Technology Diffusion, Health Outcomes, and Healthcare Expenditures

技术扩散、健康成果和医疗支出

• 批准号: 8628306
• 负责人: JONATHAN S SKINNER
• 金额: $ 83.1万
• 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 2018-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8628306
• 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; public health relevance; randomized trial; rapid growth; rosiglitazone; social

PROJECT SUMMARY 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?

项目摘要 在以前的研究中，在医疗保健支出和健康成果中都发现了广泛的差异， 两者之间几乎没有相关性。这些研究仅限于横断面分析，很少说明 关于这些模式出现的动态过程。一个假设是跨区域的变化 技术扩散的速率，无论是否有效治疗（对健康结果产生很大的影响） 或对于价值未知的昂贵处理（对支出产生了很大影响），可以解释 观察到的支出和结果的横截面模式。 在此提案中，AIM 1试图更好地了解高效医疗保健的扩散 血红蛋白A1C（HBA1C）测试糖尿病患者的血糖控制。使用国家 有关美国每个医师的数据库，以及有关医师院士网络（PHN）和 医师社交网络，研究团队将测试HBA1C为什么如此迅速扩散的原因（在所有种族和种族中 族裔群体）在某些地区，但不是其他领域。他们还将测试HBA1C的更快扩散 神经病，视网膜病和截肢的速度。 AIM 2专注于通常有益的扩散 治疗但治疗实际上可能损害特定类型的患者。考虑了两个例子： 可植入的心脏逆转除颤器（ICD）的快速增长以及新且昂贵的增长 抗凝剂-Dabigatran，Apixaban和Rivaroxaban。 AIM 3研究扩散的对立面 - “循环”或使用的撤退 - 询问医师医院如何 网络和区域缩减了新发现的治疗方法，对患者亚组的价值较差。 该提案考虑了两种特定的治疗方法：颈动脉内膜切除术的急剧减少（均为手术 和支架），以及在2007年之后的抗糖尿病药物（Avandia）的使用下降（Avandia）（Avandia） 出版物显示出严重的心血管风险。在这些情况下，最有效的分发模式 应该体验适合较不合适的患者使用最大的使用情况。 AIM 4检查了具有未知甚至不利后果的治疗的扩散，例如快速 ICU床容量的某些地区（但没有其他地区）的增长。研究团队将研究网络， “外部”治疗的扩散模式 - 非法行为是由利润促进的，没有利益 患者，一个例子是2002 - 2005年免疫球蛋白输注的兴衰。最后， 研究小组将使用这四个目标的结果返回中心假设：可以观察到 特定治疗特异性扩散的差异解释了健康结果的区域变化的观察模式 和支出？