Michael E. Minshall

The CORE Diabetes Model: Projecting Long-term Clinical Outcomes, Costs and Cost- effectiveness of Interventions in Diabetes Mellitus (Types 1 and 2) to Support Clinical and Reimbursement Decision-making

SUMMARY Objectives: We have developed an Internet-based, interactive computer model to determine the longterm health outcomes and economic consequences of implementing different treatment policies or interventions in type 1 and type 2 diabetes mellitus. The model projects outcomes for populations, taking into account baseline cohort characteristics and past history of complications, current and future diabetes management and concomitant medications, screening strategies and changes in physiological parameters over time. The development of complications, life expectancy, quality-adjusted life expectancy and total costs within populations can be calculated. Methods: The model is based on a series of sub-models that simulate important complications of diabetes (cardiovascular disease, eye disease, hypoglycaemia, nephropathy, neuropathy, foot ulcer, amputation, stroke, ketoacidosis, lactic acidosis and mortality). Each sub-model is a Markov model using Monte Carlo simulation incorporating time, state, time-in state, and diabetes type-dependent probabilities derived from published sources. Analyses can be performed on cohorts with type 1 or type 2 diabetes. Cohorts, defined in terms of age, gender, baseline risk factors and pre-existing complications, can be modified or new cohorts defined by the user. Economic and clinical data in the model can be edited, thus ensuring adaptability by allowing the inclusion of new data as they become available; creation of country- or provider-specific versions of the model; and allowing the investigation of new hypotheses. Conclusions: The CORE Diabetes Model allows the calculation of long-term outcomes, based on the best data currently available. Diabetes management strategies can be compared in different patient populations in a variety of realistic clinical settings, allowing the identification of efficient diabetes management strategies.

Validation of the CORE Diabetes Model Against Epidemiological and Clinical Studies

OBJECTIVES The aim of this study was to assess the validity of the CORE Diabetes Model by comparing results from model simulations with observed outcomes from published epidemiological and clinical studies in type 1 and type 2 diabetes. METHODS A total of 66 second- (internal) and third- (external) order validation analyses were performed across a range of complications and outcomes simulated by the CORE Diabetes Model (amputation, cataract, hypoglycaemia, ketoacidosis, macular oedema, myocardial infarction, nephropathy, neuropathy, retinopathy, stroke and mortality). Published studies were reproduced in the model by recreating cohorts in terms of demographics, baseline risk factors and complications, treatment patterns and patient management strategies, and simulating the progress of the cohort to an equivalent time horizon. RESULTS Correlation analysis on results from 66 validation simulations produced an R2 value of 0.9224 (perfect fit = 1). A correlation plot of published study data versus values simulated by the CORE Diabetes Model had a trend line with a gradient of 1.0187 (perfect fit = 1). Validation analyses in type 1 and type 2 diabetes were associated with R2 values of 0.9778 and 0.8861 respectively. Correlation of second-order validation analyses (model predictions versus observed outcomes in studies used to construct the model) produced an R2 value of 0.9574, and the value for third-order analyses (model predictions versus observed outcomes in studies not used to construct the model) was 0.9023. CONCLUSIONS The CORE Diabetes Model provides an accurate representation of patient outcomes when compared to 66 studies of diabetes and its complications. Model flexibility ensures it can be used to compare diabetes management strategies in different cohorts across a variety of clinical settings.

Direct medical costs for type 2 diabetes mellitus complications in the US commercial payer setting: a resource for economic research.

BackgroundMedical complications are the key drivers of the direct medical costs of treating patients with type 2 diabetes mellitus. However, the published literature shows great variability across studies in the number and type of sources from which these costs for diabetes are obtained.ObjectiveTo provide to researchers a set of costs for type 2 diabetes complications, originally developed for input into an established diabetes model, that are empirically based, clearly and consistently defined and applicable to a large segment of managed care patients in the US.MethodsPatients with 1 of 24 diabetes-related complications between 1 January 2003 and 31 December 2004 and with evidence of type 2 diabetes were identified using a nationally representative US commercial insurance claims database. Therapy utilization and complication cost data were extracted for all patients for the 12 months following the first identified complication; data for months 13–24 were obtained for a subset of patients with at least 24 months of follow-up enrolment. Medical costs included both the amounts charged by medical providers and the health plan contracted allowed amounts. Costs were expressed as

Estimating the Long-Term Cost-Effectiveness of Exenatide in the United States: An Adjunctive Treatment for Type 2 Diabetes Mellitus

US, year 2007 values.ResultsA total of 44021 patients with a minimum of 12 months of continuous follow-up enrolment were identified, with a mean age of 56 years; a subset of 32991 patients with at least 24 months of continuous health-plan enrolment was also identified. Among the aggregate sample, 74% of patients were receiving oral antidiabetics, 26% were receiving insulin, 43% were receiving ACE inhibitors and 50% were receiving antihyperlipidaemics/HMG-CoA reductase inhibitors (statins) during the first 12 months following the index complication. The majority of patients had at least one physician office visit (99.8%), laboratory diagnostic test (96.2%) and other outpatient visit (97.5%). Six complications (angina pectoris, heart failure, peripheral vascular disease, renal disease, nonproliferative retinopathy and neuropathy) had a prevalence of at least 10%. Allowed amounts for most complications were 30–45% of charges. Myocardial infarction, heart failure and renal disease had the greatest fiscal impact because of the total number of patients experiencing them (7.2%, 14.0% and 11.0%, respectively) and their associated costs; 12-month mean allowed amounts were

A Cost-Effectiveness Analysis of Continuous Subcutaneous Insulin Injection versus Multiple Daily Injections in Type 1 Diabetes Patients: A Third-Party US Payer Perspective

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Continuous subcutaneous insulin infusion versus multiple daily injections of insulin : Economic comparison in adult and adolescent type 1 diabetes mellitus in Australia

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Cost-effectiveness of insulin detemir compared to NPH insulin for type 1 and type 2 diabetes mellitus in the Canadian payer setting: modeling analysis

US13876, respectively, and 12-month mean charged amounts were

Health economic comparison between continuous subcutaneous insulin infusion and multiple daily injections of insulin for the treatment of adult type 1 diabetes in Canada.

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Self-monitoring of blood glucose (SMBG) for type 2 diabetes patients treated with oral anti-diabetes drugs and with a recent history of monitoring: cost-effectiveness in the US.

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What Impact Would Pancreatic Beta-cell Preservation Have on Life Expectancy, Quality-adjusted Life Expectancy and Costs of Complications in Patients with Type 2 Diabetes? A Projection Using the CORE Diabetes Model

US34987, respectively. Similarly, in the subset of 32991 patients, these three complications had higher allowed and charged amounts over months 13–24 compared with the majority of other complications of interest.ConclusionThese costing results provide an important resource for economic modelling and other types of costing research related to treating diabetes-related complications within the US managed care system.