An Electronic Health Record-Based Tool to Identify Newly Diagnosed Breast Cancer Patients at Risk of Low Social Support

一种基于电子健康记录的工具，用于识别新诊断的乳腺癌患者面临社会支持低的风险

• 批准号: 10643952
• 负责人: CANDYCE H KROENKE
• 金额: --
• 依托单位: KAISER FOUNDATION RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10643952
• 关键词: Academy; Address; African American; Area; Asian; Black race; Breast Cancer Patient; Breast Cancer Treatment; California; Cancer Research Network; Caring; Clinical; Code; Cohort Studies; Data; Data Collection; Development; Diagnosis; Documentation; Electronic Health Record; Emergency Situation; Ethnic Origin; Ethnic Population; Funding; Health; Healthcare Systems; Hispanic; Information Technology; Intervention; Language; Linear Regressions; Link; Literature; Logistic Regressions; Logistics; Marital Status; Measures; Medical; Medical Care Team; Medical Records; Medicine; Minority Women; Natural Language Processing; Newly Diagnosed; Not Hispanic or Latino; Operative Surgical Procedures; Outcome; Pacific Islander; Pathway interactions; Patient risk; Patient-Focused Outcomes; Patients; Perception; Pilot Projects; Population; Provider; Publishing; Questionnaires; ROC Curve; Race; Recommendation; Research; Research Personnel; Resources; Risk; Services; Social Conditions; Social Network; Social support; Source; Structure; Text; Treatment outcome; Woman; Work; analytical method; anticancer research; cancer care; cancer health disparity; chemotherapy; clinical care; clinically relevant; cohort; ethnic disparity; ethnic diversity; ethnic minority; hazard; health care settings; high risk; hormone therapy; improved; improved outcome; malignant breast neoplasm; mortality; patient response; racial disparity; racial diversity; racial minority; racial population; social; social computing; social health determinants; social relationships; social structure; structured data; theories; tool; treatment and outcome; unstructured data

ABSTRACT Social support, a social determinant of health (SDoH), is a definitive predictor of breast cancer (BC) treatment and mortality outcomes. Because of the recognition that social support is critical to BC patient outcomes, clinicians within Kaiser Permanente Northern California (KPNC) have documented information on social support in the electronic health record (EHR) since the advent of Epic in 2005. However, no EHR-based social support measure currently exists to help clinicians identify patients at high risk of low social support. Such a measure has high relevance for addressing racial/ethnic disparities in BC treatment and outcomes. Therefore, we propose to develop an Electronic Health Record Social Support Patient Risk Tool (EHR-SUPPORT) that could be used to identify women with BC at risk of low social support for referral to social support resources. We propose to: 1) Identify terms in the EHR, based on theory and prior literature, and informed by KPNC stakeholders in BC care, that reflect structural and/or functional social support, and have been associated with BC treatment and outcomes; 2) Develop EHR-SUPPORT, using structured, semi-structured, and unstructured data (to include natural language processing of text) that identifies patients at risk of low social support, overall and by race/ethnicity, and validate the measure against published social support measures; and 3) Evaluate associations of EHR-SUPPORT and its component variables with BC treatment (surgery and chemotherapy delays, nonadherence to hormonal therapy) and BC-specific and total mortality, overall and by race/ethnicity in 44,348 women diagnosed with stage I-IV BC within Kaiser Permanente Northern California between 2006- 2023 including 3,450 Black, 4,441 Hispanic, 6,571 Asian women, and 28,589 non-Latina white women. In an exploratory aim, we will develop, with KP clinician stakeholders, steps to the implementation of EHR- SUPPORT. We will review 100 medical records (25 in each race/ethnic group) within two months of diagnosis, informed by investigator expertise and clinician stakeholders, to develop terms used to describe patient support. In addition to developing structured data, we will use natural language processing of text fields to further develop social support indicators (Aim 1). EHR-SUPPORT will be computed from social support indicators; we will use linear and logistic regression to validate the developed measure against established social support measures in Pathways, a well-established cohort of 4,505 women with BC and use factor analytic and confirmatory factor analytic methods as well as ROC curves to further evaluate the score (Aim 2). We will use linear, logistic, and Cox proportional hazards regression to evaluate associations in Aim 3. The unique convergence of EHR and cohort data provides the first opportunity to develop and validate an EHR- based social support measure in in diverse women with BC, adjusted for an extensive set of covariates. This work is central to identifying patients at elevated risk of low social support and to enhancing social support- cancer research needed to improve clinical care and reduce BC disparities.

抽象的 社会支持是健康的社会决定因素 (SDoH)，是乳腺癌 (BC) 治疗的明确预测因素 和死亡率结果。由于认识到社会支持对于 BC 患者的治疗结果至关重要， 北加州凯撒医疗机构 (KPNC) 的临床医生已记录有关社交的信息 自 2005 年 Epic 出现以来，电子健康记录 (EHR) 得到了支持。然而，还没有基于 EHR 的社交媒体 目前存在的支持措施可以帮助临床医生识别社会支持低风险高的患者。这样一个 该措施对于解决 BC 治疗和结果中的种族/民族差异具有高度相关性。所以， 我们建议开发电子健康记录社会支持患者风险工具（EHR-SUPPORT） 可用于识别患有 BC 的女性面临社会支持较低的风险，以便转介至社会支持资源。 我们建议：1) 根据理论和先前文献，并由 KPNC 告知，确定 EHR 中的术语 BC 护理中的利益相关者，反映结构性和/或功能性社会支持，并与 BC 治疗和结果； 2) 使用结构化、半结构化和非结构化开发 EHR-SUPPORT 识别总体上处于低社会支持风险的患者的数据（包括文本的自然语言处理） 按种族/民族，并根据已发布的社会支持措施验证该措施； 3) 评估 EHR-SUPPORT 及其组成变量与 BC 治疗（手术和化疗）的关联 延迟、不遵守激素治疗）以及 BC 特定死亡率和总死亡率（总体死亡率和按种族/族裔划分） 2006 年至 2006 年期间，北加州 Kaiser Permanente 共有 44,348 名女性被诊断患有 I-IV BC 期 BC 到 2023 年，其中包括 3,450 名黑人、4,441 名西班牙裔、6,571 名亚裔女性和 28,589 名非拉丁裔白人女性。在一个 为了探索性目标，我们将与 KP 临床医生利益相关者一起制定实施 EHR 的步骤 支持。我们将在诊断后两个月内审查 100 份医疗记录（每个种族/民族 25 份）， 由研究者的专业知识和临床医生利益相关者提供信息，制定用于描述患者的术语 支持。除了开发结构化数据之外，我们还将使用文本字段的自然语言处理来 进一步制定社会支持指标（目标 1）。 EHR-SUPPORT 将根据社会支持计算 指标；我们将使用线性和逻辑回归来根据既定的方法验证开发的措施 Pathways 中的社会支持措施，这是一个由 4,505 名 BC 女性组成的成熟队列和使用因子 分析和验证因素分析方法以及ROC曲线以进一步评估分数（目标2）。 我们将使用线性、逻辑和 Cox 比例风险回归来评估目标 3 中的关联。 EHR 和队列数据的独特融合为开发和验证 EHR- 基于不同 BC 女性的社会支持测量，并针对一组广泛的协变量进行了调整。这 工作对于识别社会支持水平较低风险较高的患者以及增强社会支持至关重要 癌症研究需要改善临床护理并减少 BC 差异。

项目成果

Examining the Association of Social Needs with Future Health Care Utilization in an Older Adult Population: Which Needs Are Most Important?

• DOI: 10.1089/pop.2023.0171
• 发表时间: 2023-12-01
• 期刊: POPULATION HEALTH MANAGEMENT
• 影响因子: 2.5
• 作者: Mosen，David M.;Banegas，Matthew P.;Dickerson，John F.
• 通讯作者: Dickerson，John F.

Impact of Racial/Ethnic Discrimination on Quality of Life Among Breast Cancer Survivors.

种族/民族歧视对乳腺癌幸存者生活质量的影响。

• DOI: 10.1093/aje/kwac208
• 发表时间: 2023
• 期刊: American journal of epidemiology
• 影响因子: 5
• 作者: Shariff-Marco,Salma;Sangaramoorthy,Meera;Ellis,Libby;Thomsen,Catherine;Roh,JaniseM;Kroenke,Candyce;Valice,Emily;Kwan,MarilynL;Ambrosone,Christine;Kushi,Lawrence;Gomez,ScarlettLin
• 通讯作者: Gomez,ScarlettLin

Role of dietary patterns and acculturation in cancer risk and mortality among postmenopausal Hispanic women: results from the Women's Health Initiative (WHI).

• DOI: 10.1007/s10389-020-01342-8
• 发表时间: 2022-04
• 期刊: Zeitschrift fur Gesundheitswissenschaften = Journal of public health

Social Isolation and Incident Heart Failure Hospitalization in Older Women: Women's Health Initiative Study Findings.

• DOI: 10.1161/jaha.120.022907
• 发表时间: 2022-03
• 期刊: JOURNAL OF THE AMERICAN HEART ASSOCIATION
• 影响因子: 5.4
• 作者: Cene, Crystal W.;Leng, Xiaoyan Iris;Faraz, Khushnood;Allison, Matthew;Breathett, Khadijah;Bird, Chloe;Coday, Mace;Corbie-Smith, Giselle;Foraker, Randi;Ijioma, Nkechinyere N.;Rosal, Milagros C.;Sealy-Jefferson, Shawnita;Shippee, Tetyana P.;Kroenke, Candyce H.
• 通讯作者: Kroenke, Candyce H.

Associations Between Changes in Loneliness and Social Connections, and Mental Health During the COVID-19 Pandemic: The Women's Health Initiative.

• DOI: 10.1093/gerona/glab371
• 发表时间: 2022-12-06
• 期刊: The journals of gerontology. Series A, Biological sciences and medical sciences
• 作者: Goveas JS;Ray RM;Woods NF;Manson JE;Kroenke CH;Michael YL;Shadyab AH;Meliker JR;Chen JC;Johnson L;Mouton C;Saquib N;Weitlauf J;Wactawski-Wende J;Naughton M;Shumaker S;Anderson GL
• 通讯作者: Anderson GL