Operationalizing a Real-Time Scoring Model to Predict Fall Risk among Older Adults in the Emergency Department.
Frontiers in digital health(2022)
摘要
Predictive models are increasingly being developed and implemented to improve patient care across a variety of clinical scenarios. While a body of literature exists on the development of models using existing data, less focus has been placed on practical operationalization of these models for deployment in real-time production environments. This case-study describes challenges and barriers identified and overcome in such an operationalization for a model aimed at predicting risk of outpatient falls after Emergency Department (ED) visits among older adults. Based on our experience, we provide general principles for translating an EHR-based predictive model from research and reporting environments into real-time operation.
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关键词
falls prevention,EHR,risk stratification,machine learning,AI,precision medicine
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