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 HbA(1c) was >5.6% (HbA(1c) + 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 HbA(1c) + OGTT from the perspective of the statutory health insurance remained, as did fasting glucose + OGTT and HbA(1c) + 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. HbA(1c) + 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 HbA(1c) 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.
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 HbA(1c) was >5.6% (HbA(1c) + 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 HbA(1c) + OGTT from the perspective of the statutory health insurance remained, as did fasting glucose + OGTT and HbA(1c) + 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. HbA(1c) + 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 HbA(1c) 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.
Authors: Valerie Hahn; Martin Halle; A Schmidt-Trucksäss; W Rathmann; C Meisinger; A Mielck Journal: Diabetes Care Date: 2008-12-15 Impact factor: 19.112