All Outputs (2)

Developing an electronic Surprise Question to predict end-of-life prognosis in a prospective cohort study of acute hospital admissions (2025)
Journal Article
Singh, B., Kumari-Dewat, N., Ryder, A., Klaire, V., Jennens, H., Ahmed, K., …Parry, E. (2025). Developing an electronic Surprise Question to predict end-of-life prognosis in a prospective cohort study of acute hospital admissions. Clinical Medicine, Article 100292. https://doi.org/10.1016/j.clinme.2025.100292

Objective
Determining the accuracy of a method calculating the Gold Standards Framework Surprise Question (GSFSQ) equivalent end-of-life prognosis amongst hospital inpatients.
Design
A prospective cohort study with regression calculated 1-year mor... Read More about Developing an electronic Surprise Question to predict end-of-life prognosis in a prospective cohort study of acute hospital admissions.

A prediction algorithm to improve the accuracy of the Gold Standard Framework Surprise Question end-of-life prognostic categories in an acute hospital admission cohort-controlled study. The Proactive Risk-Based and Data-Driven Assessment of Patients at the End of Life (PRADA) (2023)
Other
Singh, B., Kumari-Dewat, N., Ryder, A., Klaire, V., Bennion, G., Jennens, H., …Parry, E. (2023). A prediction algorithm to improve the accuracy of the Gold Standard Framework Surprise Question end-of-life prognostic categories in an acute hospital admission cohort-controlled study. The Proactive Risk-Based and Data-Driven Assessment of Patients at the End of Life (PRADA). [preprint]

Objective To determine the accuracy of a clinical data algorithm allocated end-of-life prognosis amongst hospital inpatients.

Method The model allocated a predicted Gold Standard Framework end-of-life prognosis to all acute medical patients admitt... Read More about A prediction algorithm to improve the accuracy of the Gold Standard Framework Surprise Question end-of-life prognostic categories in an acute hospital admission cohort-controlled study. The Proactive Risk-Based and Data-Driven Assessment of Patients at the End of Life (PRADA).