Systems Science for Caribbean Health: the development and piloting of a model for guiding policy on diabetes in the Caribbean

Abstract

BackgroundDiabetes is highly prevalent in the Caribbean, associated with a high morbidity and mortality and is a recognised threat to economic and social development. Heads of Government in the Caribbean Community came together in 2007 and declared their commitment to reducing the burden of non-communicable diseases (NCDs), including diabetes, by calling for a multi-sectoral, systemic response. To facilitate the development of effective policies, policymakers are being engaged in the development and use of a system dynamics (SD) model of diabetes for Caribbean countries.MethodsPrevious work on a diabetes SD model from the United States of America (USA) is being adapted to a local context for three countries in the region using input from stakeholders, a review of existing qualitative and quantitative data, and collection of new qualitative data. Three country models will be developed using one-on-one stakeholder engagement and iterative revision. An inter-country model will also be developed following a model-building workshop. Models will be compared to each other and to the USA model. The inter-country model will be used to simulate policies identified as priorities by stakeholders and to develop targets for prevention and control. The model and model-building process will be evaluated by stakeholders and a manual developed for use in other high-burden developing regions.DiscussionSD has been applied with success for health policy development in high-income country settings. The utility of SD in developing countries as an aid to policy decision-making related to NCDs has not been tested. This study represents the first of its kind.

A System Dynamics Simulation Applied to Healthcare: A Systematic Review

“…Some studies implement the entire core part of the stock-flow diagram [ 84 , 89 , 91 , 93 , 94 , 95 ], while other studies implemented only the diagnosed part (blue box), in which there is an additional flow from the population to diagnosed patients [ 82 , 96 , 97 , 98 ]. Furthermore, several of the selected studies only implemented the undiagnosed-to-diagnosed part of the stock-flow diagram (orange box) without expanding on different stages of chronic diseases [ 79 , 80 , 81 , 83 , 85 , 87 , 92 , 99 ].…”

Validating the self-reported annual monitoring grid for the 2007 Caribbean Community Declaration of Port-of-Spain on noncommunicable diseases

“…In the Caribbean and the Pacific, small populations and resultant suboptimal capacity require tailored solutions for monitoring the NCD agenda (19–22).…”

An Innovative Approach for Decision-Making on Designing Lifestyle Programs to Reduce Type 2 Diabetes on Dutch Population Level Using Dynamic Simulations

“…To address wicked problems to an extent in which they might become manageable, this research argues the need of a holistic, integral approach, easily accessible for stakeholders, that captures non-linear behavior of the complex system over time. SD modeling is well-suited to address this complexity and an appropriate method for identifying important leverage points and examination of possible interventions in complex problems in advance of real-life implementation and subsequent evaluation, which would otherwise be too costly ( 21 , 55 ). Therefore, with the ultimate aim to develop a simulation tool, SD was used to build a first version of an SD model to gain insights in the development of the T2DM patient journey in The Netherlands under the current policy, under lifestyle programs as several intervention policies, and under programs that combine lifestyle intervention policies.…”