring to standardize care. Improving the speed and accuracy of chest pain diagnosis and management should be a priority for researchers and is likely to translate to substantive benefits for patients and health systems.
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Dawson et al. (2022) conducted a review in Acute chest pain. Novel care models and pathways was evaluated. Novel risk stratification pathways, pre-hospital devices, and artificial intelligence tools offer multiple avenues to improve the speed, accuracy, and efficiency of acute chest pain care models.
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