Predictive risk modelling under different data access scenarios: who is identified as high risk and for how long?

ABSTRACT:

Objective

This observational study critically explored the performance of different predictive risk models simulating three data access scenarios, comparing: (1) sociodemographic and clinical profiles; (2) consistency in high-risk designation across models; and (3) persistence of high-risk status over time.

Methods

Cross-sectional health survey data (2006–2009) for more than 260 000 Australian adults 45+ years were linked to longitudinal individual hospital, primary care, pharmacy and mortality data. Three risk models predicting acute emergency hospitalisations were explored, simulating conditions where data are accessed through primary care practice management systems, or through hospital-based electronic records, or through a hypothetical ‘full’ model using a wider arra

SUBMITTER: Johnson T 

PROVIDER: S-EPMC5855362 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature