End-of-life

Expanding the Reach of Structured EHR Data with Clinical Notes: Improving End-of-Life Prediction
Appropriate treatment decisions and end-of-life planning for patients with serious, life-limiting disease rely on accurate prognosis …
Seda Bilaloglu, Vincent J. Major, Himanshu Grover, Isabel Metzger, Yindalon Aphinyanaphongs
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Supporting Acute Advance Care Planning with Precise, Timely Mortality Risk Predictions
Patients with serious, life-limiting disease benefit from end-of-life conversations, goal setting, and palliative care. Hospitalized …
Erwin Wang, Vincent J. Major, Nicole Adler, Kevin Hauck, Jonathan Austrian, Yindalon Aphinyanaphongs, Leora Horwitz
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Development, Implementation, and Prospective Validation of a Model to Predict 60-Day End-of-Life in Hospitalized Adults Upon Admission at Three Sites
Background: Automated systems that use machine learning to estimate a patient’s risk of death are being developed to influence care. …
Vincent J. Major, Yindalon Aphinyanaphongs
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Estimating Real World Performance of a Predictive Model: A Case-Study in Predicting End-of-Life
Objective: One primary consideration when developing predictive models is downstream effects on future model performance. We conduct …
Vincent J. Major, Neil Jethani, Yindalon Aphinyanaphongs
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Challenges in Translating Mortality Risk to the Point of Care
An invited Editorial discussing a recent work implementing a relatively simple method to identify patients at risk of 1-year mortality and prompting the care team to consider a goals-of-care discussion or consulting Palliative Care.
Vincent J. Major, Yindalon Aphinyanaphongs
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