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Achieving Value by Risk Stratification with Machine Learning Model or Clinical Risk Score in Acute Upper Gastrointestinal Bleeding: A Cost Minimization Analysis.
American Journal of Gastroenterology 2023 September 28
INTRODUCTION: We estimate the economic impact of applying risk assessment tools to identify very-low-risk patients with upper gastrointestinal bleeding (UGIB) who can be safely discharged from the emergency department using a cost minimization analysis.
METHODS: We compare triage strategies (Glasgow-Blatchford Score (GBS)=0/0-1 or validated machine-learning model) to usual care using a Markov chain model from a U.S. healthcare payer perspective.
RESULTS: Over 5 years, the GBS triage strategy produced national cumulative savings over usual care of over $2.7 billion, and the machine-learning strategy of over $3.4 billion.
CONCLUSION: Implementing risk assessment models for UGIB reduces costs, thereby increasing value.
METHODS: We compare triage strategies (Glasgow-Blatchford Score (GBS)=0/0-1 or validated machine-learning model) to usual care using a Markov chain model from a U.S. healthcare payer perspective.
RESULTS: Over 5 years, the GBS triage strategy produced national cumulative savings over usual care of over $2.7 billion, and the machine-learning strategy of over $3.4 billion.
CONCLUSION: Implementing risk assessment models for UGIB reduces costs, thereby increasing value.
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