September/October 2016

Fit2drive: New App Predicts On-Road Driving Ability in Patients With Dementia
By Ruth M. Tappen, EdD, RN, FAAN; Jamie Zahava Ramos, BA; David O. Newman, PhD; and Matt Newman, BA
Today's Geriatric Medicine
Vol. 9 No. 5 P. 12

To assess driving fitness in patients with dementia, researchers have developed an app that predicts on-road driving skills using the results of two well-known cognitive tests.

It is well known that Alzheimer's disease and related chronic progressive dementias place affected individuals at risk for unsafe driving but also eventually leave impaired individuals unable to drive. For the large number of adults who depend upon their personal automobiles for transportation, driving cessation has a profound impact on their functional independence, self-esteem, mood, social life, ability to participate in community activities, and ability to obtain everyday necessities and needed services.1 It is no surprise then that some patients and their families have described the driving issue as "the biggest problem we've ever had to face"2 and that physicians and other primary care providers are often called upon for advice related to driving cessation.

While individuals with dementia are more likely than unimpaired older adults to be found to be unsafe drivers and to evidence more rapid decline in driving performance, there is considerable evidence that patients in the earliest stages of dementia may be able to continue driving for some time. For example, data from two longitudinal studies comparing drivers in the early stages of dementia with unimpaired drivers indicated that 88% of those with very mild impairment (having a Clinical Dementia Rating [CDR] scale score of 0.5) and 69% of those with mild impairment (a CDR score of 1) are able to pass a standardized road test. Follow-up testing found that adequate driving ability continued for a median two years for those with a CDR score of 0.5 and for one year for those with a CDR of 1.3-5

Driver Assessment
When patients and their families first realize that progressive cognitive impairment will eventually impair driving enough to make it unsafe, they often find it difficult to weigh personal safety and the safety of others against the significant losses that accompany driving cessation. This is the point at which many consult with their primary care providers about driving. If a patient does not stop driving, both the patient and family are likely to reach a crisis point where they are confronted with the obvious and increasing dangers of continued driving and serious conflicts arising from the feared losses related to driving cessation.

According to the recent (third) edition of the Clinician's Guide to Assessing and Counseling Older Drivers (http://geriatricscareonline.org/ProductAbstract/clinician's-guide-to-assessing-and-counseling-older-drivers/B022),6 a driver evaluation plan begins with a screening phase in which a patient's physical and cognitive capabilities are reviewed. Noncognitive factors that may affect driving include chronic medical conditions, impaired ambulation, sleep disorders (leading to falling asleep at the wheel), acute illness or recent surgical procedures (affecting short-term fitness to drive), behavior disorders and substance abuse, neurological conditions, medications (causing drowsiness, dizziness, and confusion particularly), and visual acuity.7

The Clinical Assessment of Driving Related Skills found in the Clinician's Guide includes visual field deficits; visual acuity; rapid pace walk; strength and range of motion of the neck, shoulders, elbows, fingers, and ankles; ability to complete a maze test; Montreal Cognitive Assessment; Trail-Making Test Part B (longer than 180 seconds suggests referral for comprehensive evaluation); and the clock drawing test. Additionally, there is a set of self-evaluation questions (Have you ever gotten lost while driving? Had any accidents? Had others criticize your driving?) that are useful in interviewing patients8 contained in the Driving and Dementia Toolkit, also available online (www.rgpeo.com/media/30422/d%20%20d%20toolkit%20pt%20crgvr%20eng%20with%20
hyperlinks.pdf). Even at the screening phase, these evaluations require a significant time investment. Our estimate is that administration of the Mini-Mental State Examination (MMSE) and Trail-Making Test, Part B needed to obtain a Fit2Drive prediction—by way of a cutting-edge app to be explained in this article—would require approximately 15 minutes and can be done by well-trained assistive personnel.

The second stage involves treatment of any medical conditions identified and a comprehensive driver evaluation, usually conducted by a driving specialist, including in-office and standardized on-road testing similar to the evaluation described in the next section. The outcome may be a finding that the patient is fit to drive with or without restriction, needs rehabilitation or recovery before returning to driving, or needs to stop driving.6

Development of Fit2Drive
To create the patent-pending Fit2Drive Calculator, the authors first collected data on driver testing results at the Louis and Anne Green Memory and Wellness Center, a memory center located on the Florida Atlantic University campus that offers a diagnostic clinic, a dementia-specific day care, family support groups, individual counseling, and driver testing. The driving evaluation involved in-office testing of cognition, using the MMSE, clock drawing test, Trails A and Trails B, and the Driving Health Inventory, including motor and visual ability assessing leg strength, head-neck and upper body flexibility, high and low contrast visual acuity, visual search, and visual information processing speed. The on-the-road test was a behind-the-wheel assessment using the DriveABLE On-Road Evaluation (DORE) customized for the Memory and Wellness Center. Patients who presented for driver evaluation were asked for their consent to obtain their driving test results for research purposes in accordance with procedures approved by the University Committee for the Protection of Human Subjects.

Tests Used
MMSE
The MMSE is a widely used tool to assess a range of cognitive functions. It consists of a 30-point questionnaire categorized into five subscales: Orientation to Time—5 points; Orientation to Place—5 points; Registration (repeating three words after the examiner)—3 points; Attention and Calculation (counting backward from 100 by sevens)—5 points; Recall of the earlier three words—3 points; and Language (naming, 3-stage command, reading and carrying out a command, writing a sentence, and copying a figure)—9 points.9,10

A score below 19 was classified by the developers as impaired, a score between 19 and 23 was classified as borderline impairment, and a score between 23 and 30 was classified as normal.9 More recently, the Alzheimer's Association (2016) suggests that a score of 20 to 24 is indicative of mild dementia, 13 to 20 of moderate dementia, 12 and less of severe dementia.11 It has been generally thought that individuals who score less than 24 on an MMSE have an increased risk of having an automobile accident.12,13 However, if an individual scores in the borderline or impaired range, this does not mean they can be assumed to be entirely unfit to drive, as this measure was designed to determine cognitive impairment but not driving skills.

Trail-Making Test, Part B
The Trail-Making Test is used to assess reaction time and executive function and has also been considered a potential tool for assessing driving fitness. It was developed in 1944 during World War II as part of the Army Individual Test Battery and later adapted for civilian use as a neuropsychological test of executive functioning, processing speed, and visual attention.14-17 Part A consists of a connect-the-dots task with 25 numbers.18 Individuals are instructed to connect the numbers in sequence as quickly and accurately as possible. Part B involves a second more complex connect-the-dots task in which individuals must alternate the 25 numbered dots sequentially with 25 letters (1, A, 2, B, 3, C, etc).18 They are instructed to connect the sequence of numbers and letters as quickly as possible with the greatest accuracy. Results are scored as the number of seconds taken to complete the task.

In a study of more than 500 adults, the reported mean time to complete Trails B in control subjects was 81.5 compared with 136 for individuals with mild cognitive impairment and 140 for individuals with Alzheimer's disease.19 The average age in this group was 72.4, which was lower than in our sample.

DORE
The DORE is a proprietary driving test designed specifically for individuals with cognitive concerns.20 It differs in several ways from the typical new driver test used by states to issue driver licenses. New drivers are expected to be able to perform basic maneuvers and understand the laws regarding driving, while on-the-road driving assessments for individuals with cognitive difficulties focus on behaviors indicative of cognitive impairment, such as drifting into another lane or difficulty making a left turn. The DORE course used in this study was customized for the Memory and Wellness Center at Florida Atlantic University and directs participants to follow a designated route through the surrounding Boca Raton community.

The test takes place in a dual-brake vehicle provided for participants. It is scored on several components, including risks of a collision/accident rating, driver rating, and the driving course difficulty level. There is no penalty for the errors or bad driving habits that are typical of unimpaired drivers. Upon completion, the scores are coded, and a coding sheet is transmitted to DriveABLE. Results are based on a proprietary computer algorithm21 and presented as a score within the range of normal safe driving, which is scored as a pass; a score within the upper range of normal-competent driving, which receives a borderline pass; or a score outside the range of normal-competent driving, which is considered a fail.

Study Sample
Altogether complete driver test information was available for 329 patients. Of these, 39 received a borderline pass on the on-the-road test and were dropped from the analyses, leaving results on testing of 290 patients for this analysis; 171 (59%) were men, and 119 (41%) were women. Their ages ranged from 50 to 97, with an average age of 81. Their average MMSE score was 23, with a very wide range from 4 to 30. The average Trails B time in seconds was 76, with a range from 54 to 300. The majority (80%) had been referred for testing by a physician, 35 (12%) by the courts or notice from the Department of Motor Vehicles, and 7 (2.5%) had participated voluntarily. Approximately one-half reported that they had received a diagnosis of Alzheimer's disease, Parkinson's disease, or a related dementia; the remainder did not report a diagnosis.

Analysis
The authors' goal in conducting the data analysis was to identify the smallest number of test results that could predict a patient's likelihood of passing the on-road driver evaluation. To do this, we entered the in-office test results into a logistic regression using pass or fail on the on-the-road test as the outcome on which the potential predictor variables were regressed. We tried a number of combinations, finding that the MMSE and Trails B time in seconds accounted for the highest proportion of unique variance in the predictive model with only minimal additional increase in predictive strength contributed by additional test scores.

Based upon the relative predictive strength of the various in-office test scores, the MMSE and Trails B time in seconds were selected for our Fit2Drive Calculator. Since there were two predictors in this model, a second logistic regression analysis was run with these predictors to determine the overall predictive weight of both the MMSE and the Trails B. These weights became the basis of the prediction equation. The binary pass-fail outcome allows the predictive model to assess the sensitivity (ie, a true positive) and specificity (ie, a true negative) of the predictive outcomes compared with the on-road test. From these results, a contingency table can be created from the four possible outcomes (true positive, false positive, true negative, and false negative). The overall combination of the sensitivity and specificity is then graphed (called a receiver operating characteristic curve, which plots true positives against true negatives on the tests of interest) and the area under the curve provides an estimate of the overall accuracy of our predictors. For this analysis, the overall accuracy was 75%.

If we printed a table with every possible combination of the MMSE score and Trails B time, the table would be 176 pages long and very clumsy to use during a patient consultation. To provide quick access to these predictions, we developed a calculator, Fit2Drive, based on an equation derived from our data. When a patient's MMSE and Trails B time scores are entered, the calculator provides the probability the patient will pass an on-road driving evaluation.

Integrating Fit2Drive Into the Screening Stage of Driver Evaluation
The Fit2Drive calculator is designed to assist the primary care provider or geriatrician in making the decision to refer the patient for Stage 2 Comprehensive Evaluation. In primary care or geriatric care settings, use of Fit2Drive is appropriate if a patient is driving but either the patient, family member, or provider has concerns about the patient's continued fitness to drive. The driving interview questions mentioned earlier may be useful in gauging the level of concern as would the provider's observation and clinical examination (See Figure 1).

The Fit2Drive calculator utilizes the total score from the original MMSE9 and Trails B time in seconds (Trails A should be administered first to provide the same amount of practice that the patients in the research study had prior to completing Trails B). A technician may be trained to administer these tests, but an untrained person may not obtain comparable results. The two scores are entered online or into the mobile app to obtain a prediction of the likelihood that the patient would pass the on-road driving test.

Using the Fit2Drive Calculator
The Fit2Drive Calculator can be accessed via the Fit2Drive website at http://Fit2Drive.us. Select "F2Drive Calculator" to bring up the dialogue box. Enter the individual's age and gender (for tracking purposes), total MMSE score and Trails B time in seconds (the maximum time allowed is 300 seconds). Click on the submit button and the probability that the individual will pass an on-road driving test is displayed immediately. For example, if a patient has an MMSE score of 27 and took 70 seconds to complete the Trails B test, the likelihood of passing a standardized on-the-road driving test would be 0.67 (67%). Alternatively, the provider can download the app from the website to an Android or iOS mobile device and enter the data on a smart phone.

Limitations
The patients whose records were accessed were primarily of European American heritage. Only a small number of Hispanic and black patients participated. There is a possibility that, given the age and education bias that has been found in the use of the MMSE in members of minority groups, the calculator may be affected by these biases and should be interpreted cautiously with members of these groups until further research is done. Another caution is the use of the calculator in patients without Alzheimer's disease or a related dementia. Because only a few patients in our sample were unimpaired, the calculator developed from their data is less accurate at higher levels of function. The calculator's results should be used in conjunction with the provider's clinical examination and patient and caregiver report. It is intended to be an adjunct to the provider's clinical judgment, not a substitute for it.

Summary
Fit2Drive is an evidence-based system for prediction of the likelihood of passing an on-road driver evaluation developed for use with older adults who have some evidence of mild cognitive impairment, Alzheimer's disease, or a related dementia. It is designed to be an adjunct to providers' observations and physical examinations during the screening stage of driver evaluation. Fit2Drive may be accessed at www.fit2drive.us.

— Ruth M. Tappen, EdD, RN, FAAN, is a professor and eminent scholar in the Christine E. Lynn College of Nursing at Florida Atlantic University (FAU) in Boca Raton. She was the founder of the Memory and Wellness Center at FAU and has conducted a number of funded studies on Alzheimer's disease and related dementias.

— Jamie Zahava Ramos, BA, is a graduate student in the department of psychology at FAU.

— David O. Newman, PhD, is a biostatistician at the College of Nursing at FAU. He developed the predictor equation discussed in this article.

— Matt Newman, BA, is president and CEO of SolveIT Consulting, Inc, which created the Fit2Drive website.

References
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