Technology Diffusion, Health Outcomes, and Healthcare Expenditures

技术扩散、健康成果和医疗支出

• 批准号: 9111769
• 负责人: JONATHAN S SKINNER
• 金额: $ 101.39万
• 依托单位: DARTMOUTH COLLEGE
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-30 至 2018-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9111769
• 关键词: Adopted; Adverse effects; Age; Amputation; Anticoagulants; Antidiabetic Drugs; Area; Atrial Fibrillation; Back; Beds; Belief; Blood Glucose; Blood Vessels; Cardiac; Cardiovascular Diseases; Carotid Endarterectomy; Categories; Characteristics; Clinical; Cross-Sectional Studies; Data; Databases; Deep Vein Thrombosis; Diffuse; Diffusion; Drops; Ethnic group; Exhibits; Expenditure; Fee-for-Service Plans; Glycosylated hemoglobin A; Growth; Health; Health Care Costs; Health Personnel; Healthcare; Hemoglobin; Hospitals; Immunoglobulins; Implantable Defibrillators; Individual; Infusion procedures; Intensive Care Units; Link; Marketing; Masks; Measures; Medical; Medicare; Medicare claim; Monitor; Neuropathy; Operative Surgical Procedures; Outcome; Patient Selection; Patients; Pattern; Pharmaceutical Preparations; Physicians; Population; Process; Provider; Publications; Quality of Care; Race; Registries; Research; Residencies; Retinal Diseases; Risk; Social Network; Speed; Stents; Structure; Subgroup; System; Technology; Testing; Variant; adverse outcome; bed capacity; blood glucose regulation; cardiovascular risk factor; data registry; diabetic; diabetic patient; effective therapy; experience; falls; illegal behavior; medical schools; medical specialties; organizational structure; randomized trial; rapid growth; rosiglitazone; social; technology diffusion; treatment group

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?

描述：在以前的研究中，在医疗保健支出和健康结果方面发现了广泛的差异，两者之间几乎没有相关性。这些研究仅限于横截面分析，对这些模式产生的动态过程知之甚少。一种假设是，区域间技术扩散率的差异，无论是对于高效治疗（对健康结果有很大影响）还是对于价值未知的昂贵治疗（对支出有很大影响），都可以解释所观察到的支出和结果的横截面模式。在本提案中，Aim 1旨在更好地了解高效医疗保健的传播，如糖化血红蛋白（HbA1c）检测在糖尿病患者中的血糖控制。研究小组将利用美国每位医生的国家Doximity数据库，以及关于医生-医院网络（PHN）和医生社交网络的信息，测试为什么HbA1c在某些地区传播得如此之快（并且在所有种族和族裔群体中），而在其他地区却没有。他们还将测试更快的HbA1c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侧重于传播通常有益的治疗方法，但治疗实际上可能伤害特定类型的患者。考虑到两个例子：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。目的3研究扩散的对立面——“创新”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亚组患者价值不高的治疗。该提案考虑了两种特定的治疗方法：颈动脉内膜切除术（手术和支架）的急剧减少，以及抗糖尿病药物罗格列酮（文迪雅）的使用减少，2007年发表的一篇文章显示了严重的心血管风险。在这些情况下，最有效的创新模式应该在不太合适的患者中经历最大的使用下降。目的4检查了治疗方法的扩散，这些治疗方法具有未知的甚至不良的后果，例如在某些地区（而不是其他地区）ICU病床容量的快速增长。该研究小组将研究“医疗外”治疗的网络和扩散模式，这是一种以利润为动机的非法行为，对患者没有任何好处，2002-2005年免疫球蛋白输注的兴衰就是一个例子。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卫生结果和支出的区域差异模式？