Improving medication safety for nursing home residents prescribed psychotropic dr

提高疗养院居民精神药物处方的用药安全

• 批准号: 8634379
• 负责人: Richard David Boyce
• 金额: $ 11.44万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-12-01 至 2016-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8634379
• 关键词: Address; Adoption; Adverse event; Aging; Antidepressive Agents; Antipsychotic Agents; Applications Grants; Artificial Intelligence; Clinical; Clinical Research; Collaborations; Complement; Data; Delirium; Detection; Doctor of Philosophy; Dose; Drug Combinations; Drug Interactions; Effectiveness; Elderly; Event; Fatigue; Feasibility Studies; Focus Groups; Future; Geriatric Psychiatry; Geriatrics; Goals; Government; Group Interviews; Guidelines; Health; High Prevalence; Informatics; Intervention; Interview; Jordan; Knowledge; Learning; Mentored Research Scientist Development Award; Mentors; Methods; Modeling; Monitor; Mood stabilizers; National Institute on Aging; Nurse Practitioners; Nurses; Nursing Homes; Outcome; Patient Monitoring; Patients; Perception; Pharmaceutical Preparations; Pharmacists; Pharmacoepidemiology; Physicians; Pilot Projects; Psychotropic Drugs; Public Health; Reporting; Research; Research Activity; Research Methodology; Research Training; Risk; Risk Factors; Safety; Science; Series; Solid; Syndrome; System; Training; Training Activity; Training Support; Translating; United States; Universities; Vent; Work; base; biomedical informatics; career; career development; comparative; comparative effectiveness; design; effective intervention; effectiveness research; electronic data; experience; fall risk; falls; high risk; hypnotic; improved; innovation; interdisciplinary approach; professor; prognostic; prototype; sedative; therapy design

DESCRIPTION (provided by applicant): Richard D. Boyce, PhD is an Assistant Professor of Biomedical Informatics at the University of Pittsburgh. He has training in informatics, pharmacoepidemiology, and comparative effectiveness research as well as a strong commitment to improving medication safety for older adults. His prior work has focused on artificial intelligence methods for predicting drug-drug interactions and the comparative safety of antidepressants for treating de- pressed nursing home residents. The current proposal is for a three year Mentored Research Scientist Development Award (K01) from the National Institute on Aging for training and support that will address gaps in his knowledge of aging research and the nursing home setting. In collaboration with his mentoring team (Drs. Charles Reynolds, Jordan Karp, and Steven Handler) he has developed a training and research plan that will both fill in these knowledge gaps and prepare him for an independent research career. The overarching goal of his K01 is to become an expert on how to effectively translate research results from pharmacoepidemiology and comparative effectiveness research to informatics interventions that improve medication safety for older adults, especially nursing home residents. To accomplish this goal, he proposes eight career development activities and two research aims that will help him 1) obtain rigorous training in the science and practice of creating clinical decision support interventions that are effective in the nursing home setting; 2) obtain a thorough understanding of how falls and fall risk factors are detected, monitored, reported, and assessed in the nursing home setting; and 3) learn the perceptions of multiple nursing home clinician stakeholders on what research is needed to help reduce medication-related adverse events. The two research aims will enable him to integrate and apply the knowledge that he will gain through the proposed training activities by exploring the feasibility and potential clinical usefulness of actively monitoring patients exposed to psycho- tropic PDDIs. The approach would use electronic data available in most United States (US) NHs to provide highly specific and actionable alerts to physicians and/or nurses when a resident who is exposed to a PDDI involving a psychotropic drug transitions to a state of unacceptably high risk for experiencing a fall. Dr. Boyce's hypothesis is that this approach will extend the ability of NH clinicians to perform the recommended "diligent monitoring" of PDDIs, while avoiding alert fatigue. He anticipates that the approach would be generalizable to other prevalent NH ADEs (e.g., delirium) and other drug classes (e.g., mood stabilizers). This proposal is relevant to public health because it will explore an innovative approach to managing PDDIs that may ultimately re- duce the occurrence of one of the most prevalent multifactorial geriatric syndromes (falls). It wil also inform an R-series grant proposal to study a mature intervention that Dr. Boyce plans to submit in year 2 of the project.

描述（由申请人提供）：Richard D.博伊斯博士是匹兹堡大学生物医学信息学助理教授。他接受过信息学、药物流行病学和比较有效性研究方面的培训，并坚定地致力于改善老年人的用药安全。他之前的工作主要集中在预测药物相互作用的人工智能方法以及药物的相对安全性。 用于治疗疗养院居民抑郁症的抗抑郁药。目前的提案是由国家老龄化研究所颁发的为期三年的指导研究科学家发展奖（K 01），用于培训和支持，以解决他在老龄化研究和养老院环境知识方面的差距。在与他的导师团队（查尔斯·雷诺兹博士，乔丹·卡普和史蒂芬·诺伊斯）的合作中，他制定了一个培训和研究计划，既填补了这些知识空白，又为他的独立研究生涯做好了准备。他的K 01的总体目标是成为如何有效地将药物流行病学和比较有效性研究的研究结果转化为信息学干预措施的专家，以提高老年人，特别是养老院居民的用药安全性。为了实现这一目标，他提出了八个职业发展活动和两个研究目标，这将有助于他1）获得严格的培训，在科学和实践中创造临床决策支持干预措施，是有效的护理之家设置; 2）获得一个全面的了解如何福尔斯和跌倒风险因素的检测，监测，报告，并在护理之家设置评估;以及3）了解多个护理之家临床医生利益相关者对需要进行哪些研究以帮助减少药物相关不良事件的看法。这两个研究目标将使他能够整合和应用他将通过探索主动监测暴露于精神性PDDI的患者的可行性和潜在临床用途，通过拟议的培训活动获得的知识。该方法将使用大多数美国（US）NH中可用的电子数据，当暴露于涉及精神药物的PDDI的居民转变为经历跌倒的不可接受的高风险状态时，向医生和/或护士提供高度具体和可操作的警报。博伊斯博士的假设是，这种方法将扩展NH临床医生执行推荐的PDDI“勤奋监测”的能力，同时避免警觉疲劳。他预计，这种方法将推广到其他流行的NH ADE（例如，谵妄）和其它药物类别（例如，情绪稳定剂）。该提案与公共卫生相关，因为它将探索一种管理PDDI的创新方法，最终可能减少最常见的多因素老年综合征（福尔斯）之一的发生。它还将通知R系列赠款提案，以研究博伊斯博士计划在项目第二年提交的成熟干预措施。