Implementation of Point-of-Care Pharmacogenomic Decision Support in Perioperative Care - Resubmission 01

项目总结/摘要 药物不良反应是导致死亡的主要原因，成千上万的额外患者被处方 没有任何益处的药物。药物基因组学允许发现遗传变异 影响数百种药物的反应或毒性，但这些信息在临床上很少被发现。 利用。由于医生知识贫乏、检测途径有限、延误， 以及基因组实施的信息学障碍。也有人怀疑， 药物基因组学的临床应用，支持临床疗效随机检查的需要。 这是我们提出这个项目的兴趣的起源，这个项目的目的是了解一部小说是否 提供患者特异性药物基因组学信息的决策支持工具可以证明， 遗传信息处方减少了围手术期和重症监护中的不适当药物使用 设置.我们以前开发和研究了这个工具，称为基因组处方系统（GPS）， 在过去的五（5）年里，我们机构的门诊医生-患者配对。全球定位系统结合了先发制人- 获得患者特异性药物基因组学结果，并将其转化为临床决策支持 摘要。该模型的重要性在于它解决了基因组学的几个主要障碍。 实施/传播-需要在护理点即时获得结果， 将基因组信息纳入决策逻辑，并提供有关基因组学的教育/决策支持。 我们有兴趣知道我们采用和使用药物基因组学的概念框架是否 信息在围手术期环境中具有独特的介质或意想不到的障碍， 重症监护提供者会非常迅速地做出许多高风险的处方决定。此外，在 围手术期设置的想法，预先确定患者谁有基因组倾向增加， 药物风险有可能增加临床价值，大于其他临床试验中的筛查价值。 因为对于许多围手术期患者来说，这将是第一次接受手术（因此， 首次暴露于各种相关围手术期药物）。 我们的假设是，个性化护理的医疗实施模型， 药物基因组学信息在开处方时即时可获得， 在药物基因组学结果不正确的患者中使用不适当和高风险药物 知道的这一假设的前提是，基因组发现的有效临床转化 将通过系统/技术变更和临床医生行为的变更进行调节。影响到公共 健康不仅取决于我们使用的技术，还取决于我们对决策的理解 在精准医疗时代促进和采用降低风险行为的过程。

PROJECT SUMMARY/ABSTRACT Adverse drug reactions are a leading cause of death, and thousands of additional patients are prescribed medications which provide no benefit. Pharmacogenomics has allowed the discovery of genetic variants impacting response or toxicity for hundreds of drugs, but such information has infrequently been clinically utilized. Implementation has been hampered by poor physician knowledge, limited avenues for testing, delays in receipt of results, and informatics barriers to genomic implementation. There is also skepticism regarding the clinical utility of pharmacogenomics, underpinning the need for randomized examination of clinical efficacy. This was the genesis for our interest in proposing this project, which aims to understand whether a novel decision-support tool delivering patient-specific pharmacogenomic information can demonstrate that genetically-informed prescribing reduces inappropriate medication use in the perioperative and critical care settings. We previously developed and studied the tool, called the Genomic Prescribing System (GPS), among outpatient physician-patient pairs at our institution over the past five (5) years. GPS incorporates preemptively- obtained patient-specific pharmacogenomic results and translates these into clinical decision support summaries. The significance of this model is that it addresses several of the primary barriers to genomic implementation/dissemination–the need for instantaneous access to results at the point-of-care, translation of genomic information into decision-making logic, and provider education/decision support about genomics. We are interested to know whether our conceptual framework for adoption and use of pharmacogenomic information has unique mediators or unanticipated barriers in the perioperative setting, where anesthesiologists and critical care providers make many high-stakes prescribing decisions very rapidly. Additionally, in the perioperative setting the idea of pre-identifying patients who have genomic predisposition to increased medication risk has the potential for added clinical value that is greater than that for screening in other clinical populations, because for many perisurgical patients, it will be the first time having an operation (and thus the first time being exposed to various associated perioperative drugs). Our hypothesis is that a medical implementation model for personalized care that makes relevant pharmacogenomic information instantaneously accessible at the time of prescribing will reduce the use of inappropriate and high risk medications in patients for whom pharmacogenomic results are known. This hypothesis is based on the premise that the efficacious clinical translation of genomic discovery will be mediated by both systems/technology changes and changes in clinician behaviors. Impact on public health will result not only from the technology we employ but from our understanding of decision-making processes involved in promoting and adopting risk-reductive behavior in the era of precision medicine.