Empirical Studies of the Development and Diffusion of Medical Technologies

其他项目信息-项目摘要/摘要 医疗技术发展与扩散的实证研究 技术变革是医疗保健市场的一个中心特征，在过去的几十年里， 彻底改变了许多疾病的治疗方法。尽管突破性的科学进步是一种 医疗创新步伐的重要驱动力，市场激励--如专利提供的激励 系统--通常是潜在技术成功转型的关键决定因素 从实验室走向市场。该项目的主要贡献是开发新的数据(目标1和3)和新的 调查专利如何影响医学发展和传播的实证方法(目标2和4) 创新。具体地说，我们应用这些新数据和新方法来估计两个相关参数： 专利在多大程度上激励了新技术的发展，以及在多大程度上 现有技术的专利阻碍了后续的创新。更有效的专利是在诱导 研究投资越多，要求更长或更广泛专利的理由就越强。另一方面，越大的 专利成本在阻碍后续创新方面越弱，这种情况就越弱。评估这些成本 专利的好处是最优政策设计的关键投入。要估计第一个参数-如何 更强的专利保护前景影响着研究投资--我们开发了一种新的经验方法(AIM 2)基于以下想法：因为制药公司在开始临床试验之前提交专利，所以时间更短 临床试验为公司提供了更长的有效专利期。因此，如果更长的专利期鼓励更多的研究 投资，我们应该看到对需要治疗的患者群体的研究投资水平更高 更短的临床试验。我们将这种方法应用于一个新开发的数据集，该数据集衡量了 癌症患者的治疗(在目标1中制定)。估计第二个参数-专利如何 现有技术会影响后续研究投资--我们开发了一种新的经验方法(目标4)。 我们方法背后的关键思想是利用两个事实：第一，专利申请是准 随机分配给美国专利商标局的专利审查员；第二，专利审查员 在向任何给定的申请授予专利的可能性上存在差异。我们将此方法应用于一个新的- 开发了衡量与人类基因组有关的研究投资的数据集(在目标3中开发)和 量化人类基因专利在多大程度上阻碍了随后的医学创新。新的 实验方法(目标2和目标4)将应用于两类特殊的医疗技术--癌症 治疗和基于基因的诊断和治疗--但每种方法都可以应用于其他情况。在……里面 此外，新的数据构建方法(目标1和3)-基于文本的匹配与临床试验登记 列表和网格--将研究投资与相关患者群体进行ICD匹配--也可以应用 在其他情况下。

OTHER PROJECT INFORMATION - Project Summary/Abstract Empirical Studies of the Development and Diffusion of Medical Technologies Technological change is a central feature of health care markets, and over the past few decades has revolutionized the treatment of many medical conditions. Although breakthrough scientific advances are an important driver of the pace of medical innovation, market incentives - such as those provided by the patent system - are often a critical determinant of which potential technologies successfully make the transition 'from the lab to the market.' The key contribution of this project is to develop new data (Aims 1 and 3) and new empirical methods (Aims 2 and 4) to investigate how patents shape the development and diffusion of medical innovations. Specifically, we apply these new data and new methods to estimate two relevant parameters: the extent to which patents provide incentives for the development of new technologies, and the extent to which patents on existing technologies hinder subsequent innovation. The more effective patents are in inducing research investments, the stronger the case for longer or broader patents. On the other hand, the larger the costs of patents in terms of hindering subsequent innovation, the weaker is this case. Evaluating these costs and benefits of patents is a key input into optimal policy design. To estimate the first parameter - how the prospect of stronger patent protection affects research investments - we develop a new empirical method (Aim 2) based on the following idea: because pharmaceutical firms file patents prior to starting clinical trials, shorter clinical trials grant firms longer effective patent terms. Hence, if longer patent terms encourage more research investments, we should see higher levels of research investments on treatments for patient groups that require shorter clinical trials. We apply this method to a newly developed data set measuring research investments on treatments for cancer patients (developed in Aim 1). To estimate the second parameter - how patents on existing technologies affect subsequent research investments - we develop a new empirical method (Aim 4). The key idea behind our approach is to take advantage of two facts: first, patent applications are quasi- randomly assigned to patent examiners at the US Patent and Trademark Office; and second, patent examiners differ in their likelihood of awarding a patent to any given application. We apply this method to a newly- developed data set measuring research investments related to the human genome (developed in Aim 3) and quantify the extent to which patents on human genes have hindered subsequent medical innovation. The new empirical methods (Aims 2 and 4) will be applied to two particular classes of medical technologies - cancer treatments and gene-based diagnostics and treatments - but each method can be applied in other contexts. In addition, the new data construction methods (Aims 1 and 3) - text-based matching with clinical trial enrollment lists, and MeSH-ICD matching of research investments to the relevant groups of patients - can also be applied in other contexts.