Diabetes modeling

Cost-Effectiveness of a Diabetes Self-Management Education and Support Intervention Led by Community Health Workers and Peer Leaders: Projections From the Racial and Ethnic Approaches to Community Health Detroit Trial

OBJECTIVE

To simulate the long-term cost-effectiveness of a peer leader (PL)-led diabetes self-management support (DSMS) program following a structured community health worker (CHW)-led diabetes self-management education (DSME) program in reducing risks of complications in people with type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

The trial randomized 222 Latino adults with T2D to 1) enhanced usual care (EUC); 2) a CHW-led, 6-month DSME program and 6 months of CHW-delivered monthly telephone outreach (CHW only); or 3) a CHW-led, 6-month DSME program and 12 months of PL-delivered weekly group sessions with telephone outreach to those unable to attend (CHW + PL). Empirical data from the trial and the validated Michigan Model for Diabetes were used to estimate cost and health outcomes over a 20-year time horizon from a health care sector perspective, discounting both costs and benefits at 3% annually. The primary outcome measure was the incremental cost-effectiveness ratio (ICER).

RESULTS

Over 20 years, the CHW + PL intervention had an ICER of $28,800 and $5,900 per quality-adjusted life-year (QALY) gained compared with the EUC and CHW-only interventions, respectively. The CHW-only intervention had an ICER of $430,600 per QALY gained compared with the EUC intervention. In sensitivity analyses, the results comparing the CHW + PL with EUC and CHW-only interventions were robust to changes in intervention effects and costs.

CONCLUSIONS

The CHW + PL-led DSME/DSMS intervention improved health and provided good value compared with the EUC intervention. The 6-month CHW-led DSME intervention without further postintervention CHW support was not cost effective in Latino adults with T2D.

Cost-effectiveness of Community-Based Depression Interventions for Rural and Urban Adults With Type 2 Diabetes: Projections From Program ACTIVE (Adults Coming Together to Increase Vital Exercise) II

OBJECTIVE

We estimated the cost-effectiveness of the Program ACTIVE (Adults Coming Together to Increase Vital Exercise) II community-based exercise (EXER), cognitive behavioral therapy (CBT), and EXER+CBT interventions in adults with type 2 diabetes and depression relative to usual care (UC) and each other.

RESEARCH DESIGN AND METHODS

Data were integrated into the Michigan Model for Diabetes to estimate cost and health outcomes over a 10-year simulation time horizon from the health care sector and societal perspectives, discounting costs and benefits at 3% annually. Primary outcome was cost per quality-adjusted life-year (QALY) gained.

RESULTS

From the health care sector perspective, the EXER intervention strategy saved $313 (USD) per patient and produced 0.38 more QALY (cost saving), the CBT intervention strategy cost $596 more and gained 0.29 more QALY ($2,058/QALY), and the EXER+CBT intervention strategy cost $403 more and gained 0.69 more QALY ($585/QALY) compared with UC. Both EXER and EXER+CBT interventions dominated the CBT intervention. Compared with EXER, the EXER+CBT intervention strategy cost $716 more and gained 0.31 more QALY ($2,323/QALY). From the societal perspective, compared with UC, the EXER intervention strategy saved $126 (cost saving), the CBT intervention strategy cost $2,838/QALY, and the EXER+CBT intervention strategy cost $1,167/QALY. Both EXER and EXER+CBT interventions still dominated the CBT intervention. In comparison with EXER, the EXER+CBT intervention strategy cost $3,021/QALY. Results were robust in sensitivity analyses.

CONCLUSIONS

All three Program ACTIVE II interventions represented a good value for money compared with UC. The EXER+CBT intervention was highly cost-effective or cost saving compared with the CBT or EXER interventions.

The Community Diabetes Education (CoDE) program: cost-effectiveness and health outcomes

BACKGROUND

Limited evidence exists regarding the long-term effects of community health worker-led diabetes management programs on health outcomes and cost-effectiveness, particularly in low-income, ethnic minority populations.

PURPOSE

To examine the long-term cost-effectiveness and improvements in diabetes-related complications of a diabetes education and management intervention led by community health workers among uninsured Mexican Americans.

METHODS

Clinical data, changes in hemoglobin A1c over 12 months, and costs from an RCT of 180 uninsured Mexican Americans with type 2 diabetes conducted in 2006 were utilized for secondary analyses in 2012. Simulation modeling was used to estimate long-term cost and health outcomes using the validated Archimedes Model. The absolute differences for the incremental cost-effectiveness ratios and cumulative incidence of diabetes-related complications were derived by comparing intervention and control groups.

RESULTS

During a 20-year time horizon, participants who received the intervention would be expected to have significantly lower hemoglobin A1c levels (p<0.001), fewer foot ulcers (p<0.001), and a reduced number of foot amputations (p=0.005) in comparison with a control group receiving usual medical care. An incremental cost-effectiveness ratio of $355 per quality-adjusted life year gained was estimated for intervention participants during the same time period.

CONCLUSIONS

A simulated clinical trial suggests that a community health worker-led diabetes intervention is a cost-effective way to reduce diabetes-related complications for uninsured Mexican Americans during a 20-year horizon in comparison to usual medical care.

The contributions of prevention and treatment to the decline in cardiovascular mortality: lessons from a forty-year debate

Mortality from coronary heart disease in the United States has fallen 60 percent from its peak in the mid-1960s. Cardiologists and epidemiologists have debated whether this decline reflects better control of risk factors, including lifestyle interventions to reduce smoking or intake of dietary fats, or the power of medical interventions, including defibrillators and therapeutics such as statins. Attempts to resolve this debate and guide health policy have generated sophisticated data sets and techniques for modeling cardiovascular mortality. Neither effort has provided specific guidance for health policy. Historical analysis of the debate over the causes of the decline, concomitant with development of cardiovascular modeling, offers valuable policy lessons about tensions among medical and public health strategies, the changing meanings of disease prevention, and the ability of evidence-based research and models to guide health policy. Policy makers must learn to open up the "black box" of epidemiological models-and of their own decision-making processes-to produce the best evidence-informed policy.

Use of Secondary Data to Estimate Instantaneous Model Parameters of Diabetic Heart Disease: Lemonade Method

With the increasing burden of chronic diseases on the health care system, Markov-type models are becoming popular to predict the long-term outcomes of early intervention and to guide disease management. However, statisticians have not been actively involved in the development of these models. Typically, the models are developed by using secondary data analysis to find a single "best" study to estimate each transition in the model. However, due to the nature of secondary data analysis, there frequently are discrepancies between the theoretical model and the design of the studies being used. This paper illustrates a likelihood approach to correctly model the design of clinical studies under the conditions where 1) the theoretical model may include an instantaneous state of distinct interest to the researchers, and 2) the study design may be such that study data can not be used to estimate a single parameter in the theoretical model of interest. For example, a study may ignore intermediary stages of disease. Using our approach, not only can we accommodate the two conditions above, but more than one study may be used to estimate model parameters. In the spirit of "If life gives you lemon, make lemonade", we call this method "Lemonade Method". Simulation studies are carried out to evaluate the finite sample property of this method. In addition, the method is demonstrated through application to a model of heart disease in diabetes.

Cost-effectiveness of implementing the chronic care model for diabetes care in a military population

BACKGROUND

Applying the chronic care model (CCM) for diabetes management helps improve health outcomes and patient care. The CCM was implemented at U.S. Air Force Wilford Hall Medical Center through the Diabetes Outreach Clinic (DOC) in 2006, but its cost-effectiveness in this setting is unknown.

METHODS

We constructed a Markov decision model to estimate DOC cost-effectiveness compared with usual care (UC) over a 20-year period. Based on empirical, post-intervention demographic and clinical data, we applied United Kingdom Prospective Diabetes Study risk equations to predict long-term probabilities of developing microvascular or macrovascular complications. Health care system and societal perspectives were considered, discounting costs and benefits at 3% annually. Intervention costs and outcomes were obtained from military data, while other costs, disease progression data, and utilities were drawn from published literature.

RESULTS

From a health care system perspective, the DOC cost $45,495 per quality-adjusted life-year (QALY) compared with UC; from a societal perspective, the DOC compared with UC cost $42,051/QALY (when the model started with the uncomplicated diabetes cohort), $61,243/QALY (when starting with the DOC cohort), or $61,813/QALY (when starting with the UC cohort). In one-way sensitivity analyses, results were most sensitive to yearly costs for specialty care visits. In probabilistic sensitivity analysis, the DOC was favored in 51% of model iterations using an acceptability threshold of $50,000/QALY and in 72% at a threshold of $100,000/QALY.

CONCLUSIONS

The DOC strategy for diabetes care, performed with the CCM methodology in a military population, appears to be economically reasonable compared with UC.

Chronic disease modeling and simulation software

Computers allow describing the progress of a disease using computerized models. These models allow aggregating expert and clinical information to allow researchers and decision makers to forecast disease progression. To make this forecast reliable, good models and therefore good modeling tools are required. This paper will describe a new computer tool designed for chronic disease modeling. The modeling capabilities of this tool were used to model the Michigan model for diabetes. The modeling approach and its advantages such as simplicity, availability, and transparency are discussed.

A critical review of mathematical models and data used in diabetology

The literature dealing with mathematical modelling for diabetes is abundant. During the last decades, a variety of models have been devoted to different aspects of diabetes, including glucose and insulin dynamics, management and complications prevention, cost and cost-effectiveness of strategies and epidemiology of diabetes in general. Several reviews are published regularly on mathematical models used for specific aspects of diabetes. In the present paper we propose a global overview of mathematical models dealing with many aspects of diabetes and using various tools. The review includes, side by side, models which are simple and/or comprehensive; deterministic and/or stochastic; continuous and/or discrete; using ordinary differential equations, partial differential equations, optimal control theory, integral equations, matrix analysis and computer algorithms.

A computer simulation model of diabetes progression, quality of life, and cost

OBJECTIVE

To develop and validate a comprehensive computer simulation model to assess the impact of screening, prevention, and treatment strategies on type 2 diabetes and its complications, comorbidities, quality of life, and cost.

RESEARCH DESIGN AND METHODS

The incidence of type 2 diabetes and its complications and comorbidities were derived from population-based epidemiologic studies and randomized, controlled clinical trials. Health utility scores were derived for patients with type 2 diabetes using the Quality of Well Being-Self-Administered. Direct medical costs were derived for managed care patients with type 2 diabetes using paid insurance claims. Monte Carlo techniques were used to implement a semi-Markov model. Performance of the model was assessed using baseline and 4- and 10-year follow-up data from the older-onset diabetic population studied in the Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR).

RESULTS

Applying the model to the baseline WESDR population with type 2 diabetes, we predicted mortality to be 51% at 10 years. The prevalences of stroke and myocardial infarction were predicted to be 18 and 19% at 10 years. The prevalences of nonproliferative diabetic retinopathy, proliferative retinopathy, and macular edema were predicted to be 45, 16, and 18%, respectively; the prevalences of microalbuminuria, proteinuria, and end-stage renal disease were predicted to be 19, 39, and 3%, respectively; and the prevalences of clinical neuropathy and amputation were predicted to be 52 and 5%, respectively, at 10 years. Over 10 years, average undiscounted total direct medical costs were estimated to be USD $53,000 per person. Among survivors, the average utility score was estimated to be 0.56 at 10 years.

CONCLUSIONS

Our computer simulation model accurately predicted survival and the cardiovascular, microvascular, and neuropathic complications observed in the WESDR cohort with type 2 diabetes over 10 years. The model can be used to predict the progression of diabetes and its complications, comorbidities, quality of life, and cost and to assess the relative effectiveness, cost-effectiveness, and cost-utility of alternative strategies for the prevention and treatment of type 2 diabetes.

The cost-effectiveness of lifestyle modification or metformin in preventing type 2 diabetes in adults with impaired glucose tolerance

BACKGROUND

The Diabetes Prevention Program (DPP) demonstrated that interventions can delay or prevent the development of type 2 diabetes.

OBJECTIVE

To estimate the lifetime cost-utility of the DPP interventions.

DESIGN

Markov simulation model to estimate progression of disease, costs, and quality of life.

DATA SOURCES

The DPP and published reports.

TARGET POPULATION

Members of the DPP cohort 25 years of age or older with impaired glucose tolerance.

TIME HORIZON

Lifetime.

PERSPECTIVES

Health system and societal.

INTERVENTIONS

Intensive lifestyle, metformin, and placebo interventions as implemented in the DPP.

OUTCOME MEASURES

Cumulative incidence of diabetes, microvascular and neuropathic complications, cardiovascular complications, survival, direct medical and direct nonmedical costs, quality-adjusted life-years (QALYs), and cost per QALY.

RESULTS OF BASE-CASE ANALYSIS

Compared with the placebo intervention, the lifestyle and metformin interventions were estimated to delay the development of type 2 diabetes by 11 and 3 years, respectively, and to reduce the absolute incidence of diabetes by 20% and 8%, respectively. The cumulative incidence of microvascular, neuropathic, and cardiovascular complications were reduced and survival was improved by 0.5 and 0.2 years. Compared with the placebo intervention, the cost per QALY was approximately 1100 dollars for the lifestyle intervention and $31 300 for the metformin intervention. From a societal perspective, the interventions cost approximately 8800 dollars and 29,900 dollars per QALY, respectively. From both perspectives, the lifestyle intervention dominated the metformin intervention.

RESULTS OF SENSITIVITY ANALYSIS

Cost-effectiveness improved when the interventions were implemented as they might be in routine clinical practice. The lifestyle intervention was cost-effective in all age groups. The metformin intervention did not represent good use of resources for persons older than 65 years of age.

LIMITATIONS

Simulation results depend on the accuracy of the underlying assumptions, including participant adherence.

CONCLUSIONS

Health policy should promote diabetes prevention in high-risk individuals.