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For patients with type 2 diabetes taking oral antidiabetics, self-monitoring of blood glucose cost-effectiveness (1 and 3 times per day) was modeled. Both strategies represented good value in the US payer setting.
Objective: This study was designed to model the cost-effectiveness of self-monitoring of blood glucose (SMBG) at frequencies of 1 or 3 times per day for patients with type 2 diabetes mellitus (T2DM) who are treated with oral antidiabetic (OAD) medications within the United States.
Study Design: Based on a Kaiser Permanente study showing glycosylated hemoglobin (HbA1C) improvements related to SMBG frequency, a validated model was used to project 40-year clinical and economic outcomes for SMBG at 1 or 3 times per day vs no SMBG.
Methods
: Baseline mean HbA1C (8.6%), age, and sex of the simulated cohort came from the Kaiser analysis of new SMBG users of OAD agents for T2DM. Other cohort characteristics, transition probabilities, utilities, and direct costs (from a US public payer perspective) were derived from relevant literature. Outcomes were discounted at 3% per annum, with sensitivity analyses performed on discount rates and time horizons.
Results: Compared with no SMBG, qualityadjusted life expectancy increased with SMBG frequency. Increases were 0.103 and 0.327 quality-adjusted life-years (QALYs) for SMBG at 1 and 3 times per day, respectively. Corresponding incremental cost-effective ratios (ICERs) were $7856 and $6601 per QALY gained. Results indicate that SMBG at both 1 and 3 times per day in this cohort of patients with T2DM taking OADs would represent good value for money in the United States, with ICERs being most sensitive to the time horizon.
Conclusions: Longer time horizons generally led to greater SMBG cost-effectiveness. The ICER for SMBG 3 times per day was $518 per QALY over a 10-year time horizon, indicating very good value.
(Am J Manag Care. 2008;14(3):131-140)
Glycemic control reduces diabetes-related complications. These reductions have demonstrated short- and long-term economic benefits. Self-monitoring of blood glucose (SMBG) has been linked to improved glycemic control for insulin-using patients, and less consistently for patients with type 2 diabetes taking oral agents.
Using data from a Kaiser Permanente “real-world†study, cost-effectiveness of SMBG 1 and 3 times per day was modeled.
For both SMBG frequencies, relative risks (vs no SMBG) were lower for most complications.
Although not cost saving, both SMBG frequencies showed good value. Incremental cost-effectiveness ratios were less than $8000 per quality-adjusted life-year gained.
The contribution of cost-effectiveness analyses in assessing the long-term value of healthcare interventions and management tools is increasing for a large number of disease states, including diabetes mellitus. The extremely large and growing economic burden of this chronic disease has been well documented. According to the Centers for Disease Control and Prevention, approximately 14.7 million people in the United States had been diagnosed with diabetes through 2004, with type 2 diabetes mellitus (T2DM) accounting for about 90% of those cases.1 Individuals with diabetes are commonly treated for concomitant neurological disease, peripheral vascular disease, cardiovascular disease, renal disease, endocrine/metabolic complications, and ophthalmic complications.2,3 A total of $92 billion in direct medical expenditures were attributable to diabetes for 2002, and the projected increase in the diabetes population suggests that annual direct costs could reach $138 billion by 2020.2 Identifying cost-effective technologies for diabetes management is therefore crucial for optimizing the use of healthcare dollars in the United States.
Benefit of Glycemic ControlGlycemic control is fundamental to diabetes management, and has a well-established role in preventing, delaying, and/or reducing diabetesrelated complications.4,5 The widely cited United Kingdom Prospective Diabetes Study (UKPDS) showed that each 1% reduction in glycosylated hemoglobin (HbA1C) corresponded to a 37% reduction in microvascular complication risk in T2DM.4 Decreases in complications, in turn, have demonstrated short- and long-term economic benefits.6-8
Self-monitoring of Blood GlucoseOne management tool repeatedly shown to aid in the improvement of glycemic control for insulin-using patients is self-monitoring of blood glucose (SMBG).9-12 Additionally, increased SMBG frequency has been linked to lower HbA1C values for this population.13-15 Consequently, clinical guidelines recommend SMBG at least 3 times daily for patients with diabetes who use insulin.3,16
SMBG for Patients With T2DM Taking Oral Antidiabetic MedicationsFor patients with T2DM who are treated with oral antidiabetic (OAD) agents (and not using insulin), findings (as well as subsequent recommendations) regarding SMBG have been more inconsistent. Some researchers have failed to find a clear benefit of SMBG for individuals with T2DM who are being treated with OADs.17,18 However, recent meta-analyses of randomized trials have led to conclusions that SMBG in this patient population is generally associated with a statistically significant improvement in HbA1C.19-21
Additional evidence regarding the effect of SMBG frequency on patients with T2DM taking OADs comes from a large-scale (n >30,000), 3-year observational study by the Kaiser Permanente Healthcare Group. Glycemic control was evaluated for patients with T2DM grouped according to current treatment and history of SMBG use.13,15 Patients with T2DM taking OADs were defined as either “new users” (newly initiating SMBG) or “prevalent users” (had practiced SMBG within the prior year).
While both groups showed a graded improvement in HbA1C related to SMBG frequency (up to 3 times per day), response to increasing frequency was greatest among new users. When new users began SMBG at 1, 2, or 3 times per day, reductions in HbA1C were 0.32%, 0.77%, and 1.02%, respectively.
Despite these findings, the long-term value of SMBG for T2DM patient populations treated with OADs has yet to be firmly established. Published recommendations currently vary widely and lack specificity.3 Compounding the issue is that in this era of cost containment, SMBG represents a relatively costly management tool when viewed solely within shortterm time horizons. The direct costs associated with the use of SMBG have recently been estimated to represent 58.8% of Medicare B program expenditures for treating patients with T2DM who are not taking insulin.22 Clinical and policy stakeholders in the United States are therefore interested in obtaining additional information with which to assess the long-term clinical and economic outcomes associated with SMBG frequency for this large and growing patient population.
Study ObjectivesThe present study was designed to model the cost-effectiveness of SMBG (at frequencies of 1 or 3 times daily) compared with no SMBG for patients with T2DM taking OAD medications. We addressed the extent to which increased costs associated with SMBG could be offset by fewer complications and increased quality-adjusted life-years (QALYs), so that SMBG would represent a cost-effective management tool for this patient population. An additional goal was to enumerate the comparative risks of several complications of diabetes for the 2 SMBG simulated groups, relative to patients not using SMBG.
METHODS
A computer-based diabetes model was used to project the long-term (40-year) clinical and economic outcomes associated with SMBG by patients with T2DM treated with OADs in the US payer setting. Outcomes included estimated gains in life expectancy and in QALYs, long-term costs of treatment and complications, cumulative risk of specific complications, and incremental cost-effectiveness ratios (ICERs).
Model Design and ValidationThe CORE Diabetes Model was designed to predict the development and progression of type 1 or type 2 diabetes over long-term time horizons (≥5 years), using the best available clinical and cost data. The model is based on 15 interdependent submodels, each having a Markov structure. Monte Carlo simulation and tracker variables can account for multiple complications (cardiovascular, neuropathy, renal and eye disease) at the individual patient level. Described and validated in peer-reviewed publications, the model is consistent with recently published American Diabetes Association (ADA) modeling guidelines and principles.23,24 This ADA consensus document also provides support for the 40-year time horizon in the base case scenario. Because diabetes complications (eg, end-stage renal disease) may take years or even decades to occur, time horizons that cover “a patient’s lifetime” such as 30 to 40 years are commonly incorporated for cost-effectiveness analyses.25
Simulation Cohorts and Treatment EffectsCohort characteristics and magnitude of treatment effects were based on patient samples and study outcomes from the longitudinal study by Karter et al described above.15 Detailed information was available for the “new user” cohort, and in the present analysis only results for subsets of patients within this large group (n >16,000) were included. The inclusion of this cohort, according to the investigators, reduces chronology bias and case-mix confounding associated with studies that pool data for “new” vs “ongoing” users of SMBG.
Table 1
A simulation cohort was defined using mean baseline HbA1C, age, smoking status, and sex corresponding to patients with T2DM taking oral agents and newly initiating SMBG.13 Information on race/ethnicity came from an earlier observational study of similar patients with T2DM,15 and key clinical parameters were based on the diabetes-specific substudy of the National Health and Nutrition Examination Survey (NHANES),26 as well as from 5 other published papers27-31 ().
Among new users treated with OADs in the Karter et al study,13 use of SMBG at a frequency of 0.51 to 1.00 strips per day (n = 2611) or 2.51 to 3.00 strips per day (n = 318) was associated with reductions in HbA1C of – 0.32% ± 2.56% and –1.02% ± 1.7%, respectively. Standard deviations necessary for this analysis were supplied by the Kaiser Permanente study group. The reference group (referred to here as the no SMBG group) consisted of the 5313 patients taking OADs who did not use SMBG or who (on average) self-monitored at a frequency of no more than 0.5 times per day. The mean change in HbA1C for this group was +0.13% ± 2.38%.
The simulated mean change in HbA1C was maintained over the course of the simulation (40 years). Based on the progressive nature of diabetes as documented through the UKPDS, it was assumed that after 5 years, patients switched to insulin treatment.32 Furthermore, it was conservatively assumed that although patients continued to use SMBG (testing frequency 3 times per day) when treated with insulin, no further improvements in HbA1C were associated with its use.25 In the base case, compliance was modeled to be 100%.
Costs, Utility Values, and ComplicationsAnalyses were conducted from a public payer perspective in the US healthcare system and thus included only direct medical (treatment and complication) costs. Costs of treating diabetes-related complications were extracted from published sources33-39 and inflated to 2006 US dollars using the Consumer Price Index (Table 2).40
Acquisition costs for strips and lancets required for monitoring were based on Medicare reimbursement values (as supplied by LifeScan, a Johnson & Johnson Company) and were $0.74 and $0.12 per unit, respectively). The SMBG monitor itself was considered to be cost-free in the model. Patient education and training costs were based on the assumption that patients receive a 1-hour course from a nurse at the initiation of SMBG during year 1 only, at a cost of $108.77.
Discounting rates of 3% were applied to both clinical and economic outcomes.41 Utility values used to calculate QALYs were based on data from the UKPDS, and from other published studies,42-46 with no “dis-utility” assumed for the SMBG use. Finally, the examination of diabetes-related complications included the calculation of cumulative incidence, as well as relative risk for SMBG at 1 and 3 times per day compared to no SMBG.
Statistical Methods
For patients testing once per day, undiscounted life expectancy and QALYs were improved by 0.205 and 0.103, relative to patients not using SMBG. Use of SMBG 3 times per day was associated with even greater improvements compared with not testing; the increase in undiscounted life expectancy was 0.647 years, and the increase in QALYs was 0.327 (Table 3).
Diabetes-related ComplicationsThe cumulative incidence of 16 diabetes-related complications modeled for no SMBG patients are presented in Table 4. Also included are risk ratios (relative to no SMBG) modeled for SMBG once per day and 3 times per day. Compared with no SMBG, SMBG once per day was projected to have very slightly higher risks for 2 complications (first stroke and first amputation). Of the other 14 complications, SMBG once per day was associated with slightly lower risks for 13 (relative risks ranging from 0.921 to 0.988); for endstage renal disease, the risk reduction was greater than 10% (relative risk 0.898). The number needed to treat (NNT) ranged from 41 for onset of neuropathy to 513 for angina.
Simulated patients utilizing 3 times daily SMBG showed greater reductions in the cumulative incidence of many (particularly microvascular) complications. The relative risk was lower for 14 of 16 complications modeled and slightly increased for 2 (first stroke and first amputation). SMBG 3 times per day resulted in relative risk improvements of at least 10% for 10 complications, with greatest risk reductions (>20%) for 2 renal-related complications (gross proteinuria 0.724, and end-stage renal disease 0.616) and for 2 complications related to the eye (proliferative retinopathy 0.739, and macular edema 0.786). The risk of peripheral vascular disease onset was also decreased by 20% with a relative risk of 0.797. The NNT ranged from 15 for microalbuminuria to 437 for angina, and NNT values were 20 or less for 4 complications.
Lifetime Direct Costs and Cost-effectivenessFor both scenarios, use of SMBG was associated with increased total direct medical costs (Table 3). Compared to no SMBG, increases in mean per patient lifetime direct medical costs were $808 for once per day and $2161 for 3 times per day SMBG. For once per day, the improvements in QALYs reported earlier partially offset the increased costs so that the projected ICER was $7856 per QALY gained. For 3 times per day, the even larger improvement in QALYs resulted in an ICER of $6601 per QALY gained. Complication costs were $66,317 for no SMBG, $65,511 for SMBG once per day, and $63,784 for SMBG 3 times per day.
Figure 1
Figure 2
Incremental Cost-effectiveness Scatter Plots/Acceptability Curves shows the base case cost-effectiveness scatter plot for SMBG once per day vs no SMBG. Although more points were to the right of the grid (indicating greater effectiveness with SMBG once per day), the results showed wide scatter. This resulted partially from the relatively large (and therefore conservative) standard deviation used to model the clinical response (change in HbA1C). The base case costeffectiveness scatter plot for SMBG 3 times per day vs no SMBG is shown in . As expected, more points appear in the upper 2 quadrants, indicative of greater costs. Compared with the scatter plot for SMBG once per day, the upper right quadrant (indicating greater costs but greater effectiveness) contains a larger proportion of the points, and also shows less scatter.
Relative to no SMBG, acceptability at a willingness-to-pay of $50,000/QALY was 52.6% for SMBG once per day and 60.7% for SMBG 3 times per day. Compared with no SMBG, SMBG once per day would be cost-effective at the threshold of $20,000/QALY, 51.5% of the time and of $10,000/QALY, 51.3% of the time. For 3 times per day vs no SMBG, values were 56.7% and 51.6% for the $20,000/QALY and $10,000/QALY thresholds, respectively.
Sensitivity AnalysesAs is commonly the case, results were sensitive to the time horizon used (Table 5). For SMBG once per day, reductions in time horizon to 5 years resulted in an ICER of $23,380/QALY. For SMBG 3 times per day, a 5-year time horizon was associated with an ICER of $29,137/QALY. With a 10-year time horizon, SMBG once per day resulted in an ICER of $9346/QALY. Finally, the ICER for SMBG 3 times per day was only $518/QALY under a 10-year time horizon, indicating very good value for money.
As expected, when compliance was modeled at 66% and at 33%, ICERs increased from the base case. For 66% compliance (SMBG 3 times per day treatment costs and 2 times clinical benefits, vs no SMBG), the difference in QALYs was 0.250, the difference in total costs was $2594, and the ICER was $10,362. For a compliance assumption of only 33% (SMBG 3 times per day treatment costs and once per day HbA1C improvement vs no SMBG), the difference in QALYs was 0.103 and the difference in total costs was $2952. These differences resulted in an ICER of $28,676 per QALY gained.
CONCLUSIONS
The CORE Diabetes Model was used to simulate the cost effectiveness (and several related outcomes) of SMBG at frequencies of 1 and 3 times per day for patients with T2DM taking OAD medications. The strengths and limitations of the model, as well as of the studies upon which present simulations were based, have been discussed in previous publications.13,23,50
Results showed that a portion of the increased costs associated with SMBG were offset by reductions in the cumulative incidence of several diabetes-related complications and associated costs, as well as by modest increases in QALYs. The greatest reduction of risk (for 3 times per day relative to no SMBG) was associated with end-stage renal disease. The relative risk for (hypothetical) patients who monitor 3 times per day was 0.616. Although this complication had a smaller overall incidence compared with most others examined (8.724% of the simulated population at end point for no SMBG), its clinical and economic impact can be substantial.51
As others have noted, several factors may contribute to the relatively modest effects typically found for SMBG in patients taking OADs. SMBG effects on HbA1C must be considered to be indirect, with no clear understanding of how the use of SMBG results in improved HbA1C (eg, Did patients’ selfmanage timing/dose of medication? Did they report monitoring results to clinicians who modified prescribed regimens?)13,22,52 As Karter et al13 have recently suggested, pathways are likely to vary on an individual basis, with both representing potentially important benefits of SMBG.
In both of the present comparisons, use of SMBG was associated with increased total direct costs. However, the base case ICERs, for both SMBG once per day vs no SMBG and SMBG 3 times per day vs no SMBG, were well within the range considered to represent good value for money in the United States.49 Baseline results showed sensitivity to the time horizon considered. This finding is consistent with the nature of diabetes modeling; longer time horizons are generally necessary to capture the development of key complications and thus reflect the overall value of an intervention or a management tool.24 Despite this, ICERs for both SMBG regimens remained below $30,000, even with the very short time horizon of 5 years. The ICER for SMBG 3 times per day was less than $600 over a 10-year time horizon. Moreover, this cost-effectiveness estimate can be considered conservative in the sense that a relatively large degree of variability in patient response was assumed.
As is the case for all studies, several limitations are relevant in interpreting present results. The patient cohort for this simulation was based on a large group of SMBG “new users” from a longitudinal study, and response to increasing SMBG frequency in that study was greatest for this subpopulation. The magnitude of present treatment effects should be interpreted within the context of this patient subpopulation. Another factor that influences the results of any cost-effectiveness analysis is the cohort definition. For this study, the cohort had an average illness duration of 12 years and a baseline HbA1C of 8.6%. If patients had represented a “less severe” or a “more severe” clinical cohort, results could be expected to differ from those obtained in the present study. In general, SMBG has been found to be somewhat less costeffective for patients with T2DM who are on a diet-andexercise regimen only (ie, earlier in disease progression), and more cost-effective for individuals who require the use of insulin.25
Another important point is that for the base case simulations, compliance was assumed to be 100%, even for SMBG at 3 times per day. Thus, the theoretical patient population is likely to most closely resemble what has been described as motivated patients who have been appropriately educated in the use of SMBG, and who are likely to exhibit good self-care practices and relatively healthy lifestyles. It follows, then, that the benefit of SMBG in clinical settings may be increased by better integrating SMBG practice into an overall program of health education and therapeutic decision making.13
As expected, compliance rates less than 100% increased ICERs in the present study. However, the 66% compliance scenario ICER was only minimally higher than the ICER for the base case. Both the 66% and 33% compliance scenarios represent very conservative analyses in that they included the assumption that patients would continue to purchase enough strips to monitor 3 times per day, even though they would continue to monitor two thirds or even one third of the time. Compliance with healthcare interventions and management tools has become an important topic, and several researchers have attempted to assess SMBG compliance.25,53 One of the most robust predictors of decreased SMBG “compliance” is the presence of environmental barriers such as lack of insurance coverage for monitoring supplies.53,54
A final study caveat to be mentioned is that economic outcomes were defined as direct medical expenditures. Not assessed were economic impacts of temporary incapacity, long-term disability, or mortality-related productivity losses. Regarding assessments of direct costs (for diabetes as well as other disease states), no single comprehensive source of data is available.2 It is necessary to draw upon multiple sources having different levels of details regarding service utilization and various combinations of charges and reimbursements. Future work will benefit from efforts to standardize cost definitions and address their impact on cost-effectiveness evaluations.
This study was intended to contribute to the growing body of clinical and policy research on the long-term value of SMBG for patients with T2DM taking OADs. According to the ADA, more intensive disease management and the advent of new technologies are key factors for reducing health problems caused by diabetes, substantially improving the quality of life for patients and their families, and reducing national expenditures for healthcare services.2
The overall value of SMBG in the scenarios modeled was based on modest increases in glycemic control (associated with SMBG frequency), and partial offsets of SMBG expenditures through projections of complication cost reductions. Although the potential effect of acquisition costs could be nontrivial if applied to a very large patient population, the present analyses showed SMBG at both 1 and 3 times per day to be cost-effective management regimens for patients with T2DM being treated with OADs within the US payer system.
We are grateful for the assistance of Andrew J. Karter, PhD, of Kaiser Permanente, Oakland, CA, in providing standard deviations for HbA1C values used in this analysis.
Author Afflilations: From the Division of Health Economics and Outcomes Research, IMS Consulting Services, Noblesville, IN (SLT, MEM).
Funding Source: This study was funded by LifeScan, a Johnson & Johnson Company.
Author Disclosure: The authors (SLT, MEM) received payment for their involvement in the preparation of this manuscript. A portion of this work was included in a podium presentation at the ISPOR 9th European Congress, Copenhagen, Denmark, October 28-31, 2006. A separate but related analysis was presented in poster format at the American Diabetes Association 67th Annual Meeting & Scientific Sessions, Chicago, IL, June 22-26, 2007.
Authorship Information: Concept and design (SLT, MEM); analysis and interpretation of data (SLT, MEM); drafting of the manuscript (SLT); critical revision of the manuscript for important intellectual content (SLT, MEM); statistical analysis (SLT); and supervision (MEM).
Address correspondence to: Sandra L. Tunis, PhD, Health Economics and Outcomes Research, IMS Consulting Services, 14701 Cumberland Rd, Ste 107, Noblesville, IN 46060. E-mail: stunis@us.imshealth.com.
1. US Department of Health and Human Services, Centers for Disease Control and Prevention. National Diabetes Fact Sheet: General Information and National Estimates on Diabetes in the United States. 2005. Atlanta, GA, Centers for Disease Control and Prevention.2. American Diabetes Association: Economic Costs of Diabetes in the U.S. in 2002. Diabetes Care. 2003;26(3):917-932.
4. Intensive Blood-Glucose Control with Sulphonylureas or Insulin Compared with Conventional Treatment and Risk of Complication in Patients with Type 2 Diabetes (UKPDS 33). UK Prospective Diabetes Study (UKPDS) Group. Lancet. 1998;352(9131):837-853.
6. Wagner EH, Sandhu N, Newton KM, McCulloch DK, Ramsey SD, Grothaus LC. Effect of Improved Glycemic Control on Health Care Costs and Utilization. JAMA. 2001;285(7):182-189.
8. Menzin J, Boulanger L, Langley-Hawthorne C, Cavanaugh R, Friedman M. Potential short-term economic benefits of improved glycemic control. Diabetes Care. 2001;24(6):24-51.
11. Bergenstal RM, Gavin JR III.The role of self-monitoring of blood glucose in the care of people with diabetes: report of a global consensus conference. Am J Med. 2005;118(suppl. 9A):1S-6S.
13. Karter AJ, Parker MM, Moffet HH, et al. Longitudinal study of new and prevalent use of self-monitoring of blood glucose. Diabetes Care. 2006;29(1):1-7.
15. Karter AJ, Ackerson LM, Darbinian JA, et al. Self-monitoring of blood glucose levels and glygemic control: The Northern California Kaiser Permanente Diabetes Registry. Am J Med. 2001;111(1):1-9.
17. Davis WA, Bruce DG, Davis TME. Is self-monitoring of blood glucose appropriate for all type 2 diabetic patients? The Fremantle Diabetes Study. Diabetes Care. 2006;29(8):1764-1770.
19. Welschen LM, Bloemendal E, Nijpels G, et al. Self-monitoring of blood glucose in patients with type 2 diabetes who are not using insulin: a systematic review. Diabetes Care. 2005;28(6):1510-1517.
21. Jansen JP. Self-monitoring of glucose in type 2 diabetes mellitus: a Bayesian meta-analysis of direct and indirect comparisons. Curr Med Res Opin. 2006;22(4):671-681. 22. Davidson MB. Counter point: self-monitoring of blood glucose in type 2 diabetic patients not receiving insulin: a waste of money. Diabetes Care. 2005;28(6):1531-1533. 23. Palmer AJ, Roze S,Valentine WJ, et al. Validation of the CORE diabetes model against epidemiological and clinical studies. Cur Med Res Opin. 2004;20(suppl 1):S27-S40.
26. Centers for Disease Control and Prevention (CDC). National Center for Health Statistics (NCHS). National Health and Nutrition Examination Survey (NHANES) Data. Hyattsville, MD: U.S. Department of Health and Human Services, Center for Disease Control and Prevention, 2000.
28. Harris MI. Health care and health status and outcomes for patients with type 2 diabetes. Diabetes Care. 2000;23(6):754-758.
31. Brändle M, Zhou H, Smith BR, et al.The direct medical cost of type 2 diabetes. Diabetes Care. 2003;26(8):2300-2304.
33. O’Brien JA, Patrick AR, Caro J. Estimates of direct medical costs for microvascular and macrovascular complications resulting from type 2 diabetes mellitus in the United States in 2000. Clin Ther. 2003;25(3):1017-1038.
35. Shearer A, Scuffham P, Gordois A, Oglesby A. Predicted costs and outcomes from reduced vibration detection in people with diabetes in the US. Diabetes Care. 2003;26(8):2305-2310.
37. Drug Topics Redbook. Medical Economics Company (Ed.). Montvale, NJ, Thomson PDR, 2004.
39. Kantor J, Margolis DJ. Treatment options for diabetic neuropathic foot ulcers: a cost-effectiveness analysis. Dermatol Surg. 2001;27(4):347-351.
41. Gold MR, Siegel JE, Russell LB, Weinstein MC. Cost-Effectiveness in Health and Medicine. New York: Oxford University Press; 1996.
43. Tengs TO,Wallace A. One thousand health-related quality-of-life estimates. Med Care. 2000;38(6):583-637.
45. Carrington AL, Mawdsley SK, Morley M, Kincey J, Boulton AJ. Psychological status of diabetic people with or without lower limb disability. Diabetes Res Clin Pract. 1996;32(1-2):19-25.
47. Halpern EF,Weinstein MC, Hunink MG, Gazelle GS. Representing both first- and second-order uncertainties by Monte Carlo simulation for groups of patients. Med Decis Making. 2000;20(3):314-322.
49. Hark DB, Simons TA. Economics and cost-effectiveness in evaluating the value of cardiovascular therapies. Fundamentals of economic analysis. Am Heart J. 1999;137(5):S38-S40.
51. Joyce AT, Iacoviello JM, Nag S, et al. End-stage renal disease-associated managed care costs among patients with and without diabetes. Diabetes Care. 2004;27(12):2829-2835.
53. Vincze G, Barner JC, Lopez D. Factors associated with adherence to self-monitoring of blood glucose among persons with diabetes. The Diabetes Educ. 2004;30(1):112-125.