Medically At-Risk Drivers Evidence-Based Decisions.

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Presentation transcript:

Medically At-Risk Drivers Evidence-Based Decisions

Change of Focus: Older Drivers vs. Medically At-Risk Drivers In 2008 WA introduced new laws requiring the Mandatory Reporting of Medical Conditions. All drivers with a long term medical condition that has the potential to impair driving ability must notify the licensing department.

Crash Involvement Rate Driver Age Group Rate of MVAs per Kilometre Driven Sources: COTA National Seniors, ACT (2004) Cerrelli, E. (1989) Older Drivers: The Age Factor in Traffic Safety.

Australians Aged % have at least 1 chronic condition 50% have at least 2 chronic conditions Co-morbidities & poly- pharmacy are the norm Age - Illness Association Sources: ABS (2008); Freedman, Martin & Schoeni (2002)

Increased At Fault Crash Risk At Fault Crash Risk By Diagnosis Source: Diller, E et al. (1998)

Prevalence of Cognitive Impairment Source: *(CSHA, 1991) 1 in 4 people over 65 years have cognitive impairment

Diagnosis Inadequate For Fitness To Drive Decisions eg. In the early stages of dementia: 2/3 will be unsafe to drive but1/3 remain safe to drive Revoking licence based on diagnosis alone is discriminatory to those who are still safe But... how do you best determine at what point someone becomes unsafe?

This publication is intended for use by any health professional involved in assessing fitness to drive, including: Medical Practitioners (GPs & Specialists) Occupational Therapists Physiotherapists Psychologists Optometrists

EPISODIC (eg. MI, Epilepsy, Hypoglycaemia) PERSISTENT (eg. Head injury, dementia) No question about driving ability when an event occurs Assessment question is “likelihood of the event” Assessment Issue: Judgement about the risk level Science unlikely Consensus guidelines = Suggested best practice No question about likelihood of event - it is ongoing Assessment question is “competence of the driver” Assessment Issue: Measurable outcome impairment Evidence based driving evaluations = best practice Categories of Medical Conditions

S.I.M.A.R.D. S creen for I dentifying M edically A t - R isk D rivers D.C.A.T. D riveABLE C ognitive A ssessment T ool D.O.R.E. D riveABLE O n- R oad E valuation DriveABLE ™

Assesses the time between the appearance of a visual stimulus in an unpredictable location & driver’s response. Shifting of attention, response speed, and accurate movements are involved in task performance. Measures: Reaction time Motor speed Movement Accuracy Motor Speed and Control

Driving requires an ability to attend to the road ahead while simultaneously responding to events occurring in the periphery. Measures: Ability to maintain focus on centrally presented items; While simultaneous identifying peripheral visual stimulus Span of Attentional Field

Turns, merges, & crossing traffic are associated with high crash rates Difficult for cognitively impaired drivers due to impaired judgement & decision making Complex task requiring speed, gap & acceleration judgments Measures: Spatial judgement Response time Collision rate Spatial Judgement & Decision Making

Assesses how quickly the driver can shift focus of attention from one stimulus to another. Measures: Time to respond when attention is Correctly focused Inappropriately focused Left unfocused Disengagement of attention Speed of Attentional Shifting

Higher cognitive function related to our ability to organise, plan, prioritise, manage & make decisions. Evaluates how well driver can hold information in working memory while responding to other stimuli. Executive Function

Series of short videos of real driving scenes The driver makes decisions about each driving scenario Provides information about the driver’s interpretation of road situations Measure: Ability to identify hazardous situations & take appropriate action Identification of Driving Situations

DriveABLE On Road Evaluation Specifically designed to identify the errors known to be related to competence decline Protects those drivers who remain competent from being unfairly penalised

Validation Field Testing Accuracy of predicting Road Test Results Road Test Results In Office Pass Fail Predict Pass 30%3% In-determinant 25%18% Predict Fail 2%21% 51% Pass/Fail Identified *Florida 5% Error Rate 43% Needed road test to resolve competence 95% Accuracy