Studies in health technology and informatics · 2025
It's All About Specific Features: Development of Prediction Models for Key Geriatric Risks Across Three Hospital Providers.
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Gutheil Julian, Stampfer Philip, Kramer Diether, Schrempf Michael, Jauk Stefanie, Veeranki Sai Pavan Kumar, Mrak Peter, Pinter Georg, Feichtner Franz
Аннотация
BACKGROUND: Managing geriatric risks is challenging, as early detection of conditions like delirium, frailty, dysphagia, falls, and malnutrition relies on time-intensive manual assessments requiring geriatric expertise. ML approaches can support healthcare professionals by enabling automated risk prediction using electronic health records (EHR) data, but existing models often lack geriatric-specific features.
OBJECTIVES: This study examines whether incorporating geriatric-specific features improves EHR-based prediction models for key geriatric risks and whether a one-shot Federated Learning (FL) approach enhances performance.
METHODS: EHR data from three hospital providers were linked with acute geriatric data to develop and compare three model types: (1) a baseline model using only EHR data, (2) a model incorporating geriatric-specific features, and (3) a FL ensemble.
RESULTS: Inclusion of geriatric-specific features significantly improved model performance, while a one-shot FL approach provided only marginal, non-significant additional benefit.
CONCLUSION: Geriatric-specific features are essential for capturing the complexity of the acute geriatric population.
OBJECTIVES: This study examines whether incorporating geriatric-specific features improves EHR-based prediction models for key geriatric risks and whether a one-shot Federated Learning (FL) approach enhances performance.
METHODS: EHR data from three hospital providers were linked with acute geriatric data to develop and compare three model types: (1) a baseline model using only EHR data, (2) a model incorporating geriatric-specific features, and (3) a FL ensemble.
RESULTS: Inclusion of geriatric-specific features significantly improved model performance, while a one-shot FL approach provided only marginal, non-significant additional benefit.
CONCLUSION: Geriatric-specific features are essential for capturing the complexity of the acute geriatric population.