Fit2Drive: Screening Older Drivers with Cognitive Concerns.

ABSTRACT

OBJECTIVES: The purpose of this study was to identify the most parsimonious combination of cognitive tests that accurately predicts the likelihood of passing an on-road driving evaluation in order to develop a screening measure that can be administered as an in-office test. DESIGN: This was a psychometric study of the new test's diagnostic accuracy. SETTINGS AND PARTICIPANTS: The study was conducted at the Florida Atlantic University's Memory Center and Clinical Research Unit, both easily accessible to older drivers. Participants were older drivers who received a driving evaluation at the Memory Center and agreed to have their results included in the Driving Repository and community-based older drivers who volunteered to participate. METHODS: Mini-Mental State Exam (MMSE), Trail Making Tests A and B, Clock Test, Hopkins Verbal Learning Test, and Driving Health Inventory results were compared with an on-road driving evaluation to identify those tests that best predict the ability to pass the on-road evaluation. RESULTS: Altogether, 412 older drivers, 179 men and 233 women, were included in the analysis. Fifty-four percent of Driving Repository participants failed the on-road evaluation compared with 8% of the community sample. The highest correlation to the on-road evaluation was Trails B time in seconds r = -0.713 (P < .001). Variables with high multicollinearity and/or low correlation with the on-road evaluation were eliminated and sets of receiver operating characteristics curves were generated to assess the predictive accuracy of the remaining tests. A linear combination of Trails B in seconds and MMSE using the highest of the Serial 7s or WORLD spelled backward scores accounted for the highest area under the curve of 0.915. Finally, an algorithm was created to rapidly generate the prediction for an individual patient. CONCLUSIONS AND IMPLICATIONS The Fit2Drive algorithm demonstrated a strong 91.5% predictive accuracy. Usefulness in office-based patient consultations is promising but remains to be rigorously tested.