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2 Setting the Context
Pages 7-18

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From page 7...
... WHY MODELING MATTERS FOR IMPROVING POPULATION HEALTH1 Steven Teutsch began the workshop's first presentation by displaying the framework that the County Health Rankings2 uses to describe 1This section is based on the presentation by Steven Teutsch, an independent consultant; an adjunct professor at the Fielding School of Public Health, University of California, Los Angeles; a senior fellow at the Public Health Institute; and a senior fellow at the Leonard D Schaeffer Center for Health Policy and Economics, University of Southern California, and the statements are not endorsed or verified by the Institute of Medicine.
From page 8...
... • There are three ways in which models can guide policy making, intervention design, and decision making (Hammond) : o  prospectively to try to understand in advance what the intended and u ­ nintended consequences of an intervention or policy might be; o  retrospectively to look at interventions and policies that have already been tried with the goal of better understanding how these interventions and policies work or why they do not work and to leverage that knowledge to provide insights that would be useful for replicating or scaling an interven tion or policy; and o  focusing on etiology and reducing the uncertainty that decision makers by face when developing policy.
From page 9...
... , presented by Teutsch on April 9, 2015. Figure 2-1 R02894 can incorporate the primary concerns of decision makers, and, in that raster uneditable regard, it is important for modelers to interact with decision makers to identify the issues that are most important to them so that the models can be designed to provide meaningful and useful output.
From page 10...
... For the decision makers at the workshop, the questions included • What important intractable or complex problems do you have that are not being adequately addressed by current approaches? • Can models help?
From page 11...
... Examples that Hammond cited included forecasting what next year's influenza strains might be or what might happen with the implementation of a policy that has never been tried before, such as New York City's recent move to raise the legal age to purchase tobacco to 21. "Models can help us think about these possibilities that by definition we 3This section is based on the presentation by Ross Hammond, a senior fellow in economic studies at the Brookings Institution, and the statements are not endorsed or verified by the Institute of Medicine.
From page 12...
... The models developed by this network enabled policy makers and public health officials to consider the implications of choices made during that epidemic, such as closing schools and airports, distributing antiviral drugs, and distributing vaccine. "These are choices that had to be made in real time with high uncertainty and sometimes without a lot of data to directly guide them," Hammond said.
From page 13...
... The third way that models are used to guide decisions involves focuses on etiology, and when used properly, this type of model can help reduce the uncertainty that decision makers face when developing policies by helping them understand the mechanisms that are at work. Such models do not explicitly model a policy but nonetheless have implications for policy and intervention design and can also help identify data
From page 14...
... Best practices also exist to help modelers decide what to include and what not to include in their models and to plan testing and implementation procedures. Another reason for engaging early with policy makers and decision makers, Hammond said, is so that they develop a deep understanding of the model and become stakeholders in the model development in a way that gives them a more intuitive sense of why the model comes up with a certain result, particularly when that result is counterintuitive.
From page 15...
... "To assess that," he said, "you have to use a variety of testing approaches with your model to understand what evidence is based on and what it does or does not show about what we know in the real world and what it can reproduce in the real world. That said, it is important to recognize that by design, models are simplifications, which means that they are all missing something important that is true in the real world." George Isham from HealthPartners observed that, based on his experience as a model user and policy maker, policy makers need to be much more engaged in model development if they expect to get the kind of indepth information that is useful in making policy.
From page 16...
... Louise Russell added that a good model has to be the result of a conversation not just between modelers and policy m ­ akers, but also one that includes subject matter experts. Catherine Baase from The Dow Chemical Company asked if models have confidence intervals that reflect the fact that they include assumptions when the exact information needed is not available and if there are ways of tracking the effectiveness of models over time.
From page 17...
... "That is what sensitivity analysis is about," Russell said, "That is what policy makers, other users, and subject matter experts need to keep an eye on."


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