Predicting Individual Risk of Emergency Hospital Admissions - A Retrospective Validation Study.

Purpose: A high number of hospital admissions may indicate poor general health and less than optimal health care across sectors. To prevent hospital admissions, previous studies have focused on predicting readmissions relating to a defined index admission and specific condition, whereas generic models suited for community-dwelling persons are lacking. The aim of this study was to validate a generic model that predicted risk of emergency hospital admission within the following three months and to investigate regional variation.

Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients.

Patients with severe COVID-19 have overwhelmed healthcare systems worldwide. We hypothesized that machine learning (ML) models could be used to predict risks at different stages of management and thereby provide insights into drivers and prognostic markers of disease progression and death. From a cohort of approx.