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 estimates. Many existing methods rely on structured electronic health record data which may limit generalizability …

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 patients at high risk of near-term death are likely to benefit from such interventions. As NYU Langone Health …

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. There remains sparse transparent reporting of model generalizability in different subpopulations especially for …

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 experiments to quantify the effects of experimental design choices, namely cohort selection and internal …

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.