Hierarchical models of prescription drug use in the elderly

描述（由申请人提供）：本提案中概述的五年指导研究和培训计划旨在将生物统计学家Brookhart博士培养成为一名在老年病学，生物统计学和药物流行病学交叉领域工作的独立调查员。本提案的主要研究目的是开发和应用分层统计模型来研究老年人处方药物使用的复杂模式，这是一个具有重要临床和政策意义的领域。可用于了解药物使用的数据具有多层结构，包括对聚集在医生、实践和地理区域内的患者的重复观察。为了捕捉数据的复杂结构并回答有关老年患者处方药使用的重要实质性问题，我们建议采用现代统计方法对分层数据进行分析。随着人们对处方药的适当使用和成本的日益关注，特别是随着新的医疗保险药物福利，这种开处方和坚持服药的模式可以在改善药物使用方面发挥重要作用。通过了解处方药使用的常见模式，可以设计有针对性和具有成本效益的质量改进干预措施。在该奖项的最后阶段，候选人将开发多层次统计方法，用于创建患者、医生、实践和地区概况，可用于目标质量改进干预措施，旨在促进更适当的处方和更高水平的患者对有效治疗的依从性。不同的分析方法将作为未来R01提案的一部分进行试点测试和比较。本建议中概述的指导研究将由一个正式的培训方案加以补充，该方案将包括老年学、老年病学、慢性病流行病学、健康行为理论、处方药和保健政策以及保健服务研究等课程；与导师和其他资深教员定期会面；参加研讨会、讲习班和学术会议；系统地接触临床老年病学，包括在门诊、住院和长期护理环境中度过的时间。

DESCRIPTION (provided by applicant): The five year program of mentored research and training outlined in this proposal is designed to develop Dr. Brookhart, a biostatistician, into an independent investigator working at the intersection of geriatrics, biostatistics, and drug epidemiology. The primary research aim of this proposal is the development and application of hierarchical statistical models for the study of complex patterns of prescription drug use by the elderly, an area of great clinical and policy importance. The data that are available to understand medication use have a multilevel structure consisting of repeated observations on patients who cluster within physicians, practices, and geographic regions. To capture the complex structure of the data and answer important substantive questions about prescription drug use by older patients, we propose to employ modern statistical approaches for the analysis of hierarchical data. With increasing concern over the appropriate use and cost of prescription drugs, particularly with the new Medicare drug benefit, such models of prescribing and adherence can play an important role in improving the use of medications. By understanding common patterns of prescription medication use, targeted and cost-effective quality improvement intervention can be designed. In the final phase of this award the candidate will develop multilevel statistical approaches for creating patient, physician, practice, and region profiles that can be used to target quality improvement interventions that aim to promote more appropriate prescribing and higher levels of patient adherence to effective therapies. Different profiling approaches will be pilot tested and compared as part of a future R01 proposal. The mentored research outlined in this proposal will be complemented by a formal training program that will involve coursework in gerontology, geriatrics, chronic disease epidemiology, theories of health behavior, prescription drug and health care policy, and health services research; regular meetings with mentors and other senior faculty; attendance at seminars, workshops, and academic conferences; and systematic exposure to clinical geriatrics including time spent in outpatient, inpatient, and long-term care environments.