JOURNAL ARTICLE
RESEARCH SUPPORT, NON-U.S. GOV'T
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Using the community health assessment to screen for continued driving.

This project used the interRAI based, community health assessment (CHA) to develop a model for identifying current elder drivers whose driving behavior should be reviewed. The assessments were completed by independent housing sites in COLLAGE, a non-profit, national senior housing consortium. Secondary analysis of data drawn from older adults in COLLAGE sites in the United States was conducted using a baseline assessment with 8042 subjects and an annual follow-up assessment with 3840 subjects. Logistic regression was used to develop a Driving Review Index (DRI) based on the most useful items from among the many measures available in the CHA assessment. Thirteen items were identified by the logistic regression to predict drivers whose driving behavior was questioned by others. In particular, three variables reference compromised decision-making abilities: general daily decisions, a recent decline in ability to make daily decisions, and ability to manage medications. Two additional measures assess cognitive status: short-term memory problem and a diagnosis of non-Alzheimers dementia. Functional measures reflect restrictions and general frailty, including receiving help in transportation, use of a locomotion appliance, having an unsteady gait, fatigue, and not going out on most days. The final three clinical measures reflect compromised vision, little interest or pleasure in things normally enjoyed, and diarrhea. The DRI focuses the review process on drivers with multiple cognitive and functional problems, including a significant segment of potentially troubled drivers who had not yet been publicly identified by others. There is a need for simple and quickly identified screening tools to identify those older adults whose driving should be reviewed. The DRI, based on the interRAI CHA, fills this void. Assessment at the individual level needs to be part of the backdrop of science as society seeks to target policy to identify high risk drivers instead of simply age-based testing.

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