摘要：The Prevention Impacts Simulation Model (PRISM) projects the multiyear impacts of 22 different interventions aimed at reducing risk of cardiovascular disease. We grouped these into 4 categories: clinical, behavioral support, health promotion and access, and taxes and regulation. We simulated impacts for the United States overall and also for a less-advantaged county with a higher death rate. Of the 4 categories of intervention, taxes and regulation reduce costs the most in the short term (through 2020) and long term (through 2040) and reduce deaths the most in the long term; they are second to clinical interventions in reducing deaths in the short term. All 4 categories combined were required to bring costs and deaths in the less-advantaged county down to the national level. Public health decision-makers often have to decide among multiple and potentially competing interventions to strategically direct their prevention programs. Interventions vary by private or public costs, political acceptability, ease of implementation, and the magnitude, time frame, and uncertainty surrounding their health impacts. 1 They also vary in terms of their aim (e.g., individual, social environment, physical environment). We used a computer simulation model to explore how 4 distinct categories of interventions differ in terms of their potential for reducing the risks of cardiovascular disease (CVD) in a population over a 30-year time horizon. The Prevention Impacts Simulation Model (PRISM), 2,3 originally developed to represent the entire US population, includes 22 intervention levers, which we found could be usefully grouped according to a 2 × 2 conceptual representation ( Figure 1 ). On 1 axis, some of the levers act at the individual level (clinical, behavioral support), whereas others act at the population level (taxes and regulation, health promotion and access). On a second axis, some of the levers are prescriptive (clinical, taxes and regulation), whereas others are facilitative (behavioral support, promotion and access). Facilitative levers require a certain awareness, motivation, and creativity on the part of the individual, whereas prescriptive levers affect behavior more simply or directly. Open in a separate window FIGURE 1— Two axes defining 4 categories of interventions for reducing risks of cardiovascular disease: Prevention Impacts Simulation Model. The impacts of public health interventions may be mediated, in part, by the socioeconomics of the target population. 4 Although PRISM does not include interventions to modify socioeconomic factors, it is possible to illustrate the importance of such factors by recalibrating the model to represent a local area whose socioeconomics are different from those of the nation overall. After testing the 4 categories of interventions at the US level, we compared the national results with those of the model calibrated to represent the demographics, risk factor prevalence, and CVD events and deaths of a less-advantaged county that has a higher death rate than the nation overall. Assuming the same intervention effect sizes in the national and less-advantaged county models, the comparison allowed us to explore 2 questions: (1) Do the starting differences between the less-advantaged county and the United States overall lead to different conclusions about the relative effectiveness of the different categories of interventions? (2) Is it possible to close the current CVD health gap between the less-advantaged county and the rest of the nation, and, if so, what combination of interventions would this require?
