Validation of the Candrive Older Driver Risk Stratification Tool for Assessing Medical Fitness-to-Drive in Older Australian Drivers.

Abstract

Background: Assessing older drivers' fitness-to-drive (FTD) is challenging, with decisions impacting mobility and health. This study aimed to validate the Candrive older driver risk stratification tool (RST) for screening medical FTD in an independent cohort of older adults from the Ozcandrive 8-year prospective study.

Methods: A convenience sample of drivers aged 75 and older residing in Melbourne, Australia completed the Candrive assessments. Their vehicles were instrumented to collect vehicle and Global Positioning System (GPS) data, including trip distance. The first four years of Ozcandrive data were analysed. The primary outcome measure was self-reported at-fault collisions, adjusted per 10,000 kilometers driven. Collision risk status was modelled using Generalized Estimating Equations with Poisson regression using predetermined Candrive RST predictor variables.

Results: A total of 257 older drivers (70.8% male) were recruited with an average age at study enrollment of 79.7 years (Standard Deviation (SD) = 3.5). Of the 755 adjusted person-years of driving, 74.1% were in the Low risk category (vs. original sample, Candrive: 74.8%) and 10.5% were in the Low-Medium risk category (Candrive: 9.3%). Only 15.4% were in the Medium-High risk category (Candrive: 15.9%), where the relative risk for self-reported at-fault collisions was 1.79 (95% confidence interval [CI]= 1.06-3.03) compared to the Low risk category.

Conclusions: This study demonstrates an association between self-reported at-fault collisions and Candrive RST scores. This result is promising given the primary outcome measure differed from the original Candrive study that used police-reported, at-fault collisions, and supports Candrive RST's use by healthcare providers when initiating FTD conversations.