To assess the cost-effectiveness of Roux-en-Y gastric bypass for treating type 2 diabetes mellitus (T2DM) in the United States compared with standard medical management, using clinical data from a prospective observational study conducted at an academic medical center.

Our study used a predictive health economic model (the CORE Diabetes Model) to project the long-term costs and clinical effectiveness of Roux-en-Y gastric bypass as a treatment for T2DM using the prospective observational study as the basis for our clinical effectiveness assumptions.

The CORE Diabetes Model used Monte Carlo simulation with tracker variables to estimate the lifetime costs and clinical outcomes of Rouxen-Y gastric bypass compared with standard medical management of obese T2DM patients. Sensitivity analyses were performed on key clinical assumptions, discount rates, and shorter time horizons.

The base-case scenario yielded an incremental cost-effectiveness ratio (ICER) of $21,973 per quality-adjusted life-year (QALY) gained. In sensitivity analyses, shortening the time horizon to 5 and 10 years and excluding the negative impact of increased body mass index on the patient’s quality of life had the greatest adverse impact on the ICERs (ie, higher cost per QALY).

Under base-case assumptions, Roux-en-Y gastric bypass is cost-effective in the treatment of T2DM in the United States with an ICER below $50,000 per QALY gained. Sensitivity analyses indicated that bariatric surgery is not cost-effective over shorter time horizons, or if the negative quality-of-life impact of increased body mass index is ignored.

A predictive health economic model (the CORE Diabetes Model) was used to project the longterm costs and clinical effectiveness of bariatric surgery as a treatment for type 2 diabetes mellitus.

Our study demonstrated that compared with medical management, the Roux-en-Y gastric bypass procedure is cost-effective under very conservative assumptions for procedure costs and complication rates/costs, using procedure-related and follow-up data from the University of Minnesota.

Results for the analysis were robust under most scenarios observed, with the exception of shorter time horizons or when the quality-of-life impact of losing weight was removed.

Obesity is a major independent risk factor for type 2 diabetes mellitus (T2DM), an effect thought to occur through increased insulin resistance of cells.

 Nearly one-third of the nonpregnant adult population (age ≥20 years) in the United States is obese (defined as having a body mass index [BMI] ≥30 kg/m2),

 and about one-quarter of obese persons have T2DM.

 Conversely, about 8% of the US population has T2DM,

 and more than half of the patients with diabetes (both type 1 and type 2) are obese.

 Together, these 2 conditions impose an enormous burden on patients, caregivers, and society as a whole. The total cost of obesity has been estimated at $155 billion, including $60 billion in direct medical costs (adjusted to 2007 price levels from an estimate for 1998)

 and $95 billion in indirect costs (lost productivity, again adjusted to 2007 price levels from an estimate for 1995).

 Similarly, the total cost of T2DM in 2007 was an estimated $174 billion, including $116 billion in direct medical costs and $58 billion in indirect costs.

In recent years, bariatric surgery—mainly gastric bypass, usually the Roux-en-Y type, but also adjustable gastric banding, and vertical banded gastroplasty&mdash;has increasingly become recognized as a highly effective alternative for achieving major weight reduction for obese patients.

 Moreover, recent studies have demonstrated that patients with diabetes who have undergone bariatric surgery also experienced major reductions in blood glucose levels, some sufficient to suggest remission of diabetes mellitus.

 However, bariatric surgery is not without its own risks, including some potentially serious complications,

; consequently, candidates for bariatric surgery must be carefully screened. Practice guidelines suggest that bariatric surgery should be considered only for patients with a BMI ≥40 kg/m2 (35 kg/m2 if the patient has major comorbidities such as T2DM) after failure of a 1-year course of well-conducted medical treatment.

 Previous studies have demonstrated the cost-effectiveness of bariatric surgery, but most have included nondiabetic obese patients in their study populations.

 Our study used an established health economic model and prospective observational data from an academic medical center in the United States to assess the long-term costeffectiveness and clinical outcomes of bariatric surgery compared with standard medical management of T2DM.

The CORE Diabetes Model (CDM) has been described and validated in 2 separate publications and is consistent with recently published American Diabetes Association modeling guidelines and principles.

 The CDM is designed to predict the development and progression of type 1 or type 2 diabetes over long time horizons (≥5 years) using the best published clinical and epidemiologic data available. The model has a standard Markov structure, combined with Monte Carlo simulation and tracker variables, which allows for the development and progression of multiple complications within an individual patient, while at the same time overcoming the memory-free properties of basic Markov models. The CDM design includes 16 submodels that simulate diabetes-related complications and nonspecific mortality.

 Transition probabilities and risk adjustments for the CDM were derived from published resources and have been detailed in previous reports.

 The CDM was validated through 66 separate analyses, including both second-order and third-order validation exercises and is fully detailed elsewhere.

Data on the effectiveness of bariatric surgery were drawn from a prospective observational study conducted at an academic medical center in the United States (Minnesota cohort; unpublished data, University of Minnesota Medical Center, Minneapolis). From January 2001 through May 2007, 2223 consecutive patients underwent Roux-en-Y gastric bypass surgery, of whom 567 (25.5%) had previously been diagnosed with either T2DM or prediabetes. Several clinical end points were measured at varying times before and after surgery (minimum duration of follow-up was 11 months, maximum was 80 months). These included BMI, glycosylated hemoglobin (A1C), lipid parameters (total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglycerides), systolic blood pressure, and use of medications for diabetes (both oral and insulin), hypertension (angiotensin-converting enzyme inhibitors and angiotensin receptor blockers), and dyslipidemia (statins), as well as aspirin for prevention of cardiovascular disease (CVD). Of the 567 bariatric surgery patients with T2DM, 204 (36.0%) had complete data on all end points needed for simulation of future clinical and economic outcomes (unpublished data, University of Minnesota Medical Center). We performed additional analyses for those with follow-up data available (n = 204) compared with those Roux-en-Y gastric bypass patients without end-point follow-up data (n = 363). Compared with the patients who had follow-up data available, the patients without follow-up end-point data (n = 363) were younger (46.6 vs 50.1 years, 

<.001), had higher baseline low-density lipoprotein cholesterol (107.2 vs 96.9 mg/dL, 

<.001), and had a shorter preoperative duration of T2DM (72.5 vs 104.5 months, 

<.001) (unpublished data, University of Minnesota Medical Center). The sex, preoperative BMI and weight, A1C, and systolic blood pressure were similar between the 2 groups of patients with T2DM or prediabetes who had Rouxen-Y gastric bypass (unpublished data, University of Minnesota Medical Center).

The Minnesota cohort demographic and baseline clinical characteristics, plus other data used in the standard “US medical management of diabetes” arm of the CDM (drawn from the literature on diabetes and obesity, as summarized elsewhere

), were used in both the bariatric surgery cohort and the medical management cohort (

). Changes from before and after surgery on the clinical measures listed above constituted the impact of surgery in the bariatric surgery cohort (

). Changes in the control cohort over time on those same measures were based on standard algorithms derived from the literature on diabetes and its complications, and summarized elsewhere.

 For modeling purposes, we made no assumption with respect to weight gain after Roux-en-Y gastric bypass because of lack of data and assumed this value to be zero. We assumed that A1C and systolic blood pressure values would increase based on values obtained from the United Kingdom Prospective Diabetes Study (UKPDS),

 while lipid values would increase along the same curve observed in the Framingham Heart Study.

Patients in the bariatric surgery observational study were relatively young (mean age 50.1 years, with only 11.8% over age 60 years), predominantly female (77.9%), and Caucasian (83.5%) (Table 1). On average, they had been diagnosed with T2DM or prediabetes for 104 months (8.7 years) and were followed for a mean of 27.6 months (2.3 years). Their baseline BMI scores were high (mean 48.4, with only 12.8% having a BMI <40), but their baseline scores on other key end points were not as high as those of patients in other studies of T2DM (mean A1C of 7.7%, mean systolic blood pressure of 137.2 mm Hg, and mean low-density lipoprotein cholesterol of 96.9 mg/dL).

Adverse Effects of Bariatric Surgery and Complications of Diabetes Although some data on the incidence of various adverse effects of bariatric surgery were available in these observational data, more comprehensive data were available from previously published studies of bariatric surgery (

 Although the patient populations in those studies included nondiabetic obese patients, the complications of bariatric surgery may not differ substantially between diabetic and nondiabetic patients. Costs and Utilities for Bariatric Surgery and Medical Management of Diabetes The analysis assumed a third-party payer perspective. Direct medical costs (

) for estimating quality-adjusted life-years (QALYs) for events and states associated with medical management of diabetes in the CDM were drawn from T2DM studies previously detailed elsewhere.

 The increase in overall utility for decreasing BMI associated with bariatric surgery for T2DM patients came from the Cost of Diabetes in Europe—type 2 (CODE-2) study.

 The coefficient for each unit decrease in BMI increases the overall utility score by 0.003813 and was based on the CODE-2 study from Europe.

Costs associated with bariatric surgery were derived from previously published studies,

 as were health-state utilities associated with bariatric surgery.

 In those studies, cost and utility/disutility estimates were reported separately for early onset (eg, within 30 days of surgery) and late onset (more than 30 days and up to 1 year after surgery) for each complication of bariatric surgery. However, the structure of the CDM required that a single estimate be entered for the cost and the utility of any such complication. Accordingly, a weighted average of the “early” estimate and the “late” estimate for the cost and utility for each complication was computed by multiplying the risk of each early and late complication (see eAppendix B)

by the cost estimate for each early and late complication to arrive at a single cost for any complication, and a cumulative risk for any complication. These composite estimates for each complication were then further averaged across all complications. The resulting composite estimates are detailed in Table 2 (cost) and in eAppendix C. All cost figures were inflated to 2007 dollars using the Consumer Price Index for All Urban Consumers,

 which yields a more conservative estimate than the Medical Care component of the same index.

The model was run over a 35-year period, consistent with current guidelines, which recommend that the time horizon be sufficient to capture the development of long-range disease complications.

 Costs and clinical outcomes were both discounted at 3% per annum, also in accordance with published US recommendations.

Exploratory simulations were run on shorter time horizons of 5 and 10 years and annual discount rates of 0% and 6%. Additional sensitivity analyses were performed on the following clinical and economic parameters: using the actual costs associated with bariatric surgery at the site that provided the clinical data on bariatric surgery, as this estimate was much lower than the published national data we used in the base case; excluding the negative impact of increased BMI on the patient’s quality of life; excluding the effects of lipid parameters; weight gain

 after bariatric surgery; reducing the effect of bariatric surgery on A1C levels by 25%; decreasing the A1C decay from 0.15% per year from UKPDS to 0.016% per year over the first 6 years and returning to the default diabetes decay rate of 0.15% per year thereafter; and decreasing the overall complication rate for bariatric surgery by 25% (from 22.6% to 16.9%) and 50% (from 22.6% to 11.3%).

A nonparametric bootstrapping technique was used to explore uncertainty in clinical and cost outcomes for the CDM simulations.

 In summary, each transition probability used in the CDM was simulated by applying first-order Monte Carlo simulation techniques to provide a point estimate for each parameter to be used in the second-order Monte Carlo simulation technique.

 The resampling method was then applied to each parameter estimate obtained in the first-order Monte Carlo results with costs and outcomes calculated for 1000 theoretical patients, with each patient going through the model 1000 times. The mean costs and outcomes then were calculated from these simulations. The percentages of joint distributions falling within a preconceived  cost-effectiveness range were calculated and the data plotted into a scatter plot and cost-effectiveness acceptability curve. This basic procedure was performed on the base-case simulation and repeated for all sensitivity analyses.

Life Expectancy and Quality-Adjusted Life-Years 

The base-case analysis showed that compared with medical management of T2DM, bariatric surgery improved life expectancy, both unadjusted and adjusted for patient quality of life (

). The mean discounted life expectancy for bariatric surgery was 11.54 years, compared with 10.87 years for medical management of T2DM, representing an increase of 0.67 year. Undiscounted life expectancy for bariatric surgery was 15.94 years, compared with 14.66 years for medical management of T2DM. In terms of discounted QALYs, the mean for bariatric surgery was 6.78, compared with 5.88 for medical management of diabetes, representing an increase of 0.90 QALY.

Direct Medical Costs and Cost-Effectiveness

The survival improvements with bariatric surgery compared with standard medical management of diabetes were achieved at increased direct medical costs, but at an acceptable level of cost-effectiveness (Table 3). Mean lifetime direct medical costs for bariatric surgery were $83,482 per patient, compared with $63,722 per patient for medical management of diabetes, representing an increase of $19,760. The highest costs in both cohorts were those associated with CVD, which were higher for the medical-management cohort ($37,824) than for the bariatric surgery cohort ($34,811) and represented an 8% decrease in CVD-related costs. Indeed, costs were higher in the medical-management cohort than in the bariatric surgery cohort for all components except those associated with diabetic foot ulcer ($5776 vs $5915). The resulting overall incremental cost-effectiveness ratio (ICER) for bariatric surgery was $29,676 per life-year gained and $21,973 per QALY, well under the standard and perhaps stricter guideline for costeffectiveness in the United States of $50,000.

The incremental cost-effectiveness scatter plot displays the difference in mean costs plotted against the difference in mean life expectancy between bariatric surgery and standard medical management of T2DM for 1000 patients (

). The majority of points in this scatter plot are in the upper-right quadrant, indicating that bariatric surgery was both more costly and more effective than standard medical management. When the scatter plot was converted into cost-effectiveness acceptability curves (

), bariatric surgery had a 74% probability of being cost-effective at or below $50,000 per life-year gained and an 84% probability of being cost-effective at or below $50,000 per QALY compared with medical management, using the base-case assumptions.

Sensitivity analyses using the shorter time horizon of 10 years had the greatest impact on the cost-effectiveness of bariatric surgery compared with standard medical management of T2DM, yielding a much higher ICER of $122,001 per QALY (

). Using the even shorter time horizon of 5 years resulted in a loss of 0.042 QALY (presumably due to the shortterm effects of surgery, not yet offset by its long-term benefits), and a subsequent dominated strategy. The only other sensitivity analysis that increased the ICER above the US standard guideline

 of cost-effectiveness ($50,000 per QALY) was exclusion of the negative impact of increased BMI on the patient’s quality of life, yielding an ICER of $69,313 per QALY, demonstrating the sensitivity and impact of weight loss on an obese T2DM patient’s overall well-being.

The results of our study suggest that bariatric surgery can lead to positive  clinical impacts on T2DM at a reasonable additional cost, relative to standard medical management. These positive clinical effects of bariatric surgery could mean a lower incidence of long-term diabetic complications, reduced long-term treatment costs, and improved QALYs for T2DM patients in the United States. These results were robust over a wide range of clinical and economic assumptions, including discount rates, reduced effects on A1C, lipid effects, and weight gain

 after Roux-en-Y gastric bypass. The ICERs for the base-case and most sensitivity analyses fell below $50,000 per life-year gained, a level that may be considered cost-effective in the United States.

 Only shorter time horizons (5 and 10 years) and exclusion of the impact of increased BMI on the patient’s quality of life yielded ICERs above that level.

The chief limitation of the study is the lack of clinical data directly comparing bariatric surgery with standard medical management of diabetes as we assumed that medically managed patients would stay at the same baseline parameters as the bariatric surgery cohort and worsen over time along standard clinical paradigms available from the literature and programmed into the CDM (eg, UKPDS). Furthermore, the clinical data on the effects of bariatric surgery on diabetesrelated end points were drawn from only 1 academic medical center in the United States. The CDM utilizes data from credible sources to calculate epidemiologic risk functions. However, many of the inputs for our analysis came from the University of Minnesota triple end-point study (unpublished data, University of Minnesota Medical Center, Minneapolis), potentially limiting full generalizability. These facts may diminish the potential contribution of risk factors for which available data are currently sparse. Our analysis also excluded the potential added costs of skin reduction surgery, skin infections, and other complications because of lack of data on these outcomes and accompanying costs.

Inclusion of only those patients with complete data on all parameters needed for the model may have biased the study results in favor of the active treatment (here, bariatric surgery), similar to using only completers in clinical trials rather than all randomized or treated patients (intention to treat). In both cases, the included patients may be more likely to respond favorably to the study treatment.

The University of Minnesota triple end-point study did not collect complete information on the costs of surgical adverse events and Roux-en-Y gastric bypass surgery costs. Therefore, we utilized published literature to address this data gap. Also, Roux-en-Y gastric bypass complications and costs were assumed to occur only in the first year after surgery, consistent with the published literature.

 Reanalysis of the University of Minnesota cohort found a crude Roux-en-Y gastric bypass complication rate of 12.7% (26/204) up to 30 days postoperatively for any complication related or not to Roux-en-Y gastric bypass, increasing to 25.0% (51/204) at 90 days, which is consistent with the published data we used for these rates (22.9% overall complication rate) in our analysis.

Our analysis may underestimate the cost-effectiveness of weight reduction in patients with T2DM by leaving out the positive effects of weight loss on other comorbid conditions not directly assessed by the CDM. Gilmer and colleagues

 found that CVD, hypertension, and depression more strongly predicted future costs than reductions in A1C for adults with diabetes, suggesting that efforts to improve glycemic control, CVD, hypertension, and depression may have a more substantial financial impact on diabetes than efforts to improve only glycemic control. Our results did not include the potential ameliorating effects on depression in T2DM for patients undergoing bariatric surgery, thereby making the procedure potentially more cost-effective, as our analysis focused primarily on direct medical complications of T2DM.

Lastly and perhaps most importantly, we based all of our modeling results on continuation of a 2.3-year observational study, which in T2DM is a very short period of follow-up. Future studies designed to follow Roux-en-Y gastric bypass patients longer will help bridge the gap between what is known and our modeled outcomes.

This study has demonstrated that under our base-case assumptions, bariatric surgery provides good value for the money compared with standard medical management of T2DM, with an ICER of $21,973 per QALY gained. When assumptions were varied in sensitivity analyses (reduced effects on A1C, exclusion of lipid effects, lower and higher discount rates, and lower costs of treatment as observed at the medical center where bariatric surgery was performed), the ICERs remained under $50,000 per QALY in most cases. Only when the time horizon was greatly reduced and the quality-of-life impact of increased BMI was excluded did the ICERs exceed that standard guideline. These results can provide managed care formularies and other healthcare payers with important information on the economic value of bariatric surgery in treating T2DM in the United States.

The authors wish to thank Dr Sandra Tunis for her invaluable contributions to this study.

Articles

DIABETES FOCUS

A predictive health economic model indicated that Roux-en-Y gastric bypass is cost-effective in the treatment of type 2 diabetes mellitus compared with medical management.

Cost-Effectiveness of Roux-en-Y Gastric Bypass in Type 2 Diabetes Patients

To estimate the direct and indirect costs of type 2 diabetes  mellitus (T2DM) in China in 2007 and project these costs for the year 2030, and to examine and compare the benefits of selected interventions. 

Annual direct costs of medical and nonmedical care and indirect costs of income losses were estimated through case calculation of data from a cross-sectional survey carried out in 4 major Chinese cities from March 2007 to

 The subjects were consecutively recruited T2DM outpatients and inpatients from 20 secondary and tertiary hospitals using selection probability proportional to size sampling. We combined the existing data from  cost-effectiveness studies into the case estimation to examine the benefits of the observed regime of interventions for preventing and treating diabetes.

 Annual direct medical and direct nonmedical costs per case averaged $1320.90 and $180.80, respectively. The mean annual indirect costs of T2DM and its complications were estimated to be $206.10. Based on case numbers in 2007

and projected case numbers in 2030, the direct medical costs of T2DM and its complications were estimated to be $26.0 billion in 2007 and were projected to be $47.2 billion in 2030. 

The results indicated that T2DM consumes a large portion of healthcare expenditures and will continue to place a heavy burden on health budgets in the future. Preventive intervention, screening, and treatment strategies may effectively decrease the incidence and complications of diabetes and therefore save costs. 

The economic burden of type 2 diabetes mellitus (T2DM) makes it an important clinical and public health challenge in China, requiring policymakers to determine both the current and future economic burdens of the disease to formulate effective plans for resource allocation.

T2DM consumes a large portion of health expenditures and will continue to place a heavy burden on healthcare budgets in the future in China.

The excessive costs are largely due to treatment of complications; therefore, the importance of preventing complications through the use of more effective treatment regimens is obvious. 

Preventive interventions, especially lifestyle intervention, in high-risk populations may effectively decrease the incidence and complications of diabetes and therefore save costs.

Nearly 200 million people worldwide (or more than 5% of the global adult population) have diabetes, and this number will increase to 333 million (or 6.3% of the global adult population) by 2025.

 Diabetes affects persons of all ages as well as their families, while also placing heavy economic burdens on national economies and healthcare systems. Globally, the annual direct costs of diabetes, which include costs incurred for patient transport and care in addition to direct medical costs (DMCs), for people age 20 to 79 years are estimated to be at least $129 billion and as much as $241 billion or possibly more.

 The direct costs of diabetes consume from 2.5% to 15.0% of annual healthcare budgets, depending on local prevalence and the sophistication of available treatments. In 2025, diabetes care costs are anticipated to account for between 7% and 13% of the world’s healthcare budget.

In China, an estimated 23.46 million people currently have diabetes

; that number is predicted to increase to 42.30 million by 2030.

 Between 1996 and 2006, the prevalence of type 2 diabetes mellitus (T2DM) increased rapidly in urban China, from 4.58% to 7.67%, and was much higher in major cities (6.1%) than in small cities (3.7%) and rural areas (1.8%).

 A recent study estimated the overall annual direct economic burden of diabetes among China’s urban population in 2002 to be in excess of $2.44 billion.

 In 2003, the estimate was updated to $2.29 billion for the whole population based on data from the 2003 National Health Service Investigation.

 The annual per patient DMCs of healthcare associated with T2DM patients with complications were estimated to be $1798, compared with $484 for those without complications.

 The treatment of chronic diseases is managed by a 3-level hospital system in Chinese urban areas. Under that system, patients chose to visit primary, secondary, or tertiary hospitals on their own, and may overuse healthcare services by selecting unnecessary high-level hospitals for diabetes treatment; it was reported that 997 (6%) tertiary hospitals nationwide consumed 54.73% of China’s total healthcare expenditures.

Many of the costs associated with diabetes and its complications are preventable.

 A large number of interventions (eg, intensive blood glucose and blood pressure control, use of lipid-lowering agents, screening for and treating diabetic retinopathy, active care of feet) are known to be cost-effective, and many of these interventions also are cost-saving,

 although controversy remains regarding the significance of the effect of some strategies (eg, intense glucose control for prevention of microvascular complications).

 In recent years, 4 major trials of T2DM prevention in China,

 have demonstrated that intensive lifestyle interventions involving a combination of diet and physical activity can delay or prevent diabetes among persons at high risk.

The economic burden of diabetes makes it an important clinical and public health challenge. To formulate effective plans for resource allocation, it is necessary to determine both the current and future economic burdens of the disease. The present study provides estimates of these burdens for T2DM patients in China. Cross-sectional data drawn from surveys conducted in 4 Chinese cities were used to help to determine the preventable costs under selected alternative interventions.

We conducted a cross-sectional study in 4 major cities—Shanghai, Beijing, Guangzhou, and Chengdu&mdash;located in eastern, northern, southern, and western China, respectively. The eAppendix (available at 

Subjects were eligible for the study if they (1) met the 1999 World Health Organization diagnosis criteria for T2DM; (2) had received T2DM treatment for at least 1 year; (3) were age 18 years or older; (4) had lived in the city for at least 2 years; and (5) were willing and able to give written informed consent and complete the questionnaire interview.

 The eligible subjects included outpatients and inpatients. Patients in the outpatient group were recruited consecutively from the hospitals’ outpatient clinics from March 2007 to May 2007. Patients were categorized as inpatients if they were recruited from hospital wards from March 2007 to September 2007 using selection probability proportional to size sampling. Enrollment of inpatients involved 3 steps. First, using data from a previously published study that determined the proportions of complications associated with T2DM from a sample of 299 patients living in 7 Chinese urban areas, we obtained the proportion of inpatients with various complications.

 Second, we calculated the sample size of each inpatient group stratified by type of complication, using the proportions in the previous step. Finally, we recruited the subjects consecutively for each group until the predefined sample sizes were met.

The direct costs of illness are those expenditures used to purchase medical supplies and services. In this study, direct costs are further classified as DMCs and direct nonmedical costs. Direct medical costs include all expenditures for treating T2DM and any related complications, including copayment, diagnosis, treatment, diagnostic testing, prescription drugs, and medical supplies. Direct nonmedical costs include costs for services such as transportation for the patient and family members to clinics and costs for taking care of dependents. Indirect costs refer to lost income of patients and their family members, and costs for hiring nurses or care providers.

A complication was defined as an infrequent and unfavorable evolution of a disease or a health condition that was diagnosed after the onset of T2DM.

Annual DMCs were estimated based on payment amounts for outpatient services and hospitalization; annual direct nonmedical costs were obtained from the patient’s self-estimate; annual indirect costs were estimated based on sick leave days taken by patients and by family members caring for patients, average daily income in urban China, and payment for hiring nurses or care providers. Specifically, for outpatients, the annual DMC was computed as the DMC per outpatient visit multiplied by the number of outpatient visits in the past 6 months multiplied by 2 plus annual hospitalization cost. For inpatients, the annual DMC was computed as the annual DMC associated with outpatient visits plus the DMC per hospitalization multiplied by number of hospitalizations in the past 12 months. The currency was adjusted to US dollars using the exchange rate as of June 15, 2007 ($1 = 7.6948 Chinese Yuan).

Study coordinators who majored in clinical medicine or preventive medicine were recruited from each study site and trained by the investigators. The subjects were interviewed face-to-face in the hospitals using a survey designed by the School of Public Health at Fudan University. The survey included questions concerning patients’ demographics, diabetes characteristics, existing complications caused by T2DM, and treatment history, as well as selfestimations of the cost of T2DM and its complications. Written informed consent was obtained from all study subjects. The Ethics Committee of the School of Public Health at Fudan University approved the study.

All data were entered into a Chinese database (EpiData version 3.1; EpiData Association, Odense, Denmark) and transferred into SPSS 16 for statistic analyses (SPSS Inc, Chicago, IL). Categorical variables were presented as counts and percentages.

General Characteristics of the Study Population A total of 2054 subjects were recruited from March 2007 to September 2007. After 14 subjects were excluded for having less than 1 year of T2DM treatment history or not providing cost information, 1524 outpatients and 516 inpatients were eligible for analysis (

). The 2040 subjects ranged in age from 18 to 97 years (average age 64.2 years). More than 90% reported having some kind of medical insurance; about 70% reported a personal income below $260 per month. Among outpatients, 39.4% did not suffer complications; the median number of complications was 1 (range: 0-8). Of the 516 inpatient subjects, only 5.8% did not experience complications; the median number of complications was 3 (range: 0-10).

Because the cost data were skewed, medians and quartiles were reported together with means. The DMC for each hospitalization averaged $2294.10; the DMC per outpatient visit averaged $40.70 (

). Care for T2DM was associated with 7.3 ± 7.2 outpatient visits per outpatient in the past 6 months, and an average of 1.7 ± 1.4 hospitalizations for inpatients in the past 12 months. The DMC was calculated by taking into account the DMCs of the current visit and the number of outpatient visits, plus annual hospitalization costs in the past year; annualizing these sums yielded an estimated mean annual DMC of $1030.10. The corresponding sum for inpatients was $2309 per hospitalization.

Mean direct nonmedical costs were estimated to be $180.80 ($165 and $227.80 for outpatients and inpatients, respectively) annually. Using the 2007 urban China average per capita daily income of $10.87, the annual indirect costs of T2DM and its complications were $206.10, or $99.40 and $515.70 for outpatients and inpatients, respectively.

Economic Burden Estimation and Projection

We applied data from this sample to the Chinese population as a whole. 

 summarizes estimated national annual DMCs for subjects who had differing numbers of complications. For subjects with only 1 complication, more detailed subgroups are provided.

Assuming a prevalence of 23.46 million T2DM patients nationwide,

 the estimated national DMCs for T2DM and its complications were $26.0 billion per year, or 18.2% of China’s total health expenditures ($142.5 billion in 2007).

 Using an estimated prevalence of 42.3 million T2DM patients in the year 2030, annual DMCs were projected to be $47.2 billion. Annual direct nonmedical costs for T2DM and its complications in 2007 were estimated to be $4.0 billion and projected to be $7.2 billion in 2030. Thus, the total direct costs in 2007 were $30.0 billion, which exceeded the 2003 estimate of $22.9 billion.9 Similarly, indirect costs in 2007 were estimated to be $2.2 billion and were projected to be $4.0 billion in 2030. In total, the estimated economic cost of T2DM and its complications was $32.2 billion for 23.46 million T2DM patients in 2007 and projected to be $58.5 billion for 42.3 million T2DM patients in 2030. Estimated Benefits of Intervention for Preventing Diabetes and Its Complications

We examined the benefits of the observed regimen of interventions to prevent and treat diabetes in China (

). The World Bank determined that lifestyle interventions for preventing T2DM could reduce the incidence among persons at high risk by 35% to 58%.13 (High-risk persons were those with either impaired glucose tolerance or T2DM, as estimated from the current cross-sectional study. Impaired glucose tolerance was defined as 2-hour glucose levels of 140-199 mg/dL [7.8/11.0 mmol] on the venous plasma glucose tolerance test.) Assuming that 95% of individuals would adhere to the program, the lifestyle interventions could result in $8.6 billion to $14.2 billion saved in T2DM health expenditures in 2030. Alternative scenarios assuming that China had the same share of indirect costs (as part of the total costs) as the United States

 yield potential total costs savings of $11.4 billion to $18.9 billion and $44.3 billion to $73.4 billion in 2030, respectively. Similarly, if using the World Bank—recommended metformin interventions for preventing T2DM in 17.2 million individuals at high risk, the incidence may be reduced by 25% to 31%, resulting in potential cost savings of $6.1 billion to $7.6 billion in 2030. If the higher US and Latin American and Caribbean shares of indirect costs were used, the interventions would save a projected $8.2 billion to $10.1 billion and $31.6 billion to $39.2 billion, respectively.

Estimated Benefits of Screening for and Treating Diabetes and Its Complications

The effectiveness and benefits of screening for and treating diabetes and its complications vary greatly (

). Screening strategies to prevent T2DM among the general population may save $1.8 billion in 2030, while more specific screening or treatment strategies (ie, blood pressure control, annual screening for microalbuminuria, annual eye examination, and foot care in high-risk persons) may save even more. For example, annual eye examinations targeting 0.6 million individuals with serious vision loss may save $55 million, while foot care targeting 0.2 million persons at high risk of ulcers would save $64 million in 2030. In addition, glycemic control in persons with a glycosylated hemoglobin (A1C) value greater than 9% would reduce microvascular disease by 30% per 1% drop in A1C, thereby saving $1.2 billion in 2007 and $2.2 billion in 2030.

Although numerous cost-of-illness studies have been conducted on the estimated economic burden of diabetes in various countries, this is the first quantitative study to systematically estimate the current economic burden and project the future costs of T2DM in China. In light of increasing diabetes prevalence globally and within China, cost-of-illness studies are urgently needed to increase awareness and facilitate lobbying for resource allocation.

In China, the most recently published analysis—known as the National Health Service Investigation&mdash;estimated the cost of diabetes in 2003 to be $2.29 billion.

 This estimate, however, was obtained by national statistics data and failed to consider the burden incurred by complications, which may have been underestimated if the comorbidity of the various complications of diabetes was not considered. Another study conducted by Chen et al in 2002 estimated the urban burden from a relatively small sample of 299 patients living in 7 Chinese urban areas.8 In the current study, we attempted to estimate the proportions of comorbidity of the various complications associated with T2DM. The magnitude of the difference between the published figure and our estimate could be largely due to the inclusion of costs related to complications and the increase of the number of cases. Our estimate of DMCs was based on a separate calculation of subgroups with different complications, which may have increased the accuracy of the medical cost estimate. In addition, we applied data from the current samples to both urban and rural patients, which may have extended the gap between the estimates and the actual health expenditure. However, the gap primarily was caused by the fact that rural patients have worse affordability difficulties than urban patients, other than the willingness-to-pay burden.26 It may be reasonable to estimate economic burden in the whole population using the data of our samples.

We found that the proportion of direct health expenditures consumed by T2DM had been as high as 18.2%, although the total annual DMCs ($26.0 billion) were far less than those of Germany (€30.6 billion)

 Prior studies reported the following costs related to T2DM as percentages of total public health expenditures: 7.4% in Spain,

 Because the costs incurred by T2DM in China are proportionally higher than those of developed countries, there is an urgent need for prevention programs that reduce the risks and control the complications of T2DM in China. The medical service is particularly unaffordable to the Chinese patients, who have to pay for treatment out of their own pockets with large differences under different insurance plans.

We found that indirect costs accounted for 6.9% of diabetes- related total costs in China. Our calculation of indirect costs was based on self-estimates of production losses from patients and their families. By using production losses and premature mortality, studies in other countries

 showed that indirect costs constituted a much higher proportion of costs than our estimate, which may be partly due to the higher proportion of unemployed patients in China. An increase in accessibility to care may increase the direct costs related to diabetes, and if care is effective, this may reduce the mortality and rates of disability related to diabetes and hence reduce the economic burden of T2DM.

Type 2 diabetes mellitus and its complications are preventable, and the costs of preventing and treating diabetes can be reduced. Recent studies in diverse settings have shown that lifestyle changes and metformin interventions were effective in preventing T2DM in individuals at risk, such as those with impaired glucose tolerance.

 We assumed that the effectiveness of these interventions was the same in China as in developed countries but that the costs of interventions and other diabetes care were higher in developed than in developing countries. The China Da Qing Diabetes Prevention Study reported a 51% reduction in incidence as a result of lifestyle intervention in China,

 which was consistent with the World Bank’s range. Using this assumption, we found that both lifestyle and metformin interventions for preventing T2DM in China could result in substantial cost savings in anticipated health expenditures in 2030.

We projected that diabetes screening strategies for the general population would save $1.8 billion in 2030 by preventing the onset of T2DM, while more specific treatment strategies such as blood pressure control may save even more. The cost savings would result mainly because of the treatments’ significant health benefits and relatively low intervention costs.

The findings in this study may be subject to several limitations. First, the study subjects were either patients recruited from outpatient clinics at secondary and tertiary hospitals or patients admitted to those hospitals, which may limit the ability to generalize the results and overestimate the economic burden of T2DM. To obtain a more accurate estimate of T2DM burden in the healthcare setting of China, it would be preferable to conduct a community-based study in the future. Second, the cost data, especially for direct nonmedical costs and indirect costs, were based to some extent on patient recall, which may be subject to recall bias. The DMC data, however, were based primarily on medical history combined with billing information, which increased the accuracy of those estimates. The cost data for the previous 6 months also may not accurately reflect the cost data for the previous 12 months. Moreover, it is difficult to differentiate T2DM-related complications from comorbidities, particularly among the elderly, and it is possible that some patients were misdiagnosed and therefore stratified incorrectly. Finally, another limitation is that the projected results were based on a study of urban patients, who may have different disease burdens than rural patients. Further study is needed to cover the rural areas. In conclusion, T2DM-related treatment consumes a large portion of health expenditures. The excessive costs are largely due to the treatment of complications. As diabetes prevalence in China continues to grow in the coming years, diabetes costs will continue to weigh heavily on health budgets. However, diabetes interventions among high-risk populations have the potential for considerable cost savings. As seen in this study, excessive costs increase proportional to the number of complications, so the importance of preventing complications through the use of more effective regimens is obvious.

We would like to thank Brian D. Smith, MA, for preparing the manuscript. We also thank the following hospitals for their significant contributions to data collection: 301 Hospital, China-Japan Friendship Hospital, People’s Hospital (affiliated with Beijing University), Peking University Third Hospital, Haidian Hospital, and Fuxing Hospital in Beijing; Ruijin

Hospital, Shanghai First People’s Hospital, Changhai Hospital, Dongfang Hospital, and Minhang District Central Hospital in Shanghai; Zhongshan University Third Hospital, Nanfang Hospital, Guangdong Provincial People’s Hospital, and First People’s Hospital of Guangzhou City in Guangzhou; and Huaxi Hospital (affiliated with Sichuan University), Sichuan Province People’s Hospital, Chengdu First People’s Hospital, and Chengdu Seventh Hospital in Chengdu.

the School of Public Health (WW, CF, BX), Fudan University, Shanghai, China; the School of Health Studies and Nursing (WPM), Georgetown University, Washington, DC; the Department of Epidemiology & Biostatistics (SZ), Peking University, Beijing, China; the Department of Epidemiology (RL), Sichuan University, Chengdu, China; and the Department of Medical Statistics and Epidemiology (WC), Sun Yat-sen University, Guangzhou, China.

This study was sponsored by GlaxoSmithKline (China) Investment Co, Ltd.

The authors (WW, WPM, CF, SZ, RL, WC, BX) report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Concept and design (WW, WPM, CF, SZ, RL, WC, BX); acquisition of data (WW, CF, SZ, RL, WC, BX); analysis and interpretation of data (WW, WPM, CF, BX); drafting of the manuscript (WW, WPM, BX); critical revision of the manuscript for important intellectual content (WW, WPM, SZ, RL, WC, BX); statistical analysis (WW, CF); provision of study materials or patients (WW); obtaining funding (BX); administrative, technical, or logistic support (WW, SZ, RL, WC, BX); and supervision (WPM, BX).

Biao Xu, MD, PhD, MPH, Department of Epidemiology, Fudan University, 138 Yi Xue Yuan Rd, Shanghai 200032, China. E-mail: bxu@shmu.edu.cn.

. 3rd ed. Brussels, Belgium: International Diabetes Federation; 2006.

. Beijing, China: National Center for Disease Control and Prevention; 2006.

3. Wild S, Roglic G, Green A, Sicree R, King H. 

Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. 

4. Li LM, Rao KQ, Kong LZ, et al; The Technical Working Group of China National Nutrition and Health Survey.

 A description on the Chinese national nutrition and health survey in 2002 [in Chinese]. 

 Study on diabetes prevalence in urban China [in Chinese]. 

6. Xu L, Xie X, Wang S, Wang Y, Jonas JB. 

Prevalence of diabetes mellitus in China. 

Study on the epidemiological characteristics of diabetes mellitus and IGT in China [in Chinese]. 

 Assessing the impact of complications on the costs of type 2 diabetes in urban China [in Chinese]. 

 The study of economic burden of chronic non-communicable diseases in China [in Chinese]. 

Chinese Journal of Prevention and Control of Chronic Non-Communicable Diseases

10. Tang L, Chen X, Chen H, Zhao L, Hu S. 

The financing burden of treatment of diabetes II and its symptom in urban China [in Chinese]. 

 A summary analysis and some policy suggestion of the flows of total health expenditure in China [in Chinese]. 

12. Expert Committee on the Diagnosis and Classification of Diabetes Mellitus.

 Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. 

Treatment of type 2 diabetes mellitus and its complications places a heavy burden on healthcare budgets in China and will continue to do so.

Type 2 Diabetes Mellitus in China: A Preventable Economic Burden

Despite evidence that medication adherence can influence cost-effectiveness analysis (CEA) results, the extent to which published CEAs include adherence has not been fully characterized.

To characterize inclusion of patient adherence in CEAs of self-administered medications and to examine whether industry sponsorship affects adherence inclusion, because adherence exclusion might overstate the interventions’ costeffectiveness. 

Systematic review of the Englishlanguage medical literature published between 1998 and 2003 identified 177 original CEAs of self-administered medications. 

Two trained readers independently abstracted data. Adherence inclusion was estimated overall and by study characteristics. Predictors of inclusion were assessed with c2 tests and logistic regression.

Among 177 CEAs, 30.5% explicitly modeled adherence; of these, only half modeled adherence in both base-case and sensitivity analyses. Only 21% of studies performed sensitivity analysis on adherence; fewer than half of these provided sufficient information to determine the impact on results. Of the remaining 20 studies, 9 were sensitive to adherence. Adherence inclusion varied across clinical areas (

= .022). Only 30% of chronic anticoagulation studies, 52% of cardiovascular risk reduction studies, 38% of neuropsychiatric studies, and 32% of HIV antiretroviral studies considered suboptimal adherence. Among 128 CEAs that disclosed study sponsorship, adherence was included in 25.4% of industry-sponsored and 35.1% of non—industrysponsored studies (

Few CEAs modeled suboptimal medication adherence. As CEAs are meant to model “real world” costs and effects of interventions, investigators would do well to explicitly consider medication adherence in the future.

Suboptimal medication adherence remains pervasive in the US healthcare system, resulting in substantial adverse health and economic effects. Despite a growing body of evidence that adherence can influence cost-effectiveness analyses (CEAs), the extent to which published CEAs include adherence has not been fully characterized.

Fewer than one-third of published CEAs modeled suboptimal adherence. 

In the small subset of studies that varied adherence in sensitivity analyses, the impact on cost-effectiveness often was substantial. 

With payers and policymakers increasingly turning to these studies for guidance, failure to account for nonadherence may lead to suboptimal resource allocation strategies.

Medication adherence is perhaps the most important determinant of the therapeutic effectiveness of medications.

 Yet suboptimal adherence remains pervasive in the US healthcare system, resulting in substantial adverse health and economic effects.

 Overall, rates of nonadherence are high—fewer than 50% of patients with chronic diseases take their medications as prescribed.

 In turn, poor adherence is associated with disease progression, complications, avoidable hospitalizations, and death,

 as well as increased medical costs for some chronic diseases.

 Indeed, it has been estimated that suboptimal adherence is responsible for an estimated $177 billion in total direct and indirect health spending annually in the United States.

Given the substantial impact of adherence on health and spending, inclusion of adherence in economic evaluations may be critical for informing policymakers about the value of therapies in actual practice. Indeed, past studies have shown that adherence can influence the results and recommendations of cost-effectiveness analyses (CEAs).

 Despite the importance of adherence, however, the extent to which published CEAs consider it has not been fully characterized. Our objective was to examine the inclusion of patient adherence in CEAs of self-administered medications. Because the exclusion of adherence might overstate the cost-effectiveness of evaluated interventions, we also examined the relationship between pharmaceutical company sponsorship and inclusion of adherence.

Cost-effectiveness analyses compare alternative approaches to a health problem to determine the relative costs and benefits of each. Cost-utility analyses, the subset of CEAs with health benefits measured in quality-adjusted life-years (QALYs), represent the gold standard for conducting and reporting of CEAs in medicine.

 For the remainder of this article, we use CEA to refer to cost/QALY studies.

We previously reported on the development of a comprehensive registry of CEAs published in the public health and medical literature from 1976 through 1997.

 The Tufts cost-effectiveness analysis registry is continuously updated and maintained on the Internet as a free, public use resource (http://www.cearegistry.org). As part of the updates to this registry, we conducted a systematic review of the English-language medical literature published between 1998 and 2003. We searched MEDLINE for the following medical subject headings and text keywords: “qualityadjusted,” “quality-adjusted life year(s),” “QALY,” “adjusted life year(s),” “cost-utility,” and several variations of these terms. To identify potentially overlooked studies, our search findings were validated to those of the Health Economic Evaluation Database maintained by the British Office of Health Economics.

 Our search identified 2528 candidate articles published between 1998 and 2003. We then screened titles and abstracts to remove noneligible articles, such as methodologic and review articles, and studies that did not use cost/QALY as their main outcome measure. A final list of 568 published cost-utility analyses were included in the registry for the years 1998 through 2003.

Of the 568 cost-utility analyses, 226 had a medication component in the intervention or comparator. To restrict analyses to studies in which patient adherence was applicable, we excluded studies in which medications were administered by injection or infusion (n = 27), in an acute-care setting (n = 14), or by someone else (often the physician) for other reasons (n = 8). The final sample included 177 CEAs of self-administered medications (available at https://research.tufts-nemc. org/cear/related/ajmcappendix.pdf). Each article was reviewed by 2 independent readers, who abstracted select data elements from each article; consensus meetings were held to review and resolve discrepancies. We collected data on a wide variety of elements related to the methods, results, and quality of reporting in the article, along with data on study inclusion of adherence to therapies. In addition, we abstracted data on the source of funding for each study (when reported).

. Readers recorded whether medication adherence was (1) included in the base-case analysis only, (2) included in sensitivity analyses only, (3) included in both the base-case and sensitivity analyses, (4) mentioned in the manuscript but not included in analyses, or (5) not mentioned. If the results of sensitivity analyses on adherence were reported in the text, tables, figures, or an appendix, they were considered “sufficient” to judge the impact of adherence. Of studies with sufficient data, we report whether the authors describe the results as sensitive to adherence. In practice, adherence has many different definitions, measurement approaches, and even names (eg, compliance, persistence).

 For the purposes of this analysis, we included any form of adherence regardless of whether or how it was defined.

. Readers abstracted data from each study on the expected duration of intervention therapy, study sponsorship, and the clinical condition of interest. Intervention medications were classified as short term if therapy duration was expected to be less than 1 month. Study sponsorship was categorized as unknown if no funding source was listed, industry-sponsored if at least 1 funding source or 1 author’s affiliation was a pharmaceutical or medical device company, and non—industry-sponsored if all funding came from governments, foundations, or other nonindustry sources. Study settings included the United States, the United Kingdom, Canada, and an “other country” category that included any country that served as the CEA setting in 10 or fewer studies. Studies were grouped into the following clinical categories: cardiovascular risk factors and disease (CVD), cancers, HIV and AIDS, other infectious diseases, hepatitis, other gastrointestinal conditions,  musculoskeletal conditions (including osteoporosis), neurologic conditions, psychiatric conditions, pulmonary diseases, and an “other disease” category that included any clinical conditions examined in fewer than 5 CEAs. Additionally, a separate anticoagulation category was included because of the large number of CEAs published in this area. To assess whether the inclusion of adherence in CEAs has improved over time, we also created a variable indicating whether the study was published earlier (1998-2000) or later (2001-2003) in the 6-year study window.

A systematic literature review from 1998 to 2003 showed that few cost-effectiveness analyses of self-administered medications model suboptimal medication adherence.

September 2009

Cost-Effectiveness of Roux-en-Y Gastric Bypass in Type 2 Diabetes Patients

Type 2 Diabetes Mellitus in China: A Preventable Economic Burden

Patient Adherence: A Blind Spot in Cost-Effectiveness Analyses?

Patient-Centered Medical Home Demonstration: A Prospective, Quasi-Experimental, Before and After Evaluation

Suboptimal Identification of Obesity by Family Physicians

Are There Unintended Consequences of Step-Therapy Programs?

Effect of a Managed Care Disease Management Program on Diabetes Care

Prior Authorization to Improve Testing of Glycosylated Hemoglobin in a Managed Care Setting

Toyota Production System Quality Improvement Initiative Improves Perioperative Antibiotic Therapy

Diabetes Care Quality: Insurance, Health Plan, and Physician Group Contributions

Designing Programs for Populations with Chronic Care Needs: A Blanket or a Quilt?

Medicare Part D: Selected Issues for Plan Sponsors, Pharmacists, and Beneficiaries in 2009