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Computer-Automated Dementia Screening Using a Touch-Tone Telephone
James C. Mundt, PhD;
Kae L. Ferber, MD;
Matthew Rizzo, MD;
John H. Greist, MD
Arch Intern Med. 2001;161:2481-2487.
ABSTRACT
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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  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.
INTRODUCTION
ALZHEIMER DISEASE (AD) is the most common cause of dementia for elderly
patients. Years may pass following symptomatic onset before diagnosis,1 and current treatments may slow but will not reverse
the progressive cognitive decline.2 Earlier
detection and recognition of dementia would permit more effective use of available
treatments, better opportunity to educate patients and families, and time
to develop social support systems and implement important financial and legal
plans.3 Key to early detection and recognition
of AD are effective systems for patient screening. Screening approaches to
identify cognitive impairment in the elderly have included direct patient
evaluation4-5 and collateral informant
questionnaires.6-9
Both approaches are effective for accurately identifying unrecognized dementia
in patients. However, large community screening efforts to identify persons
for diagnostic evaluation are time consuming and resource intensive.
Interactive voice response (IVR) systems integrate telecommunications
networks with computer-automated processing. Programs using IVR systems have
become commonplace in society for automated call routing and access to banking
records, airline schedules, and local theater listings. Health care delivery
and monitoring systems have increasingly used IVR systems across a range of
problems from psychiatric and behavioral disorders (such as depression, anxiety,
obsessive-compulsive disorder, and substance abuse10-13)
to hypertension monitoring.14 Such systems
have been successfully implemented to monitor the functional status of community-residing
elders enrolled in home care programs.15
Generally, IVR systems have been used simply to collect self-reported
data using computer-automated questionnaires. Complex branching logic permits
context-dependent interactions, allowing effective delivery of IVR-mediated
educational and behavioral treatment programs.16-17
The rapid growth in computer-based assessment of individual skills and abilities
that occurred throughout the 1980s and 1990s (eg, Psychological Assessment
Resources Inc, Odessa, Fla; The Psychological Corp, San Antonio, Tex) has
not been paralleled by IVR developments. Telephone-based cognitive screening
by nurses with geriatric training has distinguished elderly subjects with
cognitive impairment from those without.18
The feasibility of using IVR technology to objectively assess psychological
and psychomotor functioning has been demonstrated previously19-20;
however, such research has been scant. The present study investigated whether
an IVR application could be developed to objectively evaluate the cognitive
abilities of elderly callers with sufficient sensitivity to distinguish early
dementia from cognitively intact "normal" elders.
PARTICIPANTS AND METHODS
PARTICIPANTS
For our study, 155 subjects were recruited from both a geriatrics practice
affiliated with the Dean Medical Center, Madison, Wis (n = 91), and from ongoing
research at the Department of Neurology, University of Iowa, Iowa City (n
= 64). Geriatric patients with normal cognition and/or a diagnosis of mild
dementia who scheduled appointments with the Dean Medical Center were invited
to participate. Research subjects from the University of Iowa were recruited
from a memory disorders clinic and from a federally funded mobility study
of elderly licensed drivers. Informed consent was obtained from all participants
in accordance with required federal and institutional guidelines. Study participants
were not compensated for participation. Subjects ranged in age from 56 to
93 years (mean [SD], 76.7 [7.0] years) with 6 to 22 years of education (mean
[SD], 13.3 [3.0] years; 13.5% had not graduated high school, 51.0% graduated
high school, 22.6% had 2- or 4-year college degrees, and 12.9% had earned
graduate degrees). The sample included 98 women and 57 men; 61.3% were married,
31.0% widowed, 5.2% divorced, and 2.6% never married. In addition to the 155
subjects participating directly in the testing procedures, collateral informants
accompanied 74 subjects to their appointment (46 spouses, 27 children or grandchildren,
and 1 other). During a separate, independent telephone call to the system,
these informants completed an IVR-administered Symptoms of Dementia Screener
(SDS).9 The SDS is an 11-item checklist of
dementia symptoms often noted by family members and caregivers prior to detection,
evaluation, and diagnosis by medical staff. Previous research9
using telephone interviewers suggested that positive endorsement of 5 or more
symptoms by an informant is associated with risk of dementia. This research
is the first attempt to apply this screener with IVR technology.
Each subject was given a Mini-Mental State Examination (MMSE),4 and a trained clinician provided ratings for the Clinical
Dementia Rating Scale (CDRS).21-22
The CDRS obtains an impairment rating for each of 6 functional areas: memory,
orientation, judgment and problem solving, community affairs, home and hobbies,
and personal care. Clinical ratings in each area are anchored to explicit
descriptions of patient symptoms and functional difficulties, resulting in
impairment rating values of 0 (none), 0.5 (questionable), 1 (mild), 2 (moderate),
or 3 (severe). Scoring for the CDRS considers impairment ratings across all
6 areas using memory impairment ratings as the primary index and ratings of
impairment in the other domains as secondary indexes.22
The resulting CDRS scores are used to stage dementia levels. A score of 0
indicates no cognitive impairment; 0.5, uncertain or deferred diagnosis; 1,
mild stage of dementia; 2, moderate stage of dementia, and 3 to 5, profound
or terminal dementia. In the present study, 74 (47.7%) of the subjects had
a CDRS score of 0; 27 (17.4%), a score of 0.5; 42 (27.1%), a score of 1; and
12 (7.7%), a score of 2. None of the study participants had a CDRS score of
3 to 5.
APPARATUS
The screening procedures were designed and programmed using a Conversant
MAP40 IVR server (Lucent Technologies, Murray Hill, NJ) maintained by Healthcare
Technology Systems, Inc (Madison, Wis). The tasks were programmed as separable
testing modules, and instructions were provided by the IVR system prior to
each task. All responses were collected using standard Touch-Tone telephones.
Evaluative feedback regarding task performance (ie, correct or incorrect)
was not provided.
TEST MODULES
- Subjective Memory Complaint. Subjects
were asked if they often had difficulty remembering names of family or friends,
finding words or where objects had been left, or used notes to avoid forgetting.
Subjects giving positive responses were asked to rate the severity of problems
such difficulties caused (none, small, moderate, serious).
- Orientation. Subjects responded to 5
questions pertaining to their orientation in time. They were asked to enter
(1) the 4 digits of the current year; (2) the current season; (3) the current
month; (4) the current day of the month; and (5) the current day of the week.
Responses were scored as correct or incorrect and totaled to pro duce a score
of 0 to 5.
- Alphabetic Translation. Subjects were
asked to use the letters printed on the telephone keys to spell the word "FUN"
(3-8-6) and given the context as in "The party was fun" to assure comprehension.
A score of 0 to 3 reflected the number of correctly sequenced key presses.
- Immediate Recall. Subjects heard the
digit sequence "2-7-6-0-4" and were asked to enter these digits in the same
order. This procedure was repeated 3 times. Each trial was scored 0 to 5 based
on the number of correctly sequenced key presses and then totaled to produce
a score of 0 to 15.
- Directed Key Pressing. Subjects were
directed to press particular keys a specific number of times (eg, "Press the
‘7' key 3 times" "Press 6 times on the ‘3' key"). Subsequent stimuli
were presented after a 2-second delay without a key press. Performance continued
until 30 seconds had elapsed since the start of the task. Each series of key
presses was scored as correct or incorrect and totaled to produce a score
of 0 to 5.
- Delayed Recall. Following the directed
key-press task, the subjects were asked to recall the 5-digit sequence of
the immediate recall trials. The score (0-5) reflected the number of correctly
ordered key presses.
- Auditory Spatial Relations. Subjects
heard an auditory description of key locations (1-9) according to the standard
3 x 3 matrix on most telephones (top row, 1-3; middle row, 4-6; and
third row, 7-9) and were asked to press the identified key. For example, the
"top-left" key corresponds to the "1" key; the "right-bottom" key would be
the "9" key. Presentation of the next descriptor was prompted by any key press
or proceeded after a 3-second delay without a response. Total task duration
was 30 seconds, and the score (0-9) reflected the number of correct key presses
made.
- Backward Digit Span. On 3 successive
trials, subjects heard a 4-digit sequence of numbers (different sequence each
trial) and asked to press the identified keys in reverse order. Trials were
scored with respect to the number of correctly sequenced key presses (0-4)
and were then totaled to produce a score of 0 to 12.
- Semantic Comprehension. Subjects heard
6 declarative statements and were asked to judge whether each statement made
sense or not. Three statements made sense (eg, "The woman burned herself badly
when she spilled a pot of hot soup on herself while preparing dinner"), and
3 did not (eg, "We wanted to cut down a tree in our front yard, so we went
to the garage to get our hammers"). The mean (SD) length of the statements
was 24 (3.9) words (range, 18-30) with a Flesch-Kincaid grade level of 6.5
(range, 3.7-8.6). Responses were scored for accuracy and were totaled to a
score of 0 to 6.
PROCEDURES
Subjects were provided with a Touch-Tone telephone and quiet space from
which to make the call from the study site clinics. Study staff provided each
subject with a unique 4-digit identification number to enter at the beginning
of the call as well as the toll-free number to dial. Research staff provided
verbal assistance in dialing the number and entering the identification number
(ID) if needed, but no further assistance in responding to the IVR system
was provided. All instructions for completing the IVR tasks were provided
by the IVR system at the time the data were collected. After call completion,
subjects rated the overall difficulty of the testing procedures and each specific
task on a 1 to 5 scale (very easy to very difficult). Feedback was also obtained
regarding the clarity of the instructions and whether the task requirements
were understood. Paper-based forms labeled by the ID of the subject contained
the demographic information, MMSE and CDRS scores, collateral informant ID,
and patient feedback and were forwarded to Healthcare Technology Systems Inc
for integration with the IVR performance data.
When collateral informants were available to participate, they were
removed from the vicinity of the subjects while the testing call was completed.
They were not permitted to provide assistance, nor were they given knowledge
of the subjects' performance. The collateral informants completed the SDS
during a separate telephone call outside the presence of the subject. Each
collateral informant was given a unique ID that allowed the IVR to branch
to the SDS delivery module and allowed the data collected to be linked to
the ID of the target subject.
RESULTS
Including reference to Table 1, Figure 1 shows the data collection procedures
and analysis plan. The figure accurately depicts data collection from study
subjects and informants as 2 separate calls at different times from different
locations. Both calls were placed to the same telephone number and processed
by one IVR system (ID was used to identify the appropriate IVR script to apply).
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Individual Task Performance Scores Stratified by CDRS Score for All
Subjects Who Completed the Testing Call*
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Figure 1. Data collection and processing
flow. Schematic diagram of data collection and analysis. Separate data collection
paths for computer-automated cognitive assessments and informant's completion
of the Symptoms of Dementia Screener (SDS) accurately reflect independent
telephone calls that were received and processed by one interactive voice
response (IVR) system or program.
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IVR TASK PERFORMANCE
Of 155 subjects participating in this study, 16 were unable to complete
the call and "hung up" on the system. These noncompleters ranged in age from
58 to 88 years with a mean MMSE score of 21.4 (range, 11-29). Five were moderately
demented, 9 were mildly demented, and 2 had questionable diagnoses based on
their CDRS scores. The median time to hang-up was 8 minutes 40 seconds. All
subjects without dementia (CDRS score, 0; n = 74) were able to complete the
call.
Table 1 gives the mean call
length and task performance scores for the 139 subjects completing the IVR
call, stratified by CDRS score. The mean (SD) time to complete the call was
12 minutes 27 seconds (2 minutes 32 seconds); subjects with greater cognitive
impairment required more time to complete the call. Task performances also
reflect the clinicians' ratings of impairment, evidenced by significant analyses
of variance on all tasks except the delayed recall (floor effect) and directed
key-press (ceiling effect) tasks. Generally, post hoc comparisons found that
the performances of subjects with mild to moderate dementia differed significantly
from subjects without dementia; the intermediate performances of subjects
with uncertain diagnoses (CDRS score, 0.5) did not differ from one or both
of these subject groups using protected Newman-Keuls comparisons.
The bottom of Figure 1 shows
how machine-learning methods were used to investigate whether combining performances
across tasks could differentiate unimpaired subjects (CDRS score, 0) from
cognitively impaired subjects (CDRS score,  0.5). Subjects were dichotomized
and randomly assigned to a model "development" sample (P = .75) or a "validation" sample (P = .25).
Random assignment was examined by comparing the mean age, education, and MMSE,
CDRS, and total IVR task scores between the samples. No statistically significant
differences were found.
Data from the development sample were analyzed using QUEST (Quick, Unbiased,
Efficient Statistical Tree)23 to extract performance
data that maximized subject group discrimination. This binary tree–growing
algorithm recursively partitions data into homogeneous subsets using a series
of hierarchical, single variable decisions that maximizes group separation.
Figure 2 shows the development
sample data and extracted decision criteria. The shape of terminal nodes indicates
predicted classification (impaired or unimpaired). Numerators in each box
indicate the number of correct classifications; denominators indicate the
total number of subjects characterized by the decision rules.
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Figure 2. Hierarchical classification model.
Implementation of derived hierarchical binary decision model. Terminal decision
node shape indicates model classification (cognitively impaired or unimpaired).
The denominator is the total number of subjects described by terminal node,
and the numerator is the number of subjects correctly classified in the model
development sample.
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Five of 8 terminal nodes resulted in a cognitively impaired classification.
Unless 1 of these circumstances was met, subjects were classified as unimpaired.
This model correctly classified 50 of 61 subjects with questionable, mild,
or moderate dementia (82.0% sensitivity) and 47 of 55 subjects with a CDRS
score of 0 (85.5% specificity) in the development sample. Positive and negative
predictive values were 0.862 and 0.810, respectively. Such methods, however,
use ad hoc statistical properties of the sample and clinical judgments to
generate the decisional models. Independent validation is needed to evaluate
generalizability.
The decision rules of Figure 2
were applied to the 39 subjects held out of the model development analysis.
Of 20 subjects with questionable, mild, or moderate dementia, 17 were predicted
to be cognitively impaired (85.0% sensitivity); 15 of 19 subjects with a CDRS
score of 0 were predicted not to be impaired (78.9% specificity). Prospective
positive and negative predictive values were 0.810 and 0.833. The
coefficient of agreement between the predicted and true group membership was
0.64 (P<.001).
The classification tree used call noncompletion to classify subjects
as cognitively impaired (100% specificity). However, in 13 of 16 hang-ups,
1 or more of the tasks were completed, of which 8 had an orientation score
of 3 or less; 2 produced scores less than 3 on the "spell FUN" task; and 1
provided immediate recall data that would result in classification as impaired,
regardless of sentence comprehension performance. Thus, of 16 subjects not
completing the call, 11 (69%) provided sufficient data to warrant classification
as impaired before hanging up.
In summary, when the derived scoring algorithm was applied to the complete
study sample of 155 patients, 62 (84%) of the 74 patients with a CDRS score
of 0 were classified as unimpaired. A positive screening result for cognitive
impairment was found in 17 (63%) of the 27 subjects with a CDRS score of 0.5,
38 (91%) of the 42 subjects with a score of 1, and all 12 subjects with a
CDRS score of 2.
SUBJECT PERCEPTIONS AND FEEDBACK
After completing the telephone call, subjects were asked for feedback
about the IVR calling experience. They were asked to rate the overall difficulty
of the telephone program and the difficulty of each of the tasks on a 5-point
scale from "very easy" to "very difficult" with 3 indicating "neither easy
nor difficult." Not all of the subjects provided complete ratings. A total
of 474 "task difficulty" ratings were provided by subjects with a CDRS score
of 0, with 85% of these ratings indicating the system was easy or very easy
to use, 8% indicating the system was neither easy nor difficult to use, and
7% indicating the system was difficult or very difficult. Subjects with CDRS
scores of 0.5 or greater provided 436 such ratings, with 76% of the ratings
being easy or very easy, 14% indicating the system was neither easy nor difficult,
and 10% indicating the system was difficult to very difficult to use. Almost
half (49%) of the difficult or very difficult ratings were given to the backward
digit span task and another 29% given to the delayed recall task. In general,
the subjects with CDRS scores of 0.5 or greater rated the tasks as more difficult
than those with CDRS scores of 0, but the mean rating for all of the tasks
for both groups was in the direction of easy to very easy. A total of 114
subjects answered a question about the clarity of task instructions provided
by the IVR, with 93.9% indicating that the instructions were clear and allowed
them to understand what they were supposed to do during the task.
IVR-ADMINISTERED INFORMANT SCREENING
Seventy-four collateral informants called the IVR system, entered an
ID linked to a target subject, and responded to the 11-item SDS. The mean
(SD) call length was 4 minutes 46 seconds (41 seconds). Of the 22 subjects
with a CDRS score of 0, 13 had an SDS score of 0, 4 had a score of 1, and
5 had a score of 2. Of the 52 subjects with questionable, mild, or moderate
dementia, 47 had an SDS score of 3 or greater. Standard scoring of the SDS
(5) produced a sensitivity of 63.5% and specificity of 100%. These data
suggest that using an SDS score of 3 or greater as a criterion might increase
sensitivity to 90.4% without reducing specificity.
Objective computer-automated cognitive screening using IVR technology
can discriminate between patients with early dementia symptoms and those without.
The derived scoring model produced sensitivity and specificity estimates of
roughly 80%. Application of the scoring model to data obtained from the validation
sample supports generalizable validity. Adequate discrimination between cognitively
impaired and unimpaired subjects did not require complete task performance,
and the most discriminative tasks were those judged as easiest to complete
by the subjects. This may partly reflect a sampling bias of impaired subjects
with a mean CDRS score very close to 1. These data also indicate that collateral
informants can use IVR technology to identify patients with early dementia
symptoms.
COMMENT
To maximize benefits of current treatments for dementia, particularly
for treatments of AD (which may only slow the symptomatic cognitive decline),
early detection and recognition is critical. Wide-scale screening, whether
through direct patient evaluation or collateral informants, poses significant
challenges for support of the necessary resources and logistics. This study
demonstrates that IVR technology could play an important role in reliably
identifying elderly patients beginning to manifest cognitive impairment suggestive
of early dementia. Patients aged well into their 80s or 90s and even those
with mild to moderate dementia can comprehend and navigate Touch-Tone interfaces
to complete computer-automated assessments. The 10.3% hang-up rate is higher
than desired; however, this problem can be reduced. Only 5 (3.2%) of the 155
subjects were unable to complete enough of the call to permit the application
of a decision criterion that would have accurately identified their cognitive
status. A total call length of about 12.5 minutes is not an excessive burden
for accurate dementia screening; removal of unnecessary tests and use of a
real-time scoring algorithm, terminating when a criterion for accurate classification
was met, would decrease call length, task demands, and loss to hang-ups. Of
the 148 subjects completing the call through just the orientation and spell
FUN tasks, 50 had already met the criteria for a cognitively impaired classification;
90% of these subjects had CDRS scores indicating questionable, mild, or moderate
dementia (only 10% represented false-positive screens). Such results need
to be replicated, but an accurate classification of a caller within the first
few minutes of a call offers the potential to provide immediate feedback,
education, and referral to local or national treatment resources.
In November 1999, public interest in a toll-free IVR system to provide
dementia education and resource referral information was examined during a
monthlong pilot study.24 Nearly 200 anonymous
calls were received from a predominantly rural Midwest county of about 100 000
persons. These callers accessed information about dementia prevalence, risk
factors, current treatment options, and local resources for treatment and
caregiver support. Roughly half of the callers were concerned for a parent
or grandparent and another 25% of the callers were concerned about themselves.
Dementia screening using IVR was not available at that time, pending results
from the present study.
The results obtained in this study must be viewed critically, pending
further research and replication. Many factors related to patient and hardware
variability will influence the reliability and validity of this type of telephone-automated
testing. Certainly, physical disabilities (eg, severe loss of hearing or vision
or disabling arthritis) or other neurological conditions directly influence
an individual's ability to understand task requirements and respond appropriately
to IVR applications. Such considerations limit universal application of this
approach to prospective patient screening, but most cognitively intact senior
citizens are familiar with and able to navigate the many IVR systems that
are increasingly being used by banking and government institutions, medical
clinics, airlines, and cinemas. The diversity of shapes, sizes, and features
available for telephone configurations rivals that of any other standard household
equipment. Such variability of hardware instrumentation influences data reliability.
This consideration was, in part, the reason that the tasks developed for this
research focused as much as possible on cognitive performance and deemphasized
psychomotor speed or response times. While all of the automated tasks incorporated
a "time out" interval to allow for nonresponsiveness, the intervals were at
least 3 seconds or longer, allowing some confidence that failure to respond
was more likely a result of mental confusion than slowed motor response. The
extent to which most of the subjects found the task demands in this study
to be relatively easy supports this speculation. Use of a standard office
telephone by all subjects at each of the study sites controlled for much of
this type of instrumentation error variance in the present study and should
be used for any future clinical or research use. The degree to which the use
of any Touch-Tone telephone across individuals and/or over time would influence
the reliability and validity of the type of data obtained by this system remains
to be investigated.
Live clinician telephone interviews demonstrate acceptable convergence
and reliability with face-to-face clinician assessment of behavioral and psychological
symptoms of dementia.25 Interactive voice response
technology has already been used for screening and diagnostic purposes in
other medical domains. Kobak and colleagues26
demonstrated the sensitivity and specificity of an IVR mental health screener
for identifying depressive and anxiety disorders, obsessive-compulsive disorders,
and eating and alcohol use disorders. The present study extends the utility
of this technology to dementia screening. Clearly, this type of computer-automated,
remote-access technology cannot directly obtain sufficient information to
permit differential diagnosis of different types of dementia. Such differentiation
requires a wider assessment of patient histories, personal risk factors, and
evaluation of medical tests by skilled clinicians. However, the sooner such
assessments are made following the onset of abnormal cognitive difficulties,
the greater the likelihood of obtaining maximum benefits from the appropriate
course of treatment. Interactive voice response technology has been effective
for providing patients with medical education from the comfort of their homes
through the convenience of the telephone,27
and Mahoney et al15 demonstrated that this
technology can effectively link community-residing elders with professional
health care providers.
In conclusion, the pieces for a computer-automated telephone system
that are able to provide integrated dementia screening, education, and treatment
referral and monitoring services presently exist. As more effective treatments
for AD and other dementias develop, economically efficient methods for identifying
those in need and connecting them to treatment providers will become increasingly
important in providing socially responsible and cost-effective care to the
elderly.
AUTHOR INFORMATION
Accepted for publication March 13, 2001.
This study was supported by grant 1R43AG16538 (Dr Greist) and grants
AG15071 and grants AG17177 (Dr Rizzo) from the National Institute on Aging,
Bethesda, Md.
Editorial comments provided by Warner V. Slack, MD, to a previous draft
of the manuscript were very helpful in improving manuscript content and presentation.
The assistance of Deborah A. Kaplan, Shelly Bierbaum, Robin Mitchell, and
Jory Wilke, RN, RD, during data collection is also acknowledged and appreciated.
Corresponding author and reprints: James C. Mundt, PhD, Healthcare
Technology Systems Inc, 7617 Mineral Point Rd, Suite 300, Madison, WI 53717
(e-mail: Mundj{at}healthtechsys.com).
From Healthcare Technology Systems Inc, Madison, Wis (Drs Mundt and
Greist); the Department of Internal Medicine, Geriatrics Section, Dean Medical
Center, Madison (Dr Ferber); and the Department of Neurology, University of
Iowa, Iowa City (Dr Rizzo). Dr Ferber is currently with Anchor Health Centers,
Naples, Fla.
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