Computer-automated dementia screening using a touch-tone telephone.
BACKGROUND
This study investigated the sensitivity and specificity of a computer-automated telephone system to evaluate cognitive impairment in elderly callers to identify signs of early dementia.


METHODS
The Clinical Dementia Rating Scale was used to assess 155 subjects aged 56 to 93 years (n = 74, 27, 42, and 12, with a Clinical Dementia Rating Scale score of 0, 0.5, 1, and 2, respectively). These subjects performed a battery of tests administered by an interactive voice response system using standard Touch-Tone telephones. Seventy-four collateral informants also completed an interactive voice response version of the Symptoms of Dementia Screener.


RESULTS
Sixteen cognitively impaired subjects were unable to complete the telephone call. Performances on 6 of 8 tasks were significantly influenced by Clinical Dementia Rating Scale status. The mean (SD) call length was 12 minutes 27 seconds (2 minutes 32 seconds). A subsample (n = 116) was analyzed using machine-learning methods, producing a scoring algorithm that combined performances across 4 tasks. Results indicated a potential sensitivity of 82.0% and specificity of 85.5%. The scoring model generalized to a validation subsample (n = 39), producing 85.0% sensitivity and 78.9% specificity. The kappa agreement between predicted and actual group membership was 0.64 (P<.001). Of the 16 subjects unable to complete the call, 11 provided sufficient information to permit us to classify them as impaired. Standard scoring of the interactive voice response-administered Symptoms of Dementia Screener (completed by informants) produced a screening sensitivity of 63.5% and 100% specificity. A lower criterion found a 90.4% sensitivity, without lowering specificity.


CONCLUSIONS
Computer-automated telephone screening for early dementia using either informant or direct assessment is feasible. Such systems could provide wide-scale, cost-effective screening, education, and referral services to patients and caregivers.
Mundt
J C
JC
Healthcare Technology Systems Inc, 7617 Mineral Point Rd, Suite 300, Madison, WI 53717, USA. Mundj@healthtechsys.com
Ferber
K L
KL
Rizzo
M
M
Greist
J H
JH
D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001185:Artificial Intelligence; D003362:Cost-Benefit Analysis; D003663:Decision Trees; D003704:Dementia / Q000145:classification / Q000175:diagnosis*; D003936:Diagnosis, Computer-Assisted / Q000191:economics / Q000295:instrumentation / Q000379:methods* / Q000592:standards*; D016002:Discriminant Analysis; D005240:Feasibility Studies; D015577:Geriatric Assessment; D006801:Humans; D008403:Mass Screening / Q000191:economics / Q000295:instrumentation / Q000379:methods* / Q000592:standards*; D008609:Mental Status Schedule; D008875:Middle Aged; D015233:Models, Statistical; D011569:Psychiatric Status Rating Scales / Q000592:standards*; D012017:Referral and Consultation; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index; D013685:Telecommunications / Q000191:economics / Q000592:standards*; D013689:Telephone / Q000191:economics / Q000592:standards*