Improving event prediction using general practitioner clinical judgement in a digital risk stratification model: a pilot study.

ABSTRACT:

Background

Numerous tools based on electronic health record (EHR) data that predict risk of unscheduled care and mortality exist. These are often criticised due to lack of external validation, potential for low predictive ability and the use of thresholds that can lead to large numbers being escalated for assessment that would not have an adverse outcome leading to unsuccessful active case management. Evidence supports the importance of clinical judgement in risk prediction particularly when ruling out disease. The aim of this pilot study was to explore performance analysis of a digitally driven risk stratification model combined with GP clinical judgement to identify patients with escalating urgent care and mortality events.

Methods

Clinically risk stratified cohort study o

SUBMITTER: Parry E 

PROVIDER: S-EPMC11654091 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature