OBJECTIVE—To compare the cost-effectiveness of different type 2 diabetes screening strategies using population-based data (KORA Survey; Augsburg, Germany; subjects aged 55–74 years), including participation data.

RESEARCH DESIGN AND METHODS—The decision analytic model, which had a time horizon of 1 year, used the following screening strategies: fasting glucose testing, the oral glucose tolerance test (OGTT) following fasting glucose testing in impaired fasting glucose (IFG) (fasting glucose + OGTT), OGTT only, and OGTT if HbA1c was >5.6% (HbA1c + OGTT), all with or without first-step preselection (p). The main outcome measures were costs (in Euros), true-positive type 2 diabetic cases, incremental cost-effectiveness ratios (ICERs), third-party payers, and societal perspectives.

RESULTS—After dominated strategies were excluded, the OGTT and HbA1c + OGTT from the perspective of the statutory health insurance remained, as did fasting glucose + OGTT and HbA1c + OGTT from the societal perspective. OGTTs (€4.90 per patient) yielded the lowest costs from the perspective of the statutory health insurance and fasting glucose + OGTT (€10.85) from the societal perspective. HbA1c + OGTT was the most expensive (€21.44 and €31.77) but also the most effective (54% detected cases). ICERs, compared with the next less effective strategies, were €771 from the statutory health insurance and €831 from the societal perspective. In the Monte Carlo analysis, dominance relations remained unchanged in 100 and 68% (statutory health insurance and societal perspective, respectively) of simulated populations.

CONCLUSIONS—The most effective screening strategy was HbA1c combined with OGTT because of high participation. However, costs were lower when screening with fasting glucose tests combined with OGTT or OGTT alone. The decision regarding which is the most favorable strategy depends on whether the goal is to identify a high number of cases or to incur lower costs at reasonable effectiveness.

Undetected diabetes may be as prevalent as diagnosed type 2 diabetes (1,2). In a population-based study in Germany, the prevalence of known diabetes was 8.4% among 55- to 74-year-old subjects and 8.2% had previously undiagnosed diabetes (3).

There is a lack of data on the effectiveness of type 2 diabetes screening with respect to reduced morbidity or mortality (4). Nevertheless, the topic is widely discussed, particularly in regards to subjects aged ≥45 years (57). Several screening strategies have been suggested, including fasting glucose, oral glucose tolerance, or HbA1c testing and preceding risk factor assessment (810).

Although there are a variety of recommendations that screening for type 2 diabetes should be implemented, there has been limited consideration of the economic aspects involved (1113). A 1998 study (14) considered quality-adjusted life-years gained as an outcome measure, but this was based on type 1 diabetes data. There are only two existing studies that investigated different screening procedures (15,16). Neither, however, evaluated incremental cost-effectiveness or considered the incomplete participation of the target population in screening programs.

The aim of our study was to evaluate the cost-effectiveness of type 2 diabetes screening for several recommended strategies. The outcome measure was costs (in Euros) per correctly identified diabetic subject. The economic evaluation used carefully assessed primary data from a population-based study conducted in southern Germany (3). We also used a population practice study to consider the participation of subjects in screening programs.

We created a cost-effectiveness model for screening a population-based sample of subjects, aged 55–74 years and who had not been previously diagnosed with diabetes, for type 2 diabetes within 1 year. We compared four strategies. 1) In fasting glucose testing only, diabetes was assumed when fasting glucose was ≥7.0 mmol/l (8). 2) In fasting glucose + OGTT, when fasting glucose was ≥6.1 and <7.0 mmol/l (impaired fasting glucose [IFG]), an OGTT was performed during a second visit. Diabetes was considered when fasting glucose was ≥7.0 mmol/l or 2-h postglucose load was ≥11.1 mmol/l (9). 3) In OGTT only, diabetes was considered when fasting glucose was ≥7.0 mmol/l or 2-h postglucose load was ≥11.1 mmol/l (9). 4) In HbA1c + OGTT, if HbA1c was >5.6% (10), then an OGTT was performed during a second visit.

For strategies 1–3, we assumed the necessity of separate visits, since fasting glucose tests and OGTTs require a fasting state, whereas HbA1c measurements can be done during a regular visit. Nearly all subjects aged ≥55 years in Germany have at least one instance of contact with the health care system during 1 year.

We considered two different models (yielding a total of eight screening procedures for evaluation). In model A, all subjects of the screening population were included for the above-mentioned screening strategies. In model B, a first-step preselection (p) was performed (pfasting glucose, pfasting glucose + OGTT, pOGTT, and pHbA1c + OGTT). Further screening was carried out only among subjects who fulfilled at least one of the following criteria: family history of type 2 diabetes, obesity (BMI 30 kg/m2), hypertension (blood pressure >140/90 mmHg), and fasting triglycerides 2 mmol/l.

Since the actual data of the selection criteria are assumed not to be available for the majority of patients, patient assessment was considered the first step of the screening program and was associated with screening costs.

### Main outcome measures

The main outcomes were screening costs, the number of newly detected true-positive cases of type 2 diabetes related to the whole screening population, and incremental cost-effectiveness ratios (ICERs). Furthermore, we analyzed the percentage of identified diabetic cases in relation to all subjects with previously undiagnosed diabetes in the study population for each screening strategy.

### Determining cost-effectiveness

The economic evaluations were conducted from the perspective of the statutory health insurers who cover the direct costs of the screening program (a third-party payer system) as well as from a societal viewpoint, which is the most comprehensive viewpoint, since it covers both direct and indirect costs. Economic evaluations were performed as cost-effectiveness analyses. Because of the short-term perspective of this study, discounting was not required.

We compared screening strategies using ICERs (additional costs were divided by the additional effect when a screening strategy was compared with the next less expensive or less effective one). We ruled out strategies that were less effective and more expensive than others (dominated) and those with lower effectiveness and a higher ICER (extended dominance) (17).

### Clinical and epidemiological data and survey estimation

The clinical and epidemiological parameters are presented in Table 1. With the exception of the proportions of participation, which were derived from a population-based practice study in the U.K. (18), all data stem from the population-based KORA (Co-operative Health Research in the Region of Augsburg) Survey 2000 (3). The KORA Survey population was selected as a stratified sample from the city of Augsburg, Germany, and the surrounding districts (southern Germany, population of ∼600,000 in 1999). A total of 1,653 of 2,656 subjects aged 55–74 years (62%) could be included. After 131 subjects with known diabetes were excluded, 1,522 remained eligible, 1,353 of whom completed an OGTT. All data from the KORA Survey were calculated, accounting for the sample design.

Cost data are provided in Table 2. Direct medical costs included practitioner and laboratory testing fees. Medical costs were calculated using a price scale set by the German health care system (Einheitlicher Bewertungsmaßstab, average point value in 2002 of €0.04). When considering the societal perspective, costs were calculated as an approximation of opportunity costs. The calculation also took the productivity losses of patients (time away from work to visit the doctor) into account. We calculated a total of 1 h for each separate visit. For the OGTT, however, we considered an additional 2 h required for the test. We assessed productivity losses using the human capital approach, where the average labor cost of an employee was our approximate measure (17). We estimated the time cost of nonworking and retired subjects by applying the replacement approach (19). The proportions of retired subjects as well as fees for the general working population were derived from German statistics available through a personal communication (North Rhine-Westphalia Statistics Bureau and 20,21). All cost data were calculated for 2002 prices and given in Euros (31 December 2002: $1U.S. = €1.12347). ### Sensitivity analysis We varied the following input parameters (Tables 1 and 2): 1) the prevalences of disturbed glucose metabolism (type 2 diabetes, IFG, and/or elevated HbA1c), 2) the proportions of participation for the separate visits, and 3) the labor costs included in the analyses from the societal viewpoint. In the univariate sensitivity analyses, we decreased and increased baseline values of the input variable by 20% each. We conducted a multivariate sensitivity analysis with simultaneous random variation of the parameters using a Monte Carlo simulation with 1,000 iterations. We entered ranges for the input data according to the KORA Survey or the U.K. practice study or estimates (for social costs) (Table 2). We assumed that distributions were either binomial or log normal (for social costs). We fitted multiplicative regression models with and without interaction to estimate an approximate multiplicative equation among costs, effects, cost-effectiveness ratios (CERs) compared with “no intervention” (average CERs) and the variation parameters. The relative relation of the four strategies to one another (in a position of dominance or extended dominance) were analyzed systematically on the simulated datasets to evaluate the proportion of the simulated populations in which relations would change. Further details of the sensitivity analyses are included in the online appendix (available at http://care.diabetesjournals.org). ### Screening costs for the whole target-age population in Augsburg and surrounding districts We estimated the total screening costs for inhabitants aged 55–74 years in Augsburg, Germany, and surrounding districts based on the costs listed in the model (adjusted for sex and age; sample design based). We performed all analyses using SAS for UNIX (version 8.2; SAS Institute, Cary, NC) and Stata Statistical Software (version 7.0; Stata, College Station, TX). ### Detected subjects with undiagnosed diabetes The proportions of subjects with undetected type 2 diabetes per screening strategy among the study population are shown in Table 3. The pfasting glucose strategy (fasting glucose testing after preselection) delivered the lowest percentage of detected cases. Using HbA1c + OGTT (HbA1c testing combined with an OGTT in the whole screening population without first-step preselection) as a screening strategy was the most effective in detecting cases. The age and cardiovascular risk profile (BMI, blood pressure, triglycerides, and HDL cholesterol) of the subjects identified by the selected screening strategies were very similar (data not shown). ### Costs of screening and diagnostic testing The costs of the various screening strategies are presented in Table 3 and Fig. 1. There was a large variation in costs. The highest costs per study subject were incurred by the HbA1c + OGTT because of the large number of subjects using this screening strategy (100% participation in the HbA1c testing). ### Cost-effectiveness The strategies with a first-step preselection were all dominated and could be ruled out, both from the perspective of the statutory health insurance and from the societal viewpoint (Table 3 and Fig. 1). Fasting glucose testing and fasting glucose + OGTT were dominated by the OGTT strategy (which was more effective and incurred lower costs) and could be excluded when considered from the perspective of statutory health insurance. HbA1c + OGTT was more effective than OGTT but incurred higher costs. ICERs considered from the societal viewpoint show that fasting glucose testing was dominated by fasting glucose + OGTT as a screening strategy and OGTT by HbA1c + OGTT (both extended dominance). Among the remaining strategies, fasting glucose + OGTT incurred lower costs but was also less effective than using HbA1c + OGTT (Fig. 1). ICERs (additional costs per additional detected case) from both perspectives, statutory health insurance and society, are presented in Table 3. ### Sensitivity analysis HbA1c + OGTT remained the most effective and expensive strategy in all 1,000 populations generated by the Monte Carlo simulation (Table 4). The relations among the strategies and decisions about ruling out or selecting strategies remained, as they were in all of the simulated datasets from the perspective of statutory health insurance after a systematic analysis of dominances. A total of 68.3% remained from the societal perspective. The results of the regression analysis show that the variation of the parameters that were included in the sensitivity analyses had only moderate effects on the costs, effects, and CERs of the different strategies. The variation in prevalence of disturbed glucose metabolism had the largest effect on CERs. This was particularly true for the HbA1c + OGTT strategy (each 20% decrease and increase of prevalence resulted in a 1.40-fold increase and 0.76-fold decrease of CERs from societal perspective). The results remained unchanged when we included interaction terms (data not shown). Figure 1 demonstrates the minimum and maximum costs and effects resulting from the univariate specific sensitivity analyses of the prevalence of disturbed glucose metabolism (dotted lines). ### Estimation of screening costs in the whole target-age population of the study region (Augsburg and surrounding southern Germany) The population of 55- to 74-year-olds in Augsburg and its surrounding regions was 123,226 in the year 2000. From the KORA Survey (3), we calculated that 10,351 subjects had known diabetes and that 10,105 would have previously undiagnosed diabetes in this age-group. From the perspective of the statutory health insurance, the costs of screening (having ruled out the already diagnosed subjects) for previously undiagnosed diabetes were €503,779 using the OGTT as a screening strategy and €2,203,502 using HbA1c + OGTT. From the societal perspective, these costs were €1,115,142 for the fasting glucose + OGTT strategy and €3,264,646 for HbA1c + OGTT. The fasting glucose + OGTT strategy detected a total of 2,351 true cases, OGTTs 2,736 cases, and HbA1c + OGTT 4,939 cases. We present a decision analytic model for the evaluation of the cost-effectiveness of a number of screening procedures for type 2 diabetes, using population-based data from southern Germany. The OGTT incurred the lowest costs from the perspective of the statutory health insurance system, and a combination of the OGTT and fasting glucose testing incurred the lowest cost from the perspective of society (after dominated strategies were ruled out). However, both of these screening strategies detected only about one-third (OGTT alone) and one-fourth (fasting glucose + OGTT) of subjects with previously undiagnosed diabetes. HbA1c testing followed by OGTT in those subjects who proved to have elevated HbA1c yielded the highest rate of detected type 2 diabetes (more than half of all cases detected). This strategy, however, incurred the highest costs. Those strategies that were performed after a first-step preselection of subjects (considered high risk for type 2 diabetes) were all ruled out because of the additional screening costs involved in preselection. The high effectiveness of HbA1c testing combined with the OGTT to detect previously undiagnosed diabetes can be explained by the complete participation of all subjects in HbA1c testing (which requires no special visit to the doctor but can be performed as an extension of another scheduled visit). The study results remained rather stable in the sensitivity analyses. However, when a participation level of >59.5% for fasting glucose testing and >54.5% for the OGTT was achieved, an OGTT alone would be the most effective strategy and would dominate HbA1c testing combined with an OGTT (data not shown). However, these very high participations for fasting glucose testing and the OGTT can probably only be achieved in a study setting. The participation levels in the present study, which were taken from the results of a practice study in the U.K. (30–35% participation), seem to be reasonable estimations of participation and are transferable across regional settings (18). In Germany, participation in a health check that included fasting glucose testing offered by the statutory health insurance was ∼20–25% (22). It is difficult to compare our results with data from other studies. A U.S. study showed$758U.S. in screening costs per truly detected cases of diabetes from the societal perspective when using the fasting glucose test rather than no screening strategy (16). This is a higher cost expenditure than ours, which is €499. However, county-specific CERs largly depend on unit costs. At the same time, purchasing power parities are insufficient to adjust for differences in unit costs. Therefore, results from one country cannot be directly translated to other countries. Thus, the CERs in the present study may vary when our model is applied to other countries. OGTT and HbA1c testing may be more or less expensive in other health care systems. Our most important result, however, is HbA1c combined with the OGTT is the most effective, as well as most expensive, screening strategy and should not vary across health care systems. Thus, our results should also be valid in other countries.

We assumed that actual information concerning BMI, blood lipids, blood pressure, and family history of diabetes would not be available for the majority of patients. This conclusion is based on health care research data in Germany (22). We therefore considered it necessary to include costs for preselection procedures. If actual data were available, no preselection would be necessary, but the practitioner would have to select patients at high risk for diabetes screening, resulting in added cost. Generally, however, preselection reduces the effectiveness of all screening strategies.

As in the population practice study of Lawrence et al. (18), we defined successful detection of previously undiagnosed diabetes using only one fasting glucose test or OGTT. However, the American Diabetes Association recommends that a diabetes diagnosis be followed by a confirmation test. We chose a single fasting glucose and OGTT as the screening strategy, however, because we could use data on participation from a carefully designed general practice study (18). If we included confirmation testing, the costs per case detected might be higher than in the present study. Twofold testing, however, would probably reduce participation.

Several limitations of the present study must be considered. Like many other cost-effectiveness analyses of screening, we used an intermediate outcome: the number of truly positive cases detected. Including information on potential costs following the screening procedure and benefits of treatment would provide a more complete picture of the cost-effectiveness of screening for diabetes. However, no population-based data regarding the natural disease process of early detected diabetes or results describing the effectiveness of early intervention after diabetes screening are available so far (4,5).

The results of the present study are for a one-time screening situation, and they may not be applicable for ongoing screening. In the case of ongoing screening, the prevalence of undiagnosed diabetes would become lower. As can be concluded from the sensitivity analysis, a lower prevalence of undiagnosed diabetes would raise the costs per case identified and thus affect the CERs. However, the relation among strategies would probably remain the same.

The greatest strength of the present study is that it uses highly valid population-based data, whereas previous analyses used several external data resources. The sensitivity analysis showed reasonable stable results after varying the prevalence of disturbed glucose metabolism (type 2 diabetes, IFG, and elevated HbA1c), participation, and social costs. In particular, the relation among strategies with respect to their costs and level of effectiveness remained stable in the majority of simulated populations.

In general, a cost analysis cannot determine which strategies should be implemented. The choice depends on the goal of the screening program. It may be to identify the most possible cases of previously undiagnosed diabetes or to pursue lower costs per case identified. Cost-effectiveness analyses can only indicate which strategies are dominated by others and can therefore be ruled out and show ICERs to determine which program is more effective although it incurs higher costs. A decision maker can use these information to choose the most suitable screening procedure for a program by taking into account the maximum limit to be spent per additional case detected.

Further studies are warranted in order to answer the question of which screening procedure is most appropriate. To achieve better and less costly screening, participation in screening tests needs to become more accepted by the target population. The most important issue is to evaluate the effectiveness of early intervention in diabetic subjects.

Figure 1—

Cost-effectiveness for the various strategies from the perspective of the statutory health insurance. The gradient of the line reflects the incremental cost-effectiveness ratio. Dotted lines indicate variation of diabetes and pre-diabetes (each 20% decrease and increase).

Figure 1—

Cost-effectiveness for the various strategies from the perspective of the statutory health insurance. The gradient of the line reflects the incremental cost-effectiveness ratio. Dotted lines indicate variation of diabetes and pre-diabetes (each 20% decrease and increase).

Close modal
Table 1—

Clinical and epidemiological data in the whole and the preselected study population

Whole population without previously diagnosed diabetes*Preselected population
n 1,353 938
Sex (% male) 47 49
Age (years) [mean (range)] 64 (55–74) 64 (55–74)
Age distribution (% aged 55–64 years) 58 56
Prevalences and participation
Prevalence of diabetes 8.9 (7.3–10.5) 11.5 (9.2–13.8)
Prevalence of IFG 15.2 (13.6–16.9) 19.2 (17.0–21.4)
Prevalence of diabetes in IFG subjects 11.8 (8.3–15.3) 12.6 (8.8–16.4)
Prevalence of HbA1c >5.6% 46.2 (40.3–52.2) 48.1 (42.5–53.7)
Prevalence of diabetes in subjects with HbA1c >5.6% 14.4 (12.5–16.4) 18.2 (15.4–21.0)
Participation at fasting glucose testing (%) 35 (estimated range 28–42) 35 (estimated range 28–42)
Participation at OGTT (%) 30 (estimate) (estimated range 24–36) 30 (estimate) (estimated range 24–36)
Participation at OGTT in IFG (%) 72 72
Participation in OGTT in subjects with HbA1c >5.6% (%) 72 (estimate) 72 (estimate)
Test parameters
Sensitivity of fasting glucose testing (%) 59.0 (50.8–67.3)§ 58.4 (49.9–67.0)§
Specificity of fasting glucose testing (%) 100 100
Sensitivity of OGTT (%) 100 100
Specificity of OGTT (%) 100 100
Sensitivity of fasting glucose + OGTT 79.4 (72.0–86.8)§ 79.5 (70.2–88.7)§
Specificity of fasting glucose + OGTT (%) 100 100
Sensitivity of HbA1c >5.6% + OGTT 75.1 (62.1–88.1)§ 75.9 (64.5–87.3)§
Specificity of HbA1c >5.6% + OGTT (%) 100.0 100.0
Sensitivity of HbA1c >5.6% 75.1 (62.1–88.1)§ 75.9 (64.5–87.3)§
Specificity of HbA1c >5.6% 56.6 (50.8–62.4)§ 55.5 (49.9–61.2)§
Whole population without previously diagnosed diabetes*Preselected population
n 1,353 938
Sex (% male) 47 49
Age (years) [mean (range)] 64 (55–74) 64 (55–74)
Age distribution (% aged 55–64 years) 58 56
Prevalences and participation
Prevalence of diabetes 8.9 (7.3–10.5) 11.5 (9.2–13.8)
Prevalence of IFG 15.2 (13.6–16.9) 19.2 (17.0–21.4)
Prevalence of diabetes in IFG subjects 11.8 (8.3–15.3) 12.6 (8.8–16.4)
Prevalence of HbA1c >5.6% 46.2 (40.3–52.2) 48.1 (42.5–53.7)
Prevalence of diabetes in subjects with HbA1c >5.6% 14.4 (12.5–16.4) 18.2 (15.4–21.0)
Participation at fasting glucose testing (%) 35 (estimated range 28–42) 35 (estimated range 28–42)
Participation at OGTT (%) 30 (estimate) (estimated range 24–36) 30 (estimate) (estimated range 24–36)
Participation at OGTT in IFG (%) 72 72
Participation in OGTT in subjects with HbA1c >5.6% (%) 72 (estimate) 72 (estimate)
Test parameters
Sensitivity of fasting glucose testing (%) 59.0 (50.8–67.3)§ 58.4 (49.9–67.0)§
Specificity of fasting glucose testing (%) 100 100
Sensitivity of OGTT (%) 100 100
Specificity of OGTT (%) 100 100
Sensitivity of fasting glucose + OGTT 79.4 (72.0–86.8)§ 79.5 (70.2–88.7)§
Specificity of fasting glucose + OGTT (%) 100 100
Sensitivity of HbA1c >5.6% + OGTT 75.1 (62.1–88.1)§ 75.9 (64.5–87.3)§
Specificity of HbA1c >5.6% + OGTT (%) 100.0 100.0
Sensitivity of HbA1c >5.6% 75.1 (62.1–88.1)§ 75.9 (64.5–87.3)§
Specificity of HbA1c >5.6% 56.6 (50.8–62.4)§ 55.5 (49.9–61.2)§

Data are percent (95% CI) unless otherwise indicated. With the exception of the participation proportions, which were derived from a practice study in the U.K. (18), all data were taken from the KORA Survey 2000 (3). Prevalences and test parameters are sample design based.

*

KORA Survey population without previously diagnosed diabetes.

Includes at least one of the risk factors: family history of type 2 diabetes, BMI >30 kg/m2, blood pressure >140/90 mmHg, triglycerides >2 mmol/l.

It is assumed that the participating population is not different from the nonparticipants, with respect to the evaluated parameters. The preselected population was considered to participate in the same proportion as the whole study population.

§

Not included in the sensitivity analysis.

According to the definition of type 2 diabetes, fasting glucose testing has a specificity of 1.0, with OGTT as the gold standard. Defining diabetes, according to the World Health Organization’s 1999 criteria, is characterized by sensitivity and specificity of 1.0.

Table 2—

Cost data

Procedures and parametersUnits, unit costs, and proportionsSources and comments
Fasting glucose testing* €14.78 EBM: consultation fee (item 2), advice conversation fee (item 10), laboratory testing (fasting glucose: items 3661, 3707)
OGTT* €16.34 EBM: consultation fee (item 2), advice conversation fee (item 10), laboratory testing (OGT: items 3661*3, 3707*3)
HbA1c testing €16.00 EBM: advice conversation fee (item 2), laboratory testing (item 3722)
Preselection testing €12.18 EBM: conversation fee (item 10), laboratory testing (triglycerides: item 3667)
Time required for the visit including subject’s travel time to and from the practice; all separate visits, except OGTT 1 h Estimate
Time required for the visit including subject’s travel time to and from the practice for OGTT 3 h Estimate
Proportion of working subjects (%)  Year 2000, Statistics Bureau of North-Rhine Westfalia (personal communication)
Men aged 55–59 years 74.5
Men aged 60–64 years 28.9
Women aged 55–59 years 47.6
Women aged 60–64 years 13.1
All aged ≥65 years 0.0
Average labor cost per hour of an employee (assumed for working subjects) €29.19 (estimated range 23.35–35.03) Annual labor cost for 1996 (Statistics Bureau 1999), annual costs multiplied by an annual 3% increase in the gross income of employees; 2002 working hours per year
Average labor cost per hour of the civil service (assumed for subjects not working or retired) €5.37 (estimated range 4.30–6.44) Annual labor cost for 1996 (Bureau of Civil Services 1999), annual costs multiplied by an annual 3% increase in the gross income of employees up to the year 2002; 2002 working hours per year
Procedures and parametersUnits, unit costs, and proportionsSources and comments
Fasting glucose testing* €14.78 EBM: consultation fee (item 2), advice conversation fee (item 10), laboratory testing (fasting glucose: items 3661, 3707)
OGTT* €16.34 EBM: consultation fee (item 2), advice conversation fee (item 10), laboratory testing (OGT: items 3661*3, 3707*3)
HbA1c testing €16.00 EBM: advice conversation fee (item 2), laboratory testing (item 3722)
Preselection testing €12.18 EBM: conversation fee (item 10), laboratory testing (triglycerides: item 3667)
Time required for the visit including subject’s travel time to and from the practice; all separate visits, except OGTT 1 h Estimate
Time required for the visit including subject’s travel time to and from the practice for OGTT 3 h Estimate
Proportion of working subjects (%)  Year 2000, Statistics Bureau of North-Rhine Westfalia (personal communication)
Men aged 55–59 years 74.5
Men aged 60–64 years 28.9
Women aged 55–59 years 47.6
Women aged 60–64 years 13.1
All aged ≥65 years 0.0
Average labor cost per hour of an employee (assumed for working subjects) €29.19 (estimated range 23.35–35.03) Annual labor cost for 1996 (Statistics Bureau 1999), annual costs multiplied by an annual 3% increase in the gross income of employees; 2002 working hours per year
Average labor cost per hour of the civil service (assumed for subjects not working or retired) €5.37 (estimated range 4.30–6.44) Annual labor cost for 1996 (Bureau of Civil Services 1999), annual costs multiplied by an annual 3% increase in the gross income of employees up to the year 2002; 2002 working hours per year
*

Separate visit.

Remaining subjects are assumed not to work or to be retired. EBM, Einheitlicher Bewertungsmaßstab (see research design and methods for details).

Table 3—

Cost, effectiveness, and ICERs for the different strategies: perspective of the statutory health insurance and societal perspective

StrategyProportion of detected cases among all previously unknown diabetic subjects (%)Total costs (per study subject) (€)Effectiveness (number of detected cases per study subject)Additional costs per 1,000 of study population (€)Additional detected cases per 1,000 of study population (n)ICERs (costs per detected case)
Statutory health insurance perspective
Whole screening population
Fasting glucose test 20.7 5.17 0.018 — — Dominated
Fasting glucose and OGTT 25.8 5.80 0.023 — — Dominated
OGTT 30.0 4.90 0.027 Base case Base case Base case
HbA1c >5.6% and OGTT 54.1 21.44 0.048 16,539 21.4 771
Preselected population
Fasting glucose test 18.2 15.76 0.016 — — Dominated
Fasting glucose and OGTT 22.9 16.31 0.021 — — Dominated
OGTT 26.7 15.58 0.024 — — Dominated
HbA1c >5.6% and OGTT 48.6 27.18 0.044 — — Dominated
Societal perspective
Whole screening population
Fasting glucose test 20.7 8.98 0.018 — — Dominated (extended)
Fasting glucose and OGTT 25.8 10.85 0.023 Base case Base case Base case
OGTT 30.0 14.68 0.027 — — Dominated (extended)
HbA1c >5.6% and OGTT 54.1 31.77 0.048 20,916 25.2 831
Preselected population
Fasting glucose test 18.2 18.36 0.016 — — Dominated
Fasting glucose and OGTT 22.9 19.98 0.021 — — Dominated
OGTT 26.7 22.24 0.024 — — Dominated
HbA1c >5.6% and OGTT 48.6 34.47 0.044 — — Dominated
StrategyProportion of detected cases among all previously unknown diabetic subjects (%)Total costs (per study subject) (€)Effectiveness (number of detected cases per study subject)Additional costs per 1,000 of study population (€)Additional detected cases per 1,000 of study population (n)ICERs (costs per detected case)
Statutory health insurance perspective
Whole screening population
Fasting glucose test 20.7 5.17 0.018 — — Dominated
Fasting glucose and OGTT 25.8 5.80 0.023 — — Dominated
OGTT 30.0 4.90 0.027 Base case Base case Base case
HbA1c >5.6% and OGTT 54.1 21.44 0.048 16,539 21.4 771
Preselected population
Fasting glucose test 18.2 15.76 0.016 — — Dominated
Fasting glucose and OGTT 22.9 16.31 0.021 — — Dominated
OGTT 26.7 15.58 0.024 — — Dominated
HbA1c >5.6% and OGTT 48.6 27.18 0.044 — — Dominated
Societal perspective
Whole screening population
Fasting glucose test 20.7 8.98 0.018 — — Dominated (extended)
Fasting glucose and OGTT 25.8 10.85 0.023 Base case Base case Base case
OGTT 30.0 14.68 0.027 — — Dominated (extended)
HbA1c >5.6% and OGTT 54.1 31.77 0.048 20,916 25.2 831
Preselected population
Fasting glucose test 18.2 18.36 0.016 — — Dominated
Fasting glucose and OGTT 22.9 19.98 0.021 — — Dominated
OGTT 26.7 22.24 0.024 — — Dominated
HbA1c >5.6% and OGTT 48.6 34.47 0.044 — — Dominated
Table 4—

Results of the Monte Carlo analysis

StrategyProportion of detected cases among all previously unknown diabetic subjects (%)Total costs (per study subject) (€)Effectiveness (number of detected cases per study subject)
Perspective of the statutory health insurance
Fasting glucose test 20.7 ± 0.01 (19.7–21.7) 5.17 ± 0.19 (4.94–5.42) 0.018 ± 0.002 (0.016–0.021)
Fasting glucose and OGTT 25.8 ± 0.01 (24.5–27.3) 5.81 ± 0.24 (5.52–6.11) 0.023 ± 0.003 (0.020–0.026)
OGTT 30.1 ± 0.01 (28.5–31.6) 4.92 ± 0.20 (4.66–5.17) 0.027 ± 0.003 (0.023–0.030)
HbA1c >5.6% and OGTT 53.9 ± 0.02 (51.0–56.9) 21.44 ± 0.48 (20.85–22.06) 0.048 ± 0.008 (0.038–0.059)
Societal perspective
Fasting glucose test 20.7 ± 0.01 (19.7–21.7) 9.37 ± 1.63 (7.63–11.63) 0.018 ± 0.002 (0.016–0.021)
Fasting glucose and OGTT 25.8 ± 0.01 (24.5–27.3) 11.39 ± 2.13 (9.05–14.16) 0.023 ± 0.003 (0.020–0.026)
OGTT 30.1 ± 0.01 (28.5–31.6) 15.74 ± 4.12 (11.36–21.56) 0.027 ± 0.003 (0.023–0.030)
HbA1c >5.6% and OGTT 53.9 ± 0.02 (51.0–56.9) 32.83 ± 4.57 (27.74–39.08) 0.048 ± 0.008 (0.038–0.059)
StrategyProportion of detected cases among all previously unknown diabetic subjects (%)Total costs (per study subject) (€)Effectiveness (number of detected cases per study subject)
Perspective of the statutory health insurance
Fasting glucose test 20.7 ± 0.01 (19.7–21.7) 5.17 ± 0.19 (4.94–5.42) 0.018 ± 0.002 (0.016–0.021)
Fasting glucose and OGTT 25.8 ± 0.01 (24.5–27.3) 5.81 ± 0.24 (5.52–6.11) 0.023 ± 0.003 (0.020–0.026)
OGTT 30.1 ± 0.01 (28.5–31.6) 4.92 ± 0.20 (4.66–5.17) 0.027 ± 0.003 (0.023–0.030)
HbA1c >5.6% and OGTT 53.9 ± 0.02 (51.0–56.9) 21.44 ± 0.48 (20.85–22.06) 0.048 ± 0.008 (0.038–0.059)
Societal perspective
Fasting glucose test 20.7 ± 0.01 (19.7–21.7) 9.37 ± 1.63 (7.63–11.63) 0.018 ± 0.002 (0.016–0.021)
Fasting glucose and OGTT 25.8 ± 0.01 (24.5–27.3) 11.39 ± 2.13 (9.05–14.16) 0.023 ± 0.003 (0.020–0.026)
OGTT 30.1 ± 0.01 (28.5–31.6) 15.74 ± 4.12 (11.36–21.56) 0.027 ± 0.003 (0.023–0.030)
HbA1c >5.6% and OGTT 53.9 ± 0.02 (51.0–56.9) 32.83 ± 4.57 (27.74–39.08) 0.048 ± 0.008 (0.038–0.059)

Data are mean ± SD (10th to 90th percentile).

The study was supported by institutional funding (German Diabetes Research Institute) from the German Ministery of Health and by the Ministery of Science of North-Rhine Westfalia. The study was supported in part by a research grant from the German Diabetes Foundation.

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Additional information for this article can be found in an online appendix at http://care.diabetesjournals.org.

A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.