ArticleClinics and practice2025
Impact of an Artificial Intelligence-Guided Pulmonary Embolism Response Team (AIPERT) on Patient Transfers, Diagnosis, and Management: A Healthcare System Experience.
Article in Clinics and practice, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundPulmonary embolism (PE) is a time-sensitive condition with variable clinical presentations and outcomes. Rapid risk stratification and appropriate triage are essential for optimizing treatment and patient outcomes. Artificial intelligence (AI) offers an opportunity to enhance clinical decision-making, yet its real-world applications remain limited.
objectiveThe objective of this study was to describe a single healthcare system's implementation and early experience with an AI-enabled triage tool for pulmonary embolism patients across a multi-hospital network.
methodsThis retrospective observational study evaluated the deployment of an AI-based clinical decision support system within a healthcare network. The AI tool detected PE and right ventricular (RV) strain and alerted the PE response team (PERT) to facilitate timely transfer and intervention. Three cohorts were evaluated: pre-AI, Year 1 post-AI, and Year 2 post-AI. Outcomes included transfer volumes, advanced therapy rates, and hospital length of stay (LOS).
resultsA total of 183 PE transfer patients were analyzed: 36 pre-AI, 72 in Year 1 post-AI, and 75 in Year 2 post-AI. Transfers increased by 100% in Year 1 (
conclusionsImplementation of an AI-assisted triage platform for PE was associated with sustained increases in interhospital transfers and advanced interventions, and a reduction in hospital length of stay. These findings support the potential for AI to standardize and expedite acute PE care in a multi-hospital health system.
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