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Volume
7: No. 5, September 2010
ORIGINAL RESEARCH
Cost-Effectiveness Analysis of Efforts to Reduce Risk of Type 2 Diabetes and Cardiovascular Disease in Southwestern Pennsylvania, 2005-2007
This model shows 6 possible health states: 1) no diabetes, risk-factor–negative; 2) risk-factor–positive, not enrolled in
a modified Diabetes Prevention Program (mDPP); 3) risk-factor–positive, enrolled in
an mDPP; 4) stable diabetes; 5) complicated diabetes; and 6) death. For each
model cycle, patients either remain in the same health state (indicated with
short curved arrows) or move (“transition”) to another health state (indicated
with straight arrows or long curved arrows). The following transitions are
permitted. From health state 1, patients may remain in health state 1 or
transition to health states 2, 3, 4, or 6. From health state 2, patients may
remain in health state 2 or transition to health states 1, 4, or 6. From health
state 3, patients may remain in health state 3 or transition to health states 1,
4, or 6. From health state 4, patients may remain in health state 4 or
transition to health states 5 or 6. From health state 5, patients may remain in
health state 5 or transition to health state 6.
Figure 1. Model analyzing cost-effectiveness of a
modified Diabetes Prevention Program, southwestern Pennsylvania, 2005-2007.
Ovals indicate health states. Subjects may remain in a health state (short
curved arrow) or may move to a different health state (straight arrow or long
curved arrow) during each model cycle.
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Figure 2 shows the 1-way sensitivity analysis for 8 model parameters. For each parameter, we summarize the parameter values (baseline value; range: minimum, maximum) and provide the corresponding cost-effectiveness ratios
(CERs).
For example, the first parameter listed is “Probability of reducing risk factors without an mDPP.” The baseline probability was 12.1%, but in sensitivity analyses, we varied this value from a low of 3.2% to a high of 25.9%. At the baseline value, the cost-effectiveness ratio was $3,420. If this probability decreases to 3.2%, then the cost-effectiveness ratio is $783 per QALY; if the probability increases to 25.9%, then the cost-effectiveness ratio is $18,580. We
summarize this information as follows:
- Probability of reducing risk factors without an mDPP: 12.1%; range, 3.2%-25.9%
($3,420; range, $783-$18,580)
Analogous summaries for the remaining 7 parameters are
- Probability of enrollment in an mDPP: 47.0%; range, 9.2%-86.7% ($3,420; range, $16,707-$1,911)
- Probability of reducing risk factors with an mDPP: 16.2%; range, 4.2%-34.4%
($3,420; range, $13,087-$0)
- Probability of screening risk-factor–positive: 31.0%; range, 7.2%-63.5%
($3,420; range, $14,046-$1,818)
- Utility for risk-factor–positive patients with an mDPP: 0.75; range, 0.73-0.77
($3,420; range, $13,178-$1,926)
- Probability of diabetes for risk-factor–positive patients without an mDPP: 10.8%; range, 2.9%-23.3%
($3,420; range, 8,505-$0)
- Probability of diabetes for risk-factor–positive patients with an mDPP: 4.8%; range, 1.3%-10.5%
($3,420; range, $7,085-$1,911)
- Utility for risk-factor–positive patients without an mDPP: 0.73; range, 0.71-0.75
($3,420; range, $2,280-$7,301)
The parameters are listed based on the variation in CERs, with the parameter
causing the most variation listed first.
Model Parameter |
Parameter Value |
Cost-Effectiveness, $ per QALY |
Base case |
Min value |
Max value |
Base case |
Low CER |
High CER |
Probability of reducing risk factors without an mDPP |
12.1% |
3.2% |
25.9% |
3,420 |
783 |
18,580 |
Probability of enrollment in an mDPP |
47.0% |
9.2% |
86.7% |
3,420 |
1,911 |
16,707 |
Probability of reducing risk factors with an mDPP |
16.2% |
4.2% |
34.4% |
3,420 |
0 |
13,087 |
Probability of screening risk-factor–positive |
31.0% |
7.2% |
63.5% |
3,420 |
1,818 |
14,046 |
Utility for risk-factor–positive patients with an mDPP |
0.75 |
0.73 |
0.77 |
3,420 |
1,926 |
13,178 |
Probability of diabetes for risk-factor–positive
patients without an mDPP |
10.8% |
2.9% |
23.3% |
3,420 |
0 |
8,505 |
Probability of diabetes for risk-factor–positive
patients with an mDPP |
4.8% |
1.3% |
10.5% |
3,420 |
1,911 |
7,085 |
Utility for risk-factor–positive
patients without an mDPP |
0.73 |
0.71 |
0.75 |
3,420 |
2,280 |
7,301 |
Figure 2. One-way sensitivity analyses assessing cost-effectiveness of
a modified Diabetes Prevention Program (mDPP), southwestern Pennsylvania, 2005-2007.
Horizontal bars depict the range of cost-effectiveness ratios for the values
shown for each parameter. The vertical dotted line depicts the base case
cost-effectiveness ratio. Variation of all other parameters not shown in the
figure did not increase the cost-effectiveness ratio above $7,000 per QALY
gained. Abbreviations: QALY, quality-adjusted life-year; Min, minimum; Max, maximum; CER,
cost-effectiveness ratios; mDPP, modified Diabetes Prevention Program.
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This acceptability curve depicts the likelihood of a modified Diabetes Prevention Program lifestyle intervention being favored for a given cost-effectiveness ceiling threshold (willingness to pay).
Willingness to Pay, $ |
Probability of Cost-Effectiveness, % |
0 |
12 |
5,000 |
50 |
10,000 |
67 |
15,000 |
75 |
20,000 |
79 |
25,000 |
82 |
30,000 |
84 |
35,000 |
85 |
40,000 |
86 |
45,000 |
87 |
50,000 |
87 |
55,000 |
87 |
60,000 |
88 |
65,000 |
88 |
70,000 |
88 |
75,000 |
88 |
80,000 |
89 |
85,000 |
89 |
90,000 |
89 |
95,000 |
89 |
100,000 |
89 |
Figure 3. Probabilistic (Monte Carlo) sensitivity analyses assessing cost-effectiveness of
a modified Diabetes Prevention Program (mDPP), southwestern Pennsylvania, 2005-2007. The acceptability curve depicts the likelihood of an mDPP
lifestyle intervention being favored for a given cost-effectiveness ceiling
threshold (willingness to pay).
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