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Case Reports
. 2011 Mar 9;305(10):1018-26.
doi: 10.1001/jama.2011.252. Epub 2011 Mar 1.

Impaired driving from medical conditions: a 70-year-old man trying to decide if he should continue driving

Matthew Rizzo  1
Affiliations
Case Reports

Impaired driving from medical conditions: a 70-year-old man trying to decide if he should continue driving

Matthew Rizzo. JAMA. .

Abstract

Some medical disorders can impair performance, increasing the risk of driving safety errors that can lead to vehicle crashes. The causal pathway often involves a concatenation of factors or events, some of which can be prevented or controlled. Effective interventions can operate before, during, or after a crash occurs at the levels of driver capacity, vehicle and road design, and public policy. A variety of systemic, neurological, psychiatric, and developmental disorders put drivers at potential increased risk of a car crash in the short or long term. Medical diagnosis and age alone are usually insufficient criteria for determining fitness to drive. Strategies are needed for determining what types and levels of reduced function provide a threshold for disqualification in drivers with medical disorders. Evidence of decreased mileage, self-restriction to driving in certain situations, collisions, moving violations, aggressive driving, sleepiness, alcohol abuse, metabolic disorders, and multiple medications may trigger considerations of driver safety. A general framework for evaluating driver fitness relies on a functional evaluation of multiple domains (cognitive, motor, perceptual, and psychiatric) that are important for safe driving and can be applied across many disorders, including conditions that have rarely been studied with respect to driving, and in patients with multiple conditions and medications. Neurocognitive tests, driving simulation, and road tests provide complementary sources of evidence to evaluate driver safety. No single test is sufficient to determine who should drive and who should not.

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Figures

Figure
Figure
Information Processing Model for Understanding Errors That May Lead to Vehicle Crashes in Drivers With Medical Disorders
See this image and copyright information in PMC

References

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