@article{ref1,
title="Operationalizing a real-time scoring model to predict fall risk among older adults in the emergency department",
journal="Frontiers in digital health",
year="2022",
author="Engstrom, Collin J. and Adelaine, Sabrina and Liao, Frank and Jacobsohn, Gwen Costa and Patterson, Brian W.",
volume="4",
number="",
pages="e958663-e958663",
abstract="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.<p /> <p>Language: en</p>",
language="en",
issn="2673-253X",
doi="10.3389/fdgth.2022.958663",
url="http://dx.doi.org/10.3389/fdgth.2022.958663"
}