Technology Diffusion, Health Outcomes, and Healthcare Expenditures

产品说明：在以前的研究中，发现医疗保健支出和健康结果存在很大差异，两者之间几乎没有相关性。这些研究仅限于横截面分析，并告诉这些模式出现的动态过程很少。一个假设是，技术扩散率在各区域的差异，无论是高效治疗（对健康结果有很大影响）还是价值未知的昂贵治疗（对支出有很大影响），都可以解释观察到的支出和结果的横截面模式。在该提案中，目标1旨在更好地了解用于糖尿病患者血糖控制的血红蛋白A1 C（HbA 1c）测试等高效医疗保健的传播。利用美国所有医生的国家Doximity数据库，沿着关于医生-医院网络（PHN）和医生社交网络的信息，研究小组将测试为什么HbA 1c在某些地区（以及所有种族和民族群体）传播如此迅速，而不是其他地区。他们还将测试HbA 1c的快速扩散是否会降低神经病变、视网膜病变和截肢的发生率。目标2侧重于推广普遍有益的治疗方法，但这种治疗方法实际上可能会伤害特定类型的患者。考虑两个例子：植入式心律转复除颤器（ICD）的快速增长，以及新型和昂贵的抗凝剂（达比加群、阿哌沙班和利伐沙班）的增长。目标3研究了扩散的反面--“扩张”或从使用中撤退--以询问医生-医院网络和地区如何缩减新发现的对患者亚组价值不高的治疗。该提案考虑了两种具体的治疗方法：颈动脉内膜切除术（手术和支架）的急剧减少，以及在2007年发表的一篇文章显示严重的心血管风险后，抗糖尿病药物罗格列酮（文迪雅）的使用减少。在这些情况下，最有效的外展模式应该经历最大的下降，在使用不太合适的患者。目标4研究了具有未知甚至不良后果的治疗的扩散，例如某些地区（但不是其他地区）ICU床位容量的快速增长。该研究小组将研究“医疗外”治疗的网络和扩散模式--受利润驱使的非法行为，对病人没有好处，其中一个例子是2002-2005年免疫球蛋白输注的兴衰。最后，研究小组将利用这四个目标的结果回到中心假设：观察到的治疗特异性扩散的差异能否解释观察到的健康结果和支出的区域差异模式？

DESCRIPTION: In previous research wide variations have been found in both healthcare spending and in health outcomes, with little correlation between the two. These studies were limited to cross-sectional analysis, and tell little about the dynamic process by which these patterns arise. One hypothesis is that variation across regions in rates of technology diffusion, whether for highly effective treatments (with a large impact on health outcomes) or for expensive treatments with unknown value (with a large impact on expenditures), can explain the observed cross-sectional patterns of spending and outcomes. In this proposal, Aim 1 seeks to better understand the diffusion of highly effective healthcare such as hemoglobin A1C (HbA1c) tests for blood glucose control among diabetic patients. Using the national Doximity database on every physician in the U.S., along with information about physician-hospital networks (PHN) and physician social networks, the research team will test why HbA1c diffused so rapidly (and among all racial and ethnic groups) in some areas but not others. They will also test whether more rapid diffusion of HbA1c reduced rates of neuropathy, retinopathy, and amputation. Aim 2 focuses on the diffusion of generally beneficial treatments but where the treatment can actually harm specific types of patients. Two examples are considered: the rapid growth in implantable cardioverter defibrillators (ICDs), and the growth in new and expensive anticoagulants - dabigatran, apixaban and rivaroxaban. Aim 3 studies the opposite of diffusion - "exnovation" or a retreat from use - to ask how physician-hospital networks and regions scaled back on treatments newly found to have poor value for subgroups of patients. The proposal considers two specific treatments: the sharp reduction in carotid endarterectomy (both surgery and stents), and the decline in the use of Rosiglitazone (Avandia), an anti-diabetic drug, following a 2007 publication demonstrating serious cardiovascular risks. In these cases, the most effective exnovation patterns should experience the largest drop in use for the less appropriate patients. Aim 4 examines the diffusion of treatments with unknown or even adverse consequences, such as the rapid growth in some regions (but not others) in ICU bed capacity. The research team will study the network and diffusion patterns for "extramedical" treatments - illegal behavior motivated by profit and with no benefit for patients, with one example being the rise and fall of immunoglobulin infusions in 2002-2005. Finally, the research group will use results from these four aims to return to the central hypothesis: can observed differences in treatment-specific diffusion explain observed patterns in regional variations in health outcomes and spending?