Title of the Article : Multi-level preventive care for Type 2 diabetes
Author Information : Karca Aral (Whitman School of Management, Syracuse University)
Stephen E. Chick (INSEAD Business School)
Alfons Grabosch (Ruhr University Essen, Germany)
Year of Publication : WSC '14 Proceedings of the 2014 Winter Simulation Conference (2015)
Summary of Findings : The authors demonstrate that the cost effectiveness with a classical discounted net present value perspective does not imply cost effectiveness for long-run planning, and that joint optimization of a portfolio of interventions can have benefits relative to the sequential optimization of interventions individually. Thus, accounting for long-run demographics and the interaction of interventions may be a useful extension to traditional cost-utility analyses when designing preventive care policies.
Research Questions : 1. Do total discounted total cost objectives lead to substantively different decisions than do objectives with sustainable long-run average objectives?
2. What portfolios of interventions make sense for each of the objective functions (NPV, QALY, WTP)?
3. What benefits might be anticipated if one could immediately detect undiagnosed cases of prediabetes and T2DM?
What we know : Type 2 Diabetes Mellitus (T2DM), a preventive metabolic disease, accounts for 4.6 million deaths globally and for 11 percent of the global health expenditure, according to the International Diabetes Foundation. Several different primary, secondary and tertiary preventive interventions promise better health outcomes and cost savings. However, a comprehensive policy for decision makers integrating different levels of interventions to fight the spread of T2DM has been lacking.
Novel Findings : The authors demonstrate that the cost effectiveness with a classical discounted net present value perspective does not imply cost effectiveness for long-run planning, and that joint optimization of a portfolio of interventions can have benefits relative to the sequential optimization of interventions individually. Thus, accounting for long-run demographics and the interaction of interventions may be a useful extension to traditional cost-utility analyses when designing preventive care policies.
Novel Methodology : This paper proposes a portfolio approach for designing optimal preventive care policies for T2DM. The authors use a compartmental model that comprehends features of disease progression, the effect of interventions on compliance with self-management of T2DM and the interventions’ effects on the clinical indicator HbA1c (which is associated with costs and risks of complications due to T2DM) to optimize a portfolio of four different preventive interventions (primary prevention to avert new cases and to diagnose diabetics, disease management for pre-diabetics, early stage diabetics and late stage diabetics).
The model is calibrated using data from the Gulf Region. Numerical results provide guidance for prioritizing intervention investments and insights about different ways in which interventions can be beneficial (such as for screening or for averting new cases).
Implications for Policy: The model helps to inform policy in several ways. It emphasises the importance of jointly optimizing intervention decisions rather than selecting interventions individually in succession. It shows that optimizing for NPV considerations may lead to suboptimal decisions from the perspective of long-run population dynamics. And it suggests how additional resources might be focused on interventions, or on reducing uncertainty about key parameters. Beyond these and observations in Section 5 on the costs and benefits, the model suggests priorities for identifying unidentified cases of prediabetes and T2DM for treatment. This has direct implications for screening efforts in primary care settings so that treatment initiation can begin for those who have not yet been diagnosed.
Full Citations : Karca Aral, “Multi-level preventive care for Type 2 diabetes” (with Chick, S. and Grabosch, A.), IIE Transactions on Healthcare Systems Engineering, Vol. 5, No. 3, 2015.
Abstract : Type 2 Diabetes Mellitus (T2DM) accounts for 4.6 million deaths globally and for 11% of the global health expenditure (IDF, 2012). Several different primary, secondary, and tertiary preventive interventions promise better health outcomes and cost savings. Such interventions are typically studied in isolation. This paper proposes a compartmental mathematical model for T2DM that comprehends the interactions of multiple preventive interventions for various stages of T2DM, population dynamics, and the ensuing levels of clinical indicators, costs and utilities of disease states. We use the model to optimize portfolios of interventions for a multi-level preventive care program (using data from a population with high T2DM prevalence such as the UAE) and give insights about different ways in which interventions can be beneficial (such as for screening or for averting new cases). We demonstrate that the cost effectiveness with a classical discounted net present value perspective does not imply cost effectiveness for long-run planning, and that joint optimization of a portfolio of interventions can have benefits relative to the sequential optimization of interventions individually. Thus, accounting for long-run demographics and the interaction of interventions may be a useful extension to traditional cost-utility analyses when designing preventive care policies.
This study examines preventive care models for Type 2 diabetes patients and provides guidance for prioritizing intervention investments.
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