Office-Based Assessment of At-Risk Driving in Older Adults With and Without Cognitive Impairment

Stern, Robert; Abularach, Linda M.; Seichepine, Daniel R.; Alosco, Michael L.; Gavett, Brandon E.; Tripodis, Yorghos

doi:10.1177/0891988716666378

Cited by 17 publications

(39 citation statements)

References 48 publications

(66 reference statements)

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“…Other types of dementia, beyond AD, for example, dementia from cerebrovascular disease, Parkinson disease dementia, Lewy body dementia, and frontotemporal dementia have less predictable impacts on driving ability [ 8 , 25 - 28 ]. In-office tests have limited ability to predict crashes and on-road test failures in dementia [ 29 - 31 ]. Composite measures of attention, visuospatial skills, global cognition, and especially executive dysfunction are associated with crashes and on-road test failures in part [ 29 , 31 ], but misclassification rates are high and cutoff scores are lacking, limiting their clinical utility [ 30 ].…”

Section: Introductionmentioning

confidence: 99%

Computer-Based Driving in Dementia Decision Tool With Mail Support: Cluster Randomized Controlled Trial

Rapoport¹,

Sarracini²,

Kiss³

et al. 2018

J Med Internet Res

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BackgroundPhysicians often find significant challenges in assessing automobile driving in persons with mild cognitive impairment and mild dementia and deciding when to report to transportation administrators. Care must be taken to balance the safety of patients and other road users with potential negative effects of issuing such reports.ObjectiveThe aim of this study was to assess whether a computer-based Driving in Dementia Decision Tool (DD-DT) increased appropriate reporting of patients with mild dementia or mild cognitive impairment to transportation administrators.MethodsThe study used a parallel-group cluster nonblinded randomized controlled trial design to test a multifaceted knowledge translation intervention. The intervention included a computer-based decision support system activated by the physician-user, which provides a recommendation about whether to report patients with mild dementia or mild cognitive impairment to transportation administrators, based on an algorithm derived from earlier work. The intervention also included a mailed educational package and Web-based specialized reporting forms. Specialists and family physicians with expertise in dementia or care of the elderly were stratified by sex and randomized to either use the DD-DT or a control version of the tool that required identical data input as the intervention group, but instead generated a generic reminder about the reporting legislation in Ontario, Canada. The trial ran from September 9, 2014 to January 29, 2016, and the primary outcome was the number of reports made to the transportation administrators concordant with the algorithm.ResultsA total of 69 participating physicians were randomized, and 36 of these used the DD-DT; 20 of the 35 randomized to the intervention group used DD-DT with 114 patients, and 16 of the 34 randomized to the control group used it with 103 patients. The proportion of all assessed patients reported to the transportation administrators concordant with recommendation did not differ between the intervention and the control groups (50% vs 49%; Z=−0.19, P=.85). Two variables predicted algorithm-based reporting—caregiver concern (odds ratio [OR]=5.8, 95% CI 2.5-13.6, P<.001) and abnormal clock drawing (OR 6.1, 95% CI 3.1-11.8, P<.001).ConclusionsOn the basis of this quantitative analysis, in-office abnormal clock drawing and expressions of concern about driving from caregivers substantially influenced physicians to report patients with mild dementia or mild cognitive impairment to transportation administrators, but the DD-DT tool itself did not increase such reports among these expert physicians.Trial RegistrationClinicalTrials.gov NCT02036099; https://clinicaltrials.gov/ct2/show/NCT02036099 (Archived by WebCite at http://www.webcitation.org/6zGMF1ky8)

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Section: Introductionmentioning

confidence: 99%

Computer-Based Driving in Dementia Decision Tool With Mail Support: Cluster Randomized Controlled Trial

Rapoport¹,

Sarracini²,

Kiss³

et al. 2018

J Med Internet Res

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“…The in‐office screening tools that GPs report using most often in Australia include the Montreal Cognitive Assessment, the Mini‐Mental State Examination, the clock‐drawing test, and the Trails Making Test . However, despite their widespread use in clinical practice, single screening tests do not reliably predict driving risk . A toolkit comprising a composite battery of tests correlates better than any single test with the on‐road driving assessment …”

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confidence: 99%

“…However, despite their widespread use in clinical practice, single screening tests do not reliably predict driving risk . A toolkit comprising a composite battery of tests correlates better than any single test with the on‐road driving assessment …”

mentioning

confidence: 99%

“…Several toolkits have been developed and tested internationally, but their uptake in general practice has been limited, sometimes by the need for special equipment or input from family members . To be feasible in the Australian general practice context, any toolkit would need to be easy and quick to administer and require no expensive equipment or special training.…”

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confidence: 99%

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Assessing fitness to drive in older people: the need for an evidence‐based toolkit in general practice

Wallis

Matthews²,

Spurling

2020

Medical Journal of Australia

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“…The scores from several assessments are often cross-referenced to make a decision, which is ultimately based on the professional judgment of the primary-care physician [26]. This screening process is often considered to lack evidence-based information [11].…”

Section: In-office Medical Assessmentsmentioning

confidence: 99%

Characterization of Stable-Health Older Drivers Using Low-Speed Driving Maneuvers From In-Vehicle Sensor Data

Fung¹

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The Candrive study aims to improve the current practices of screening elderly drivers in Canada by identifying predictors of motor vehicle collisions from monitoring their daily driving behaviours using in-vehicle sensors. The thesis objective was to characterize the baseline behaviour of stable-health older drivers by proposing parameters of interest for detecting changes in behaviour and methods to differentiate drivers using their maneuvers. The in-vehicle sensor data from 12 stable-health drivers were processed, and a turn-identification algorithm with 97.7% accuracy was created for extracting four maneuvers: accelerating from stop, decelerating to stop, right turns, and left turns on 40 to 60 km/h roadways. Most of the drivers exhibited relatively steady month-to-month acceleration behaviours and lower accelerations in adverse driving conditions, which represented their typical driving behaviours. Drivers can be differentiated by the driving patterns from their maneuvers using a multi-expert classifier, which may be applicable for detecting changes in driving behaviour.iii Acknowledgements I would like to first thank my advisors, Dr.

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Office-Based Assessment of At-Risk Driving in Older Adults With and Without Cognitive Impairment

Abstract: Future research on larger and more clinically representative neurological samples will improve understanding of the utility of the UFOV Divided Attention and NAB Driving Scenes in detecting at-risk older adult drivers in the clinic.

Cited by 17 publications

References 48 publications

Computer-Based Driving in Dementia Decision Tool With Mail Support: Cluster Randomized Controlled Trial

Computer-Based Driving in Dementia Decision Tool With Mail Support: Cluster Randomized Controlled Trial

Assessing fitness to drive in older people: the need for an evidence‐based toolkit in general practice

Characterization of Stable-Health Older Drivers Using Low-Speed Driving Maneuvers From In-Vehicle Sensor Data

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