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

项目摘要/摘要 药物不良反应是导致死亡的主要原因，另外还开出了数千名患者的处方 没有任何益处的药物。药物基因组学使基因变异的发现成为可能 影响数百种药物的反应或毒性，但此类信息在临床上很少见 被利用了。由于医生知识贫乏、检测途径有限、延误，实施工作受到阻碍 在获得结果方面，以及基因组实施的信息学障碍。也有人对此持怀疑态度 药物基因组学的临床实用性，支持了临床疗效随机检查的必要性。 这就是我们提出这个项目的原因，这个项目的目的是了解一部小说 提供患者特定药物基因组信息的决策支持工具可以证明 基因知情处方减少围手术期和重症监护中的不适当用药 设置。我们之前开发和研究了这个名为基因组描述系统(GPS)的工具，其中包括 在过去的五(5)年中，我们机构的门诊医生-患者配对。GPS先发制人地合并了- 获得患者特定的药物基因组学结果，并将其转化为临床决策支持 摘要。这个模型的意义在于它解决了基因组的几个主要障碍 实施/传播--需要在护理地点即时获取成果，翻译 将基因组信息转化为决策逻辑，并提供关于基因组学的教育/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 信息在围手术期环境中具有独特的中介或意想不到的障碍，在那里，麻醉师 重症监护提供者很快就会做出许多高风险的处方决定。此外，在 围手术期设置预先识别基因组易感性增加的患者的想法 用药风险具有比其他临床筛查更大的临床附加值的潜力 人群，因为对于许多围手术期患者来说，这将是第一次进行手术(因此 第一次接触各种相关的围手术期药物)。 我们的假设是，个性化护理的医疗实施模式使相关 在处方时即时获取的药物基因组信息将减少 药物基因组学结果为阳性的患者使用不适当和高风险药物 为人所知。这一假设是基于这样一个前提：基因组发现的有效临床翻译 将受到系统/技术变化和临床医生行为变化的影响。对公众的影响 健康不仅来自我们使用的技术，也来自于我们对决策的理解 在精准医学时代推广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.