Technology Diffusion Pathways

申请编号：1 U 01 MH 103018 -01（原名：1U 01 AG 046691 -01） 海登·胡斯坎普博士 沙龙-利斯·特丽莎·诺曼德博士（联系人） 技术扩散途径 产品说明：在过去的几年里，人们越来越关注提供者组织，将其作为对所提供的医疗保健的成本和质量负责的中心。 一些新的战略，以遏制支出增长和提高护理质量，鼓励提供者组织，以满足这些目标，通过交付系统的变化。 采用新的医疗技术是医疗保健支出增长的主要驱动力。 医生和他们执业的组织有各种选择来采用和使用新的和现有的技术。 他们的选择可能会提高护理效率，但可能不会证明是最佳的，这取决于哪些技术采用得更快，哪些技术采用得更慢，这些策略的影响可能会因组织而异。利用2005-2015年期间收集的丰富数据，我们建议研究组织特征和技术扩散之间的关系。在目标1中，我们将研究选定的新技术的扩散，包括我们指定的高价值和低价值的技术，在4种疾病类别-癌症，抑郁症，心脏病和髋关节退行性变-作为组织特征的函数。我们的统计方法包括扩散曲线的属性，并提供新的方法来表征技术采用的路径。这些方法有助于确定使用新技术的决定是否与不同技术类型相关，或者是否与疾病状况相关。在目标2中，使用专业协会颁布的质量指标、技术特征和FDA警报，我们将区分高价值服务和低价值服务，识别预测其使用的组织因素，并确定采用高价值服务和低价值服务的决策是否相关。在目标3中，我们将确定组织特征，根据医生和患者因素进行调整，与新技术支出以及低价值服务和高价值服务相关。 大多数关于技术采用和传播的研究都是对单一技术的案例研究。我们的研究将比较疾病领域内不同类型技术（药物、设备和生物制剂）、低价值和高价值技术以及不同组织形式的采用率和使用率。

Application Number: 1 U01 MH103018-01 (Formerly: 1U01AG046691-01) HUSKAMP, HAIDEN A. PHD NORMAND, SHARON-LISE TERESA PHD (Contact) Technology Diffusion Pathways DESCRIPTION: Over the past several years, there has been increasing focus on provider organizations as the locus of responsibility for the cost and quality of health care that is delivered. A number of new strategies to contain spending growth and improve quality of care encourage provider organizations to meet these goals through delivery system changes. Adoption of new medical technology is a primary driver of health care spending growth. Physicians and the organizations in which they practice have various options to adopt and use new and existing technologies. Their choices can potentially improve efficiency of care, but might not prove optimal depending on which technologies are adopted more quickly versus more slowly, and the impact of such strategies will likely vary across organizations. Using a rich collection of data for the period 2005-2015, we propose to examine the relationship between organization traits and diffusion of technology. In Aim 1 we will study the diffusion of selected new technologies, including technologies we designate to be of higher and lower value, in 4 disease categories - cancer, depression, cardiac, and hip degeneration - as a function of organization characteristics. Our statistical methods include properties of diffusion curves, and provide new approaches to characterize the path of technology adoption. These approaches enable determination of whether decisions to use new technologies are correlated among different technology types, or within and between disease conditions. In Aim 2, using quality measures promulgated by professional societies, technology characteristics, and FDA alerts, we will distinguish higher from lower value services, identify organizational factors predictive of their use, and determine if decisions to adopt higher vs. lower value services are correlated. In Aim 3, we will identify organizational characteristics, adjusting for physician and patient factors, associated with spending for new technologies and for lower vs. higher value services. Most research on technological adoption and diffusion consists of case studies of single technologies. Our study will compare rates of adoption and use across types of technologies (medications, devices, and biologics) within disease areas, across lower and higher value technologies, and across organizational forms.