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Estimating Future Health Technology Diffusion Using Expert Beliefs Calibrated to an Established Diffusion Model

机译:使用专业信念估算未来的健康技术扩散,校准到已建立的扩散模型

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ObjectivesEstimates of future health technology diffusion, or future uptake over time, are a requirement for different analyses performed within health technology assessments. Methods for obtaining such estimates include constant uptake estimates based on expert opinion or analogous technologies and on extrapolation from initial data points using parametric curves—but remain divorced from established diffusion theory and modeling. We propose an approach to obtaining diffusion estimates using experts’ beliefs calibrated to an established diffusion model to address this methodologic gap. MethodsWe performed an elicitation of experts’ beliefs on future diffusion of a new preterm birth screening illustrative case study technology. The elicited quantities were chosen such that they could be calibrated to yield the parameters of the Bass model of new product growth, which was chosen based on a review of the diffusion literature. ResultsWith the elicitation of only three quantities per diffusion curve, our approach enabled us to quantify uncertainty about diffusion of the new technology in different scenarios. Pooled results showed that the attainable number of adoptions was predicted to be relatively low compared with what was thought possible. Further research evidence improved the attainable number of adoptions only slightly but resulted in greater speed of diffusion. ConclusionsThe proposed approach of eliciting experts’ beliefs about diffusion and informing the Bass model has the potential to fill the methodologic gap evident in value of implementation and research, as well as budget impact and some cost-effectiveness analyses.
机译:未来的健康技术扩散或随着时间的推移,未来的卫生技术扩散或未来摄取的氛围是在健康技术评估中进行的不同分析的要求。获得这种估计的方法包括基于专家意见或类似技术的恒定摄取估计,以及使用参数曲线的初始数据点的外推 - 但从建立的扩散理论和建模中仍然离立离子。我们提出了一种使用专家的信念来获得扩散估计的方法,以解决建立的扩散模型,以解决该方法差距。方法网络对专家的信念进行了对未来扩散的新早产出生筛查说明性案例研究技术的信念。选择引发的量,使得它们可以被校准以产生新产品生长的低音模型的参数,这是根据对扩散文献的审查选择的。结果可以仅仅是每个扩散曲线的三个量的诱导,我们的方法使我们能够在不同场景中量化新技术的扩散的不确定性。合并结果表明,与认为可能的内容相比,预计可获得的收养数量相对较低。进一步的研究证据只有略微略微改善可达的收养数,但导致了更大的扩散速度。结论,拟议的埃及专家信仰对扩散和通知BASS模型的方法有可能填补实施和研究价值的方法,以及预算影响和一些成本效益分析。

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