A cost effectiveness_model_of_screening_strategies.16

ORIGINAL ARTICLE
A Cost-Effectiveness Model of Screening
Strategies for Amblyopia and Risk Factors and
Its Application in a German Setting
AFSCHIN GANDJOUR, MD, PhD, STEFANIE SCHLICHTHERLE, MD,
ANTJE NEUGEBAUER, MD, WALTER RÜSSMANN, MD, and
KARL WILHELM LAUTERBACH, MD, DSs
Institute of Health Economics and Clinical Epidemiology, University of Cologne, Cologne, Germany (AG, SS, KWL), Department of
Ophthalmology, University of Cologne, Cologne, Germany (AN, WR)
ABSTRACT: Purpose. To develop a general setting–independent decision-analytical model that determines the costs,
effectiveness, and cost-effectiveness of four screening strategies to detect amblyopia or amblyogenic factors in
pre-school children and to apply the model in a German setting. Methods. The general setting–independent decision–
analytical model was developed from the perspective of society and the statutory health insurance was developed.
Outcomes were the total number of newly detected true positive cases of amblyopia and the costs per newly detected
true positive case of amblyopia. Strategies were screening of high-risk children up to the age of 1 year (ophthalmol-
ogists), screening of all children up to the age of 1 year (ophthalmologists), screening of all children aged 3 to 4 years
(pediatricians or general practitioners), and screening of children aged 3 to 4 years visiting kindergarten (orthoptists).
For the application example in a German setting, data from the published medical literature were used. Results. In the
base-case analysis of the application example, screening high-risk children by opthalmologists had the lowest average
cost per case detected but became dominated (less effective and more costly than an alternative) if a low (5.3%)
probability of familial clustering of strabismus was assumed. Considering the various assumptions tested in the
sensitivity analysis, screening of all children up to the age of 1 year by opthalmologists was the only strategy not
dominated by others. Detection rates, including cases detected before screening, were between 72% and 78% for the
strategies that screen for all children. Conclusions. The model suggests that in Germany, both from a cost-effectiveness
and a pure effectiveness point of view, screening all children up to the age of 1 year by opthalmologists is the preferred
strategy to detect amblyopia or amblyogenic factors. All strategies left a significant portion of children undetected.
(Optom Vis Sci 2003;80:259–269)
Key Words: amblyopia, children, cost-effectiveness analysis, Germany, screening
A
mblyopia is defined as a unilateral or bilateral decrease in
visual acuity for which no cause can be found through the
physical examination of the eye.1
Risk factors associated
with amblyopia are anisometropia, hyperopia, and strabismus. The
prevalence rate of amblyopia among children aged 3 to 4 years is
between 1% and 5%, depending on the threshold value of visual
acuity.2
The prevalence rates of anisometropia, hyperopia, and
strabismus are 3.1%,3
5.5%,4
and 5.3%,5
respectively.
Pre-school screening for amblyopia is recommended by a large
number of professional societies and experts in the United States,
Canada, and Germany.2, 6–14
Recent evidence supports the expert
recommendations. A controlled trial comparing amblyopia screen-
ing and treatment before the age of 37 months with screening and
treatment at 37 months demonstrated the superiority of an early
approach.15
Similarly, a prospective cohort study on occlusion
therapy for amblyopia showed greater improvement in visual acu-
ity among children 5 years of age or younger.16
Still, the question remains as to whether screening for amblyopia
is economically attractive. The high prevalence rate of amblyopia
that leads to high costs of detection and treatment makes this
question economically relevant. In this regard, it is also important
to know whether alternative screening options that are currently
not recommended would be more economically attractive.
Screening by orthoptists has been shown to be effective in the
1040-5488/03/8003-0259/0 VOL. 80, NO. 3, PP. 259–269
OPTOMETRY AND VISION SCIENCE
Copyright © 2003 American Academy of Optometry
Optometry and Vision Science, Vol. 80, No. 3, March 2003

U.K.15, 17–21
Introducing screening for amblyogenic factors up to
the age of 1 year could be an alternative to screening for manifest
amblyopia between the ages of 3 and 4 years because the treatment
of amblyogenic factors is assumed to be shorter in duration.22
However, ophthalmologists*
would need to perform such a screen-
ing if pediatricians and orthoptists lacked the skill to perform the
appropriate tests up to the age of 2 (retinoscopy plus examination
of ocular media and fundus). Among strategies for screening for
amblyogenic factors, the screening of high-risk children, such as
premature infants and children with a familial predisposition for
amblyopia, could be particularly economically attractive due to the
low number of children that need to be screened to detect one
amblyopia case.
To the best of our knowledge Barry et al.,23
and König et al.,24
and König and Barry25
have performed the only economic evalu-
ations of amblyopia screening so far. These studies, however, used
different assumptions compared with our model and did not also
evaluate screening strategies for amblyogenic factors.
The goal of this article was to present a general setting–indepen-
dent decision-analytical model that permits determination of the
costs, effectiveness (total number of newly detected true-positive
amblyopias), and cost-effectiveness (costs per newly detected true-
positive amblyopia) of four screening strategies to detect amblyo-
pia or amblyogenic factors in pre-school children. In this article, we
stress factors and assumptions that are important to construct the
model. We then use a German setting as an application example.
In general, a decision-analytical model is able to overcome the
complexity of decision making by structuring the problem clearly.
Furthermore, it permits identification of parameters that have a
strong influence on results and thus may be candidates for future
research.
METHODS
Model Overview
Our model on the cost-effectiveness of screening for amblyopia
or amblyogenic factors compares the following strategies:
1. Screening of high-risk children up to the age of 1 year
(ophthalmologist).
2. Screening of all children up to the age of 1 year
(ophthalmologist).
3. Screening of all children aged 3 to 4 years (pediatrician or
general practitioner).
4. Screening of children aged 3 to 4 years visiting kindergarten
(orthoptist).
“No screening program” should be thought of as a further alter-
native; it may be difficult, however, to assess screening patterns in
a natural setting and associated costs. In addition, screening by
office staff may be considered as an alternative to screening by
pediatricians or general practitioners if adequate training can be
assumed. The same consideration holds for screening by nonoph-
thalmologists as an alternative to screening by ophthalmologists.
Screening up to the age of 1 year is directed to amblyogenic
factors including anisometropia (Ն1 D), strabismus, and high de-
grees of hyperopia (Ͼ3.5 D) because a meaningful vision test at
this age is afflicted by high uncertainty and because amblyopia
possibly has not yet developed. Screening between the ages of 3 and
4 years has the aim of detecting amblyopia, defined in our model as
a visual acuity of Յ0.63 decimal units (Յ20/32 Snellen units).
In the model, pediatricians, general practitioners, and orthop-
tists examine children using a visual acuity test, a stereo acuity test,
a cover test, and a Hirschberg test. Ophthalmologists, however,
perform the following diagnostic procedures at initial visits and for
referral patients: retinoscopy (after the application of cycloplegic
drops), cover test, Hirschberg test, and an examination of the
ocular media and fundus.
All children with abnormal results from screening performed by
a pediatrician, general practitioner, or orthoptist are referred to an
ophthalmologist. If these children are not confirmed to have am-
blyopia, they are not invited for a second visit to an ophthalmolo-
gist. Children who are mistakenly diagnosed by ophthalmologists
of having amblyopia (false-positive cases) are identified within 1
year after the initial diagnosis and after two additional visits to an
ophthalmologist. At their first visit to an ophthalmologist after the
initial diagnosis, false-positive cases receive a retinoscopy, a cover
test, a Hirschberg test, and an examination of the ocular media and
fundus. At their second visit, they have the same examinations
except the retinoscopy. Furthermore, they receive a pair of glasses
and daily patches (occlusion therapy) for 120 days.
Determining Cost-Effectiveness
Economic evaluations of the four approaches to screening are
conducted from a societal viewpoint because this perspective is the
most comprehensive, considering all direct and indirect costs, and
is also recommended by the U.S. Panel on Cost-Effectiveness in
Health and Medicine.26
Simultaneously, the economic evaluations
also take the perspective of a third-party payer because the third-
party payer covers the costs of the screening programs.
All economic evaluations are performed as cost-effectiveness
analyses. The time horizon is 1 year. The outcome measures are
newly detected true-positive cases of amblyopia requiring treat-
ment. Thus, for screening strategies up to the age of 1 year, only
cases that develop an amblyopia at a later point of time are consid-
ered. Measures such as life-years saved, quality of life, or quality-
adjusted life years were not used because data on the life expectancy
and the quality of life of treated and untreated patients are cur-
rently unavailable.
The four screening programs are compared using the incremen-
tal cost-effectiveness ratio. This ratio is defined as the additional
cost of a specific screening strategy divided by its additional clinical
benefit compared with the next less-expensive strategy. Screening
strategies that are less effective and more costly than an alternative
(dominated) and strategies with a higher cost-effectiveness ratio
than a more-effective alternative strategy (extended dominance)
are ruled out.26
Clinical and Epidemiological Data
Tables 1 to 4 list clinical and epidemiological parameters re-
quired for the model (all values provided in tables refer to the
application example described below). Adjustment of data on the
*
In the United States and other countries outside Germany optometrists may be
considered as an alternative to opthalmologists. In order for the model to accommodate
for optometrists, however, it might need some adjustments.
260 Cost-Effectiveness of Screening for Amblyopia—Gandjour et al.

sensitivity and specificity (accuracy) of the screening procedures
needs to be considered if there is a lack of data on the accuracy (1)
of a combination of the above tests and (2) of different examiners.
In addition, the model requires estimates or data on the propor-
tion of patients that have already been identified at the time of
screening as having amblyopia because of obvious squints and/or a
positive family history.
Important clinical, epidemiological, and cost data that are un-
available may be determined by a two-round modified Delphi
panel.38
The Delphi technique uses an iterative questionnaire to
measure consensus among individual responses. There is no inter-
action between responder and interviewer.
Cost Data
Cost parameters needed to construct the model are provided by
Table 5. All evaluations include direct medical and nonmedical
(transportation) costs. The societal viewpoint considers, in addi-
tion, the productivity losses and transportation costs of caregivers.
These incur when caregivers accompany children to and from a
physician’s office. The reason for including these costs is that a
societal viewpoint considers all costs nontrivial in magnitude.
In the model, productivity losses are assessed by the human
capital approach using the average labor cost of an employee as an
approximate measure. For determining the percentage of working
caregivers missing work, it is assumed that all caregivers are moth-
ers. The time cost of nonworking caregivers for accompanying
children to and from a physician’s office is estimated by the re-
placement cost approach.48
The follow-up costs for false-positive diagnoses are added to the
cost per true-positive case detected. Follow-up costs are not dis-
counted because they incur during the first year after the initial
diagnosis.
Sensitivity Analysis
A sensitivity analysis examines how results change when input data
are varied. Whereas a univariate sensitivity analysis alters the value of
one parameter at a time, a multivariate sensitivity analysis alters the
values of two or more parameters simultaneously. Our model uses a
Monte Carlo simulation, which is a type of multivariate sensitivity
analysis. This technique runs a large number of simulations by repeat-
edly drawing samples from probability distributions of input param-
eters. Thus, it derives a probability distribution for the results and
forecaststheprobabilitythatcertainstrategiesaredominated.Further-
more, it helps to identify parameters that have a strong association
TABLE 1.
Sensitivity and specificity stratified by age and type of examiner.a
Age
(yr)
Population Examiner Sensitivity (Range)
Specificity
(Range)
Ͻ1 High risk Ophthalmologist 0.95 (0.8–1.0) 0.95 (0.7–1.0)
Ͻ1 Non-high risk Ophthalmologist 0.95 (0.8–1.0) 0.95 (0.8–1.0)
3–4 Total Pediatrician/GPb
0.75 (0.5–0.9) 0.8 (0.7–0.9)
3–4 Total Orthoptist 0.9 (0.65–1.0) 0.9 (0.8–1.0)
3–4 Referrals from pediatricians/GP’s/orthoptists Ophthalmologist 0.95 (0.85–1.0) 0.95 (0.8–1.0)
a
All data were estimated.
b
GP, general practitioner.
TABLE 2.
Rates for participation, referral, and compliance.
Activity
Base-Case Rate
(Range)
Reference Source and Comments
High-risk children aged Ͻ1 yr
Participation in the recommended pediatric exam U6a
0.91 27 (1996 data)
Referral to an ophthalmologist 0.95 (0.9–1.0) Estimate
Compliance with referral 0.90 (0.8–1.0) Estimate
All children aged Ͻ1 yr
Participation in the recommended ophthalmologic exam 0.65 (0.5–0.85) Estimate combining the rates for participation
in the exam U6, ophthalmologic referral,
and compliance with referral
All children aged 3–4 yr
Participation in the screening program U8 0.80 27 (1996 data)
Participation of a child in the kindergarten screening
program
0.91 (0.85–0.97) 28, 29 (weighted average)
Referral to an ophthalmologist after positive eye exam 0.90 (0.8–1.0) Estimate
Compliance with referral 0.90 (0.8–1.0) Estimate
a
U6, Untersuchung 6, the sixth preventative health examination in a series of 10 preventive examinations carried out by
pediatricians and general practitioners for children from birth to 13 years of age.
Cost-Effectiveness of Screening for Amblyopia—Gandjour et al. 261

withtheaveragecostpercasedetected.Suchparameterscanbefurther
evaluated in a univariate sensitivity analysis as well as a worst-case and
best-case scenario. In the latter, all parameter values are set for worst
case and best case, respectively.
RESULTS
In this article, we provide an application example of the
model in a German setting. We focus on deviations from the
above model description and the specific requirements of the
German setting.
In this setting search for visual defects including strabismus and
refractive amblyopia is part of a series of 10 preventive examina-
tions carried out by pediatricians and general practitioners for chil-
dren from birth to 13 years of age. The program is funded by the
statutory health insurance.
Model Overview
The possibility of having no screening program was not consid-
ered as an alternative because of the difficulty of assessing screening
patterns in a natural setting and their associated costs. We did not
consider screening by office staff as an alternative to screening by
pediatricians or general practitioners because the office staff in
Germany is not qualified to perform the examinations. For the
same reason, we did not consider the possibility of optometrists as
an alternative to ophthalmologists.
In the model, all screenings took place at outpatient offices
(separate from hospitals in Germany) except for the screening con-
ducted in kindergartens by orthoptists.
Data Sources
We identified sources of data by searching MEDLINE for arti-
cles in English and German that were published up to February
2000. We handsearched review articles and book chapters for ad-
ditional sources. A panel of three ophthalmologists and one phy-
sician specializing in health economics estimated any data that
were unavailable in the literature.
The percentage of time during the U8 examination devoted to
amblyopia screening was determined by a two-round modified
Delphi panel38
because this figure had been assumed to be a major
driver of the cost of pediatric examinations. Twelve pediatricians
TABLE 4.
Miscellaneous data.
Parameter Base-Case Value (Range) Reference Source and Comments
Number of children aged 3–4 attending kindergarten 374,000 33 (1998 data)
Probability of patients with strabismus developing amblyopia 0.53 (0.42–0.64) 37
TABLE 3.
Data for calculating the number of children at high risk.
Parameter
Base-Case Value
(Range)
Reference Source and Comments
Hereditary risk factors for amblyopia
Prevalence rate of strabismus among children 0.052 (0.047–0.057) Weighted average from Graham,5
Haase et
al,30
and Kendall et al.31
Risk of strabismus if one parent or one sibling
is affected
0.176 (0.053–0.3) 32
Number of households with two children
below age 18
3,536,000 33 (1998 data)
Number of households with three children
below age 18
863,000 33 (1998 data)
Number of households with four children
below age 18
249,000 33 (1998 data)
Pre-term children (birthweight Ͻ1500 g)
Prevalence rate at birth 0.01 34 (1997 data)
Probability of anisometropia (Ն1 D) and/or
strabismus and/or hyperopia (Ͼ3.5 D)
0.233 (0.183–0.283) Estimated from the prevalence rate of
strabismus among pre-term children35
and
of anisometropia and hyperopia among all
children3, 4
First year mortality rate 0.176 (0.168–0.185) 34, 36 (1997 data)
Pre-term children (birthweight 1500–2500 g)
Prevalence rate at birth 0.052 34 (1997 data)
Probability of anisometropia and/or strabismus 0.15 (0.11–0.19) Estimate
First year mortality rate 0.014 (0.013–0.015) 34, 36 (1997 data)

performing a visual acuity test and a stereo acuity test participated
in the first round; eight thereof participated in the second round
with the opportunity to change their score in view of the group’s
response.
Data Analysis
We performed the analysis using Microsoft Excel 97 and Crystal
Ball 4.0 (Decisioneering, Denver, CO), an Excel add-in program
that performs Monte Carlo simulations.
Clinical and Epidemiological Data
Tables 1 to 4 list clinical and epidemiological data used in the
model. Ranges were defined as four standard errors of the mean or, if
unavailable, as reasonable estimates covering the complete distribution.
Ourestimatesonthesensitivityandspecificity(accuracy)ofthescreening
procedureswerebasedonpublisheddata.Thesedata,however,hadtobe
adjusted for our study due to a lack of data on the accuracy (1) of a
combination of the above tests and (2) of different examiners.
The size of the child population in different age groups was
TABLE 5.
Data for calculating costs.
Item
Base-Case Value
(Range)
Reference Source and
Comments
Direct costs
Total point score of one exam at an ophthalmologist (items 1,
1200, 1202, 1216, 1242)
456 39
Total point score of a complete U8 exam (pediatrician or GP)a
650 40
Point value €0.0422b
41
Percentage of time of the U8 exam devoted to amblyopia
screening
0.25 (0.18–0.29) Modified Delphi panel
Cost of one glasses lens (to the statutory health insurance) €12.02 42
Cost of one glasses lens (to society) €12.02 (10.00–12.02) The statutory health insurance
was assumed to reimburse the
wholesale price.
Cost of a glasses frame €25.00 (12.50–37.50) Estimate of the wholesale price
Daily cost of an eye patch €0.50 (0.40–0.60) Estimate of the wholesale price
Average annual part-time salary of an orthoptist including
social security payment of the employer (according to class
Va of the German Federal Employee Tariffs)
€15 727c
43
Number of kindergartens visited by an orthoptist each day 2 Estimate
Time required to organize an orthoptist’s visit to a kindergarten 30 min (20–40) Estimate; organization was
assumed to take place on a
separate day
Time required to prepare the examination in a kindergarten 20 min (10–30) Estimate
Duration of an orthoptist’s exam in a kindergarten 8 min (5–12) 24; Range estimate
Daily driving time of orthoptist 45 min (30–60) Estimate
Daily driving distance of orthoptist 45 km (30–60) Estimate
Cost per kilometer of orthoptist €0.25 44
Indirect costs
Driving distance of caregiver to the physician office 10 km (5–15) Estimate
Cost per kilometer of caregiver €0.25 44
Average annual full-time labor cost of an employee €42 236d
45
Average annual labor cost of the civil service €8743 46
Percentage of working mothers 0.47 47
Percentage of working mothers who work part-time Յ20h/wk 0.41 47
Percentage of working mothers who work 21–35h/wk 0.16 47
Percentage of working mothers who work Ͼ35h/wk 0.42 47
Percentage of mothers working Յ20h/wk to miss work 0.10 (0.0–0.2) Estimate
Percentage of mothers working 21–35h/wk to miss work 0.5 (0.3–0.7) Estimate
Percentage of mothers working Ն35h/wk to miss work 0.8 (0.6–0.9) Estimate
Proportion of a full-time working day spent for a child’s health
care visit
0.25 (0.1–0.3) Estimate
a
U8, Untersuchung 8; GP, general practitioner.
b
Average point value for preventive services of the statutory health insurance in Northrhine Westfalia.
c
Salaries in the newly-formed German states and the old West German states are weighted according to the number of children at
the age of 3–4 years.
d
The 1996 figure is multiplied by the average increase in the gross income of employees in the industrial and service sector in 1997
and 1998 (3.6%).

taken from the Federal Office of Statistics in Germany (1997 da-
ta).33
The prevalence rate of amblyogenic risk factors was esti-
mated to be 10% (range, 7 to 13) considering the prevalence rate of
each risk factor3–5
as well as the joint occurrence. The prevalence
rate of amblyopia was calculated as the weighted average of three
studies defining amblyopia as a level of visual acuity Յ0.63 (3.1%;
95% confidence interval, 0.028 to 0.034).49–51
This is a rather
conservative estimate because the prevalence study by Attebo et
al.,51
which was performed in adults, did not include cases that had
been treated successfully. Weights were obtained by dividing the
sample size of one study by the total sample size of the three studies.
We assumed that at the time of screening a proportion of pa-
tients had already been identified as having amblyopia because of
obvious squints and/or a positive family history. The percentages
of amblyopia cases identified before screening at age under 1 year
for high-risk children, age less than one year 1 for non-high-risk
patients, and age 3 to 4 for all children were estimated to be 0.5
(range, 0.3 to 0.6), 0.25 (range, 0.1 to 0.35), and 0.6 (range, 0.4 to
0.7), respectively. The estimates present rather high values; thus,
estimates on the cost-effectiveness of screening strategies are rela-
tively conservative.
Cost Data
Cost data were calculated based on the data in Table 5. All costs
were reported in 1999 Euro (1 Euro ϭ 0.91 US$). To calculate
direct costs from the societal viewpoint, reimbursement fees were
used assuming that they are equal to opportunity costs. To calcu-
late the cost of an ophthalmologist’s examination, we used the
private health insurance fee-for-service items list (Gebührenord-
nung für Ärzte), which contains a more detailed listing of the
relevant items than the statutory health insurance’s price scale
(Einheitlicher Bewertungsma␤stab), and, thus, enables a more ac-
curate portrayal of the costs of ophthalmologic examinations. We
included items 1, 1200, 1202, 1216, and 1242 from the private
health insurance fee-for-service list, which add up to 456 points.39
In the sensitivity analysis, we applied a total point score of 890
resulting from items 1, 1216, 1219, and 1242 of the statutory
health insurance’s price scale.40
In both cases, we used the average
point value for preventive services from all statutory health insurers
in the state of Northrhine Westfalia (€0.0422).41
We used the labor cost of civil service as the market value of the
time cost of nonworking caregivers for accompanying children to
and from a physician’s office. In calculating the cost of amblyopia
screening as part of the preventative health examination U8 done
by a general practitioner or pediatrician, we did not consider pro-
ductivity losses and time costs because they were not influenced by
the absence or presence of amblyopia screening.
Sensitivity Analysis
A Monte Carlo simulation with 10,000 iterations was per-
formed. For this purpose, the parameters listed in Tables 1 to 5
were simultaneously varied. Ranges were entered as four standard
errors of the mean or, if unavailable, as reasonable estimates cov-
ering the complete distribution. Distributions were assumed to be
either normal or lognormal. A multiple regression analysis across
simulation iteration results determined the association between
model parameters and the average cost per case detected. The four
parameters with the strongest association plus the higher cost esti-
mate for ophthalmologists’ examinations were further evaluated in
a univariate sensitivity analysis as well as a worst-case and best-case
scenario.
Results of the Application Example
The two-round modified Delphi panel suggested that the me-
dian percentage of the U8 examination devoted to amblyopia
screening was 25 (95% percentile range, 18 to 29). The median
percentage of the four pediatricians who participated only in the
first round was 15 (95% confidence interval, 5 to 39).
Table 6 shows the cost per screening examination depending on
perspective (societal or statutory health insurance) and the type of
examiner. The costs of the first follow-up visit to an ophthalmol-
ogist for false-positive diagnoses were identical to those shown in
the table. The direct medical costs of the second follow-up exam-
ination were €12.82.
Table 7 shows the clinical and economic outcomes of screening
strategies from the societal perspective. The screening of high-risk
children up to the age of 1 year had the lowest average cost per case
detected. The total number of cases detected through orthoptic
screening was much lower than the number for general practitio-
ners or pediatricians mainly because less than half of all children at
the age of 3 to 4 visit kindergarten in Germany.
The probability that screening by orthoptists was less econom-
ically attractive than or dominated by screening of high-risk chil-
dren was 62%. The probability that screening by general practitio-
ners or pediatricians was less economically attractive than or
TABLE 6.
Cost items of one screening exam.a
Examiner
Direct
Medical
Cost
Travel Cost
of Examiner
Total Direct
Costb
Travel Cost of
Caregiver
Loss of
Caregiver’s
Productivity
Time Cost of
Caregiver
Total Direct and
Indirect Costc
Ophthalmologist 19.23 — 19.23 2.45 10.35 7.79 39.83
Pediatrician/GPd
6.85 — 6.85 — — — 6.85
Orthoptist 5.55 0.34 5.90 — — — 5.90
a
All estimates are in 1999 EUR.
b
Equivalent to costs from the viewpoint of the statutory health insurance.
c
Equivalent to costs from the viewpoint of society.
d

dominated by screening of all children up to the age of 1 year was
12%. The total detection rates (including prescreening cases iden-
tified) for screening at age less than 1 year for high-risk children,
age less than 1 year for non-high-risk patients, age 3 to 4 years for
pediatrician or general practitioner examination, and age 3 to 4
years for orthoptist examination were 24.4%, 75.7%, 78.2%, and
71.6%, respectively.
Table 8 shows the clinical and economic outcomes of screening
strategies from the perspective of the statutory health insurance.
Again, the screening of high-risk children up to the age of 1 year
had the lowest average cost per case detected. The screening of
children aged 3 to 4 years by orthoptists (general practitioners and
pediatricians) was dominated by screening by ophthalmologists of
high-risk children (all children) up to the age of 1 year.
Average costs from the societal perspective were higher than
those from the perspective of the statutory health insurance (€643
per case detected if the mean cost difference of all four strategies
was calculated). Table 9 shows the annual loss of working days to
caregivers employed outside the home and of time to caregivers not
employed outside the home.
The four parameters with the strongest association with the
average cost per case detected were prevalence rate of amblyopia,
prescreening detection rate, specificity, and risk of strabismus if
one parent or one sibling is affected. These parameters explained
between 48% and 94% of the variation in the average cost per case
detected.
Tables 10 to 12 show the results of the univariate and the mul-
tivariate sensitivity analysis. The number in the first row and col-
umn of Table 10 says that it costs €1203 per newly detected true-
positive case of amblyopia (compared with no screening) if we
screen high-risk children up to the age of 1 year while assuming a
high value for the prevalence rate of amblyopia (3.4%). In Table
12, the number in the first row and column is read as follows: it
costs €475 per newly detected true-positive case of amblyopia
TABLE 7.
Mean Ϯ SD of clinical and economic outcomes of screening strategies (societal perspective).a
Intervention Total Cost, €
Total
No. of Cases
Average Cost
(€)/Case
Increase in
Cost, €
Increase in
No. of Cases
Increase in Cost
(€)/Increase in
No. of Cases
Screening of high-risk
children aged Ͻ1 yr
4,556,426 Ϯ 827,933 3,682 Ϯ 1,161 1238 Ϯ 797 — — —
Screening of all children
aged Ͻ1 yr
25,391,226 Ϯ 3,362,855 10,694 Ϯ 994 2374 Ϯ 371 16,164,039 6287 2571
aged 3–4 yr
(GP/pediatrician)b
9,227,188 Ϯ 1,214,275 4,406 Ϯ 777 2094 Ϯ 370 4,670,762 725 6445
aged 3–4 yr
(orthoptist)
3,910,210 Ϯ 688,914 2,809 Ϯ 420 1392 Ϯ 278 — — Dominated
a
Standard deviations were obtained through a Monte Carlo simulation. They are not shown for incremental values because the
simulation did not account for the different causes of positive or negative incremental values which would have distorted standard
deviations.52
Calculations were made under consideration of decimal places (not shown).
b
TABLE 8.
Mean Ϯ SD of clinical and economic outcomes of screening strategies (perspective of the statutory health insurance).a
Intervention Total Cost, €
Total
No. of Cases
Average Cost
(€)/Case
Increase in
Cost, €
Increase in
No. of Cases
Increase in Cost
(€)/Increase in
No. of Cases
2,053,781 Ϯ 463,448 3258 Ϯ 1027 630 Ϯ 496 — — —
Screening of all
11,457,113 Ϯ 1,749,289 9464 Ϯ 879 1211 Ϯ 220 9,403,333 6206 1515
Screening of all
children aged 3–4 yr
(GP/pediatrician)b
5,996,990 Ϯ 734,290 3900 Ϯ 688 1538 Ϯ 279 — — Dominated
Screening of all
children aged 3–4 yr
(orthoptist)
2,852,873 Ϯ 502,807 2486 Ϯ 372 1147 Ϯ 234 — — Dominated
a
Standard deviations were obtained through a Monte Carlo simulation. They are not shown for incremental values because the
simulation did not account for the different causes of positive or negative incremental values which would have distorted standard
deviations.52
Calculations were made under consideration of decimal places (not shown).
b

(compared with no screening) if we screen high-risk children up to
the age of 1 year while assuming the most favorable estimates for
prevalence rate of amblyopia, prescreening detection rate, specific-
ity, and risk of strabismus if one parent or one sibling is affected.
In the sensitivity analysis, screening of all children up to the age
of 1 year was the only strategy not dominated by others. Screening
high-risk children was dominated in the worst-case scenario and if
the lower bound of the 95% confidence interval of the risk of
strabismus if one parent or one sibling is affected was used. Screen-
ing by general practitioners or pediatricians and orthoptists was
dominated using most of the assumptions.
DISCUSSION
This article presents a decision-analytical model to evaluate the
cost-effectiveness of screening strategies for amblyopia and its risk
factors in different settings or countries. One of the major advantages
of modeling is the identification of parameters with a strong influence
on results that may be candidates for future research. When applying
the model to Germany, the four parameters with the strongest associ-
ation with the average cost per case detected were prevalence rate of
amblyopia, prescreening detection rate, specificity, and risk of strabis-
mus if one parent or one sibling is affected.
The model suggests that screening all children in Germany up to
the age of 1 year by ophthalmologists is the most economically
attractive strategy to detect amblyopia or amblyogenic factors. This
conclusion considers the various assumptions tested in the sensi-
tivity analysis. Screening high-risk children up to the age of 1 year
showed lower average costs per case detected than screening all
children up to the age of 1 year in the base-case analysis but became
dominated if a low (5.3%) probability of familial clustering of
strabismus was assumed.
TABLE 10.
Results of the univariate sensitivity analysis (societal perspective).a
Strategy
Prevalence
Rate of
Amblyopia/
Amblyogenic
Risk Factors
Specificity
Prescreening
Detection Rates
Probability
of Familial
Clustering of
Strabismus
Cost of an
Ophthalmologist’s
Exam
High values
1,203b
1312c
1,523b
769b
2242c
aged Ͻ1 yr
2,320c
2318c
2,794c
4620c
3913c
aged 3–4 yr
(GP/pediatrician)d
4,500c
3579c
13,413c
Dominated 6689c
aged 3–4 yr (orthoptist)
Dominated 936b
Dominated Dominated 1599b
Low values
1,274b
2301b
911b
Dominated NA
aged Ͻ1 yr
2,882c
3918c
2,372c
2394c
NA
aged 3–4 yr
(GP/pediatrician)
11,376c
9946c
3,107c
3329c
NA
aged 3–4 yr (orthoptist)
Dominated Dominated Dominated 1392b
NA
a
Values indicate the cost (€) per newly detected true-positive case of amblyopia.
b
Average cost-effectiveness ratio (compared to no screening).
c
Incremental cost-effectiveness ratio (compared with the next least-expensive strategy).
d
GP, general practitioner; NA, not applicable.
TABLE 9.
Loss of working days and time according to the type of strategy.
Strategy Annual Loss of Working Days
Annual Loss of Time of
Nonworking Caregivers
(in Working Days)
Screening of high-risk children aged Ͻ1 yr 5,572 20,258
Screening of all children aged Ͻ1 yr 30,984 112,641
Screening of all children aged 3–4 yr (GP/pediatrician) 39,301 142,878
Screening of all children aged 3–4 yr (orthoptist) 19,355 70,364

In contrast, screening all children when they are between 3 and
4 years of age for amblyopia is less economically attractive both
from the perspective of the statutory health insurance and from the
perspective of society. The main reason for inefficiency is the high
percentage of amblyopia cases already identified before screening
leading to a high number of children that need to be screened to
detect one amblyopia case. However, using cost-effectiveness as the
key criterion, the ultimate choice of a strategy depends on the
willingness of decision makers or insured persons to pay for an
additional case detected.
Apart from cost-effectiveness, effectiveness is an important cri-
terion for evaluating screening strategies. Effectiveness was mea-
sured by the percentage of all true-positive cases detected including
cases identified before screening. In the model, the most effective
strategies were screening of all children up to the age of 1 year and
at the age of 3 to 4 years with detection rates between 72% and
78%. Thus, all strategies left a significant portion of children
undetected.
In our model only 31% of true-positive cases with amblyogenic
factors were true-positive cases of amblyopia as well. Thus, 69% of
true-positive cases with amblyogenic factors were unnecessarily
treated for preventing amblyopia because they would not have
manifested amblyopia. On the other hand, we believe that most
children with amblyogenic factors require glasses for correcting
anisometropia and/or hyperopia. Moreover, those 31% who
would have manifested an amblyopia may benefit from a reduced
duration of treatment.22
The net effect (lower quality of life and
additional costs for children receiving unnecessary treatment vs.
the increased quality of life of true positive amblyopia cases who
benefit from a reduced duration of treatment) cannot be deter-
mined due to a lack of data.
The results of this study need to be interpreted with caution.
TABLE 11.
Results of the univariate sensitivity analysis (perspective of the statutory health insurance).a
Strategy
Prevalence
Rate of
Amblyopia/
Amblyogenic
Risk Factors
Specificity
Prescreening
Detection Rates
Probability
of Familial
Clustering of
Strabismus
Cost of an
Ophthalmologist’s
Exam
High values
Screening of high-risk children aged Ͻ1 yr 613b
495b
776b
391b
1144b
Screening of all children aged Ͻ1 yr 1327c
1182c
1736c
2358c
2324c
Screening of all children aged 3–4 yr
(GP/pediatrician)d
Dominated Dominated Dominated Dominated 6392c
(orthoptist)
Dominated Dominated Dominated Dominated Dominated
Low values
1307b
463b
Dominated NA
2515c
1276c
1165c
NA
(GP/pediatrician)
Dominated Dominated Dominated Dominated NA
Screening of all children aged 3–4 yrs
(orthoptist)
Dominated Dominated Dominated 1147b
NA
a
b
c
d
GP, general practitioner; NA, not applicable.
TABLE 12.
Results of the multivariate sensitivity analysis.a
Intervention
Best Case
(Societal Perspective)
Best Case
(Statutory Health
Insurance)
Worst Case
(Societal Perspective)
Worst Case
(Statutory Health
Insurance)
229b
Dominated Dominated
1273c
5010c
2630c
(GP/pediatrician)d
Dominated Dominated Dominated Dominated
Screening of all children aged 3–4 yr (orthoptist) Dominated Dominated 3468b
2512b
a
b
c
d

First, some parameters used in the model had to be estimated.
Sensitivity analysis was used to modify the assumptions. In the
sensitivity analysis the relationships among strategies in terms of
dominance were fairly robust, although some uncertainty remains,
particularly with regard to the size of the cost-effectiveness ratios.
Second, the cost-effectiveness analysis did not take into account
the number of amblyopia cases detected before screening and the
costs of identifying them. The difficulty here was to assess screen-
ing patterns in a natural setting, for example the likelihood of
repeat or inadequate examinations (with inadequate examinations
resulting in a high number of false-positive cases). If the costs per
detected amblyopia case were higher for unsystematic screening
than for systematic screening, screening at 3 to 4 years of age would
become even less economically attractive.
Third, the estimate on the number of cases detected through
screening high-risk children up to the age of 1 year is very conser-
vative because non-high-risk children identified through unsys-
tematic screening beyond the age of 1 year were not taken into
account.
Fourth, we assumed ideal conditions in the base case for the
estimates of the examiners’ test statistics. We did this because we
believed that it was ethically justified to demand an optimal level of
motivation from the examiners. On the other hand, reducing the
specificity of diagnostic procedures to the low end of the range did
not change our main conclusion.
Fifth, like many other cost-effectiveness analyses on screening
and diagnostic tests, this study used an intermediate outcome, the
number of cases detected. Including information on the costs and
benefits of treatment would provide a more complete picture of the
cost-effectiveness of screening for amblyopia and its risk factors.
However, data on important treatment outcomes such as the qual-
ity of life are lacking.
Given these limitations of the study, we regard the conclusions
from our model as preliminary. Combining the results of the cost-
effectiveness and the pure effectiveness analysis, screening all chil-
dren up to the age of 1 year by opthalmologists is the preferred
strategy. However, the denominator chosen for this analysis does
not permit the deduction of whether this strategy is economically
attractive compared with other interventions in the health care
system. Furthermore, the transferability of the conclusions of this
study to situations in other countries is limited, for example, by
differences in costs, clinical management, epidemiology, or de-
mography as well as in the diagnostic accuracy and organization of
health care providers. In the U.S., for example, optometrists are
well prepared to perform screening for amblyogenic factors, fol-
low-up investigations, and treatment. In Germany, optometrists
lack the necessary skills and, thus, were not considered in the
application example.
To be able to make final recommendations regarding a favorable
screening model, additional research is needed in several areas. In
particular, we recommend (1) studies on the sensitivity and spec-
ificity of combined screening tests stratified for the age of the child
and the type of examiner, (2) prevalence studies on amblyogenic
factors and amblyopia, and (3) further investigation on the effec-
tiveness of treatment for amblyopia including the impact of ther-
apy on the quality of life.
ACKNOWLEDGMENTS
Parts of this article were presented at the joint meeting of the Bielschowsky
Society for Strabismus Research and the Association of German Orthoptists
held November 19–21, 1999, in Cologne, Germany. The authors would like
to thank Noelle Aplevich, M.A., for her very valuable comments on a prelim-
inary draft of this article.
Received June 29, 2002; revision received November 12, 2002.
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Dr. Afschin Gandjour
Institut für Gesundheitsökonomie und Klinische Epidemiologie
Universität zu Köln
Gleueler Stra␤e 176-178
50935 Köln, Germany
e-mail: Afschin.Gandjour@medizin.uni-koeln.de

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