Improving identification and healthcare for patients with Inherited Cancer Syndromes: Evidence-based EMR implementation using a web-based computer platform

改善遗传性癌症综合征患者的识别和医疗保健：使用基于网络的计算机平台实施基于证据的 EMR

• 批准号: 10831647
• 负责人: Lori Ann Orlando
• 金额: $ 10万
• 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: 2023-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10831647
• 关键词: Address; Administrative Supplement; Affect; Algorithms; Caring; Characteristics; Clinical; Collaborations; Communities; Computerized Medical Record; Computers; Data; Data Collection; Data Element; Disease; Doctor of Philosophy; Early identification; Electronic Medical Records and Genomics Network; Electronics; Elements; Endocrinology; Enrollment; Ensure; Equipment and supply inventories; Equity; Exclusion; Exposure to; Family; Family health status; Feedback; Fright; Future; Gender; Gender Identity; Genetic; Genetic Counseling; Genome; Genomics; Goals; Guidelines; Health; Healthcare; Healthcare Systems; Hereditary Malignant Neoplasm; Hereditary Neoplastic Syndromes; Hormonal; Individual; Inherited; Intercept; Intersex; Intervention; Interview; Knowledge; Lead; Malignant Neoplasms; Mammary Gland Parenchyma; Mastectomy; Measures; Medical; Medical Records; Modeling; Online Systems; Organ; Outcome; Participant; Patient Care; Patients; Personal Satisfaction; Phenotypic Sex; Pilot Projects; Population; Population Heterogeneity; Procedures; Process; Publishing; Qualitative Research; Recommendation; Recording of previous events; Reduce health disparities; Research; Research Personnel; Residual state; Risk; Risk Assessment; Sex Characteristics; Sexual and Gender Minorities; Structure; Students; Syndrome; System; Testing; Tissues; Training; Trees; Update; Work; assessment application; cancer care; cancer risk; career; clinical application; clinical care; community engagement; cultural competence; data modeling; data quality; design; early onset; evidence base; experience; falls; gender diversity; gender minority group; genetic pedigree; genetic risk assessment; genomic data; genotypic sex; hormone therapy; improved; information gathering; insight; interest; lifetime risk; marginalized community; marginalized population; member; model development; nonbinary; outreach; parent grant; phase 4 study; prevent; programs; psychosocial; reproductive development; research study; response; screening; sex; sex assigned at birth; sex development disorder; therapy design; tool; transgender

PROJECT ABSTRACT Hereditary cancers are prevalent and cause high lifetime risk of cancer. Early identification of at-risk individuals is imperative to prevent and intercept cancer, but hereditary cancer risk screening lags behind guidelines - a care gap that is wider for medically marginalized communities. Transgender, gender diverse, and sex diverse (TGSD) patients represent one such marginalized community who could benefit from better cancer care, including hereditary cancer risk screening. Phenotypic sex, chromosomal sex, current and past organ/tissue inventory, and hormonal milieu impact risk assessment and care for hereditary cancer syndromes. These elements have unique implications for TGSD individuals. While electronic apps represent an important strategy to reduce health disparities by systematizing risk assessment, these apps collect sex-related variables that are used in risk calculations; culturally incompetent, and thus inaccurate, collection of this data could cause participants to receive an incorrect risk assessment result, ultimately impacting downstream care. The parent grant of the proposed project, the Family History and Cancer Risk Study (FOREST), has implemented a risk assessment app, called MeTree, to increase systematization of risk assessment. MeTree collects sex- and gender-related data, and the sex-related data element drives risk assessment result return. However, following preliminary implementation of Me Tree with just over 300 participant responses, we have found inconsistency of the interpretation of the sex-related field among TGSD individuals, leading to sex-related responses that, based on medical record review, do not correspond with expected response domains for this question. This is likely due to question and response wording and options. Very few measures have been designed with community engagement of TGSD individuals, and no such measures have been designed for genetic risk assessment. We propose engagement with TGSD participants and community members to integrate participant feedback directly into a redesign of the Me Tree sex- and gender-related questions and response options. In semi-structured qualitative interviews with TGSD FOREST participants exposed to MeTree, we will seek to understand participant interpretations of these questions, data validity, and collect participant ideas for respectful and accurate redesign. Using rapid initial analyses of these interviews, we will incorporate changes into a new model for presentation in community engagement panels with panelists who have not been exposed to Me Tree within the study. In these panels, we will engage in co-design with TGSD community members to generate a final Me Tree model that respectfully and accurately collects elements needed for risk assessment. The entire research study will be led by transgender researchers, giving them a unique relational perspective that will facilitate addressing cisnormative assumptions present in current sex- and gender-related data models. Final analyses will be published, and changes incorporated into the MeTree app.

项目摘要 遗传性癌症很普遍，并导致终生患癌症的高风险。早期识别高危人群对于预防和拦截癌症至关重要，但遗传性癌症风险筛查落后于指南——对于医疗边缘化社区来说，护理差距更大。跨性别、性别多样化和性别多样化 (TGSD) 患者代表了这样一个边缘化群体，他们可以受益于更好的癌症护理，包括遗传性癌症风险筛查。表型性别、染色体性别、当前和过去的器官/组织清单以及激素环境影响遗传性癌症综合征的风险评估和护理。这些元素对 TGSD 个体具有独特的影响。虽然电子应用程序是通过系统化风险评估来减少健康差异的重要策略，但这些应用程序收集用于风险计算的与性别相关的变量；如果文化上不合格，因此收集的数据不准确，可能会导致参与者收到不正确的风险评估结果，最终影响下游护理。家族史和癌症风险研究 (FOREST) 拟议项目的母方资助实施了一款名为 MeTree 的风险评估应用程序，以提高风险评估的系统化程度。 MeTree收集性别和性别相关数据，性别相关数据元素驱动风险评估结果返回。然而，在 Me Tree 初步实施后，仅收到超过 300 名参与者的反馈，我们发现 TGSD 个体对性别相关领域的解释不一致，导致基于医疗记录审查的性别相关回答与实际情况不相符。该问题的预期响应域。这可能是由于问题和回答的措辞和选项造成的。很少有人设计让 TGSD 个体参与社区参与的措施，也没有为遗传风险评估设计此类措施。我们建议与 TGSD 参与者和社区成员合作，将参与者的反馈直接整合到 Me Tree 性别相关问题和回答选项的重新设计中。在对接触 MeTree 的 TGSD FOREST 参与者进行半结构化定性访谈中，我们将寻求了解参与者对这些问题的解释、数据有效性，并收集参与者的想法，以进行尊重和准确的重新设计。通过对这些访谈的快速初步分析，我们将把变化纳入新的模型中，以便在社区参与小组中与研究中未接触过 Me Tree 的小组成员一起展示。在这些小组中，我们将与 TGSD 社区成员共同设计，生成最终的 Me Tree 模型，该模型尊重且准确地收集风险评估所需的元素。整个研究将由跨性别研究人员领导，为他们提供独特的关系视角，这将有助于解决当前性和性别相关数据模型中存在的顺规范假设。最终分析将被发布，并将更改纳入 MeTree 应用程序中。

项目成果

Conducting inclusive research in genetics for transgender, gender-diverse, and sex-diverse individuals: Case analyses and recommendations from a clinical genomics study.

对跨性别、性别多样化和性别多样化个体进行遗传学包容性研究：临床基因组学研究的案例分析和建议。

• 发表时间: 2023-09-04
• 作者: Bland, Harris T;Gilmore, Marian J;Andujar, Justin;Martin, Makenna A;Celaya;Edwards, Clasherrol;Gerhart, Meredith;Hooker, Gillian W;Kraft, Stephanie A;Marshall, Dana R;Orlando, Lori A;Paul, Natalie A;Pratap, Siddharth;Rosenbloom
• 通讯作者: Rosenbloom