Vanderbilt Genome-Electronic Records (VGER) Project

范德比尔特基因组电子记录 (VGER) 项目

• 批准号: 10771648
• 负责人: DAN M RODEN
• 金额: $ 10.66万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-15 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10771648
• 关键词: Academic Medical Centers; Accidents; Administrative Supplement; Affect; Caring; Clinical; Clinical Data; Clinical Research; Collaborations; Collection; Computerized Medical Record; Data; Data Collection; Development; Disclosure; Electronic Health Record; Electronic Medical Records and Genomics Network; Electronics; Endocrinology; Enrollment; Ensure; Equipment and supply inventories; Equity; Ethics; Exclusion; Family; Fast Healthcare Interoperability Resources; Foundations; Fright; Gender; Gender Identity; Genetic; Genetic Research; Genome; Genomics; Glean; Goals; Health; Health system; Healthcare Systems; Individual; Informatics; Intervention; Interview; Lead; Medical Genetics; Methods; Modeling; Names; Organ; Participant; Patients; Personal Satisfaction; Persons; Phenotypic Sex; Population; Population Heterogeneity; Procedures; Process; Qualitative Methods; Qualitative Research; Reaction; Recommendation; Recording of previous events; Records; Reporting; Research; Research Ethics; Research Personnel; Resources; Risk; Risk Assessment; Sex Characteristics; Sexual and Gender Minorities; Site; Social Impacts; Specific qualifier value; Structure; Testing; Tissues; Underserved Population; Work; automated intervention; clinical care; cultural competence; data modeling; data quality; design; experience; gender diversity; gender minority group; gene therapy; genetic testing; genomic data; genotypic sex; improved; insight; instrument; interest; member; novel; patient engagement; psychological distress; psychosocial; research study; response; sex; transgender

It is critical to collect gender identity data to ensure affirming and equitable genetics care for transgender, gender diverse, and sex diverse (TGSD) patients. Further, a person’s phenotypic sex (expression of primary, secondary, and endocrinological sex characteristics), chromosomal sex, and organ/tissue inventory can directly impact crucial aspects of testing and care recommendations. However, TGSD individuals can experience psychosocial and clinical harms if gender/sex data collection and related care are not culturally competent and accurate. Realistic fears about such harms could deter TGSD individuals from participating in clinical research, and enrolled TGSD participants may experience harms from participation if data models and study processes do not appropriately account for these variables. Automated processes are increasingly used to streamline care and reduce health system burden, yet these processes increase the risk of misgendering participants or providing clinically inappropriate recommendations if these data are not accurate. The Electronic Medical Records and Genomics (eMERGE) Network is collecting sex/gender data at two points with different question/response options, offering an opportunity to evaluate the impact of a large electronic health record (EHR)-integrated genomics research study on TGSD individuals. The Network is evaluating the influence of a novel EHR-integrated integrated genome-informed risk assessment (GIRA) report on clinical care in 25,000 patients across 10 sites. The GIRA relies on data in the sex field to automate inclusion of recommendations on the report for certain conditions, and as a result has the potential to negatively impact TGSD participants. In this supplement application to the Vanderbilt Genome-Electronic Records (VGER) Project, which supports the Vanderbilt University Medical Center site of the eMERGE Network, we will use in- depth semi-structured qualitative interviews to investigate the impact of the eMERGE data collection, data usage, and processes on the validity of the GIRA for TGSD individuals and on potential psychosocial and clinical harms from the study on this population. We will use information gleaned in these interviews to develop a best practice guide for genomics research involving TGSD populations and propose a model for data collection that can support such research while remaining culturally competent and accurate. This model will be included in the FHIR specification for the GIRA. This supplement directly supports the overall project goals to validate and improve upon the GIRA.

必须收集性别认同数据，以确保对变性人的肯定和公平的遗传护理， 性别多样性和性别多样性（TGSD）患者。此外，一个人的表型性别（原发性， 继发性和内分泌性特征）、染色体性别和器官/组织库存可以 直接影响测试和护理建议的关键方面。然而，TGSD个人可以 如果性别/性数据收集和相关护理在文化上不符合 胜任和准确。对这种危害的现实恐惧可能会阻止TGSD个人参与 临床研究，入组的TGSD参与者可能会因参与数据模型和 研究过程没有适当考虑这些变量。越来越多地使用自动化流程 简化护理和减少卫生系统负担，但这些过程增加了性别错误的风险 如果这些数据不准确，参与者或提供临床不适当的建议。的 电子病历和基因组学网络（eMERGE）正在两个点收集性/性别数据， 不同的问题/回答选项，提供了一个机会，以评估一个大型电子健康的影响， 记录（EHR）-对TGSD个体的整合基因组学研究。该网络正在评估 整合EHR整合基因组信息风险评估（GIRA）报告对临床的影响 在10个站点的25，000名患者中进行护理。GIRA依靠性别领域的数据自动纳入性别问题， 在某些情况下，报告中的建议，因此有可能产生负面影响 TGSD参与者。在这个补充申请的范德比尔特基因组电子记录（VGER） 该项目支持eMERGE网络的范德比尔特大学医学中心网站，我们将在- 深入的半结构化定性访谈，以调查eMERGE数据收集的影响， 使用，并对TGSD个人的GIRA的有效性和潜在的心理社会和 对该人群进行研究的临床危害。我们将利用这些采访中收集到的信息， 涉及TGSD人群的基因组学研究的最佳实践指南，并提出数据模型 收集可以支持这种研究，同时保持文化能力和准确性。这种模式的 GIRA的FHIR规范中。该补充直接支持项目的总体目标 来验证和改进GIRA。

项目成果

High-throughput framework for genetic analyses of adverse drug reactions using electronic health records.

• DOI: 10.1371/journal.pgen.1009593
• 发表时间: 2021-06
• 期刊: PLoS genetics
• 影响因子: 4.5
• 作者: Zheng NS;Stone CA;Jiang L;Shaffer CM;Kerchberger VE;Chung CP;Feng Q;Cox NJ;Stein CM;Roden DM;Denny JC;Phillips EJ;Wei WQ
• 通讯作者: Wei WQ

DDIWAS: High-throughput electronic health record-based screening of drug-drug interactions.

DDIWAS：基于高通量电子健康记录的药物间相互作用筛查。

• DOI: 10.1093/jamia/ocab019
• 发表时间: 2021
• 期刊: Journal of the American Medical Informatics Association : JAMIA
• 作者: Wu,Patrick;Nelson,ScottD;Zhao,Juan;StoneJr,CosbyA;Feng,QiPing;Chen,Qingxia;Larson,EricA;Li,Bingshan;Cox,NancyJ;Stein,CMichael;Phillips,ElizabethJ;Roden,DanM;Denny,JoshuaC;Wei,Wei-Qi
• 通讯作者: Wei,Wei-Qi

ConceptWAS: a high-throughput method for early identification of COVID-19 presenting symptoms.

ConceptWAS：一种用于早期识别出现症状的 COVID-19 的高通量方法。

• DOI: 10.1101/2020.11.06.20227165
• 发表时间: 2020
• 期刊: medRxiv : the preprint server for health sciences
• 作者: Zhao,Juan;Grabowska,MonikaE;Kerchberger,VernEric;Smith,JoshuaC;Eken,HNur;Feng,QiPing;Peterson,JoshF;Rosenbloom,STrent;Johnson,KevinB;Wei,Wei-Qi
• 通讯作者: Wei,Wei-Qi

PheMap: a multi-resource knowledge base for high-throughput phenotyping within electronic health records.

• DOI: 10.1093/jamia/ocaa104
• 发表时间: 2020-11-01
• 期刊: Journal of the American Medical Informatics Association : JAMIA
• 作者: Zheng NS;Feng Q;Kerchberger VE;Zhao J;Edwards TL;Cox NJ;Stein CM;Roden DM;Denny JC;Wei WQ
• 通讯作者: Wei WQ

Phenome-Wide Association Studies.

• DOI: 10.1001/jama.2021.20356
• 发表时间: 2022-01-04
• 期刊: JAMA
• 作者: Bastarache L;Denny JC;Roden DM
• 通讯作者: Roden DM