PhendoPHL:A Data-Science Enabled Personal Health Library to Manage Endometriosis

PhendoPHL：基于数据科学的个人健康库，用于管理子宫内膜异位症

• 批准号: 10391429
• 负责人: NOEMIE ELHADAD
• 金额: $ 35.24万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-02-07 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10391429
• 关键词: Affect; Age; Anxiety; Arthralgia; Behavior; Chronic; Clinical; Clinical Data; Competence; Complex; Computing Methodologies; Critical Incident Technic; Data; Data Science; Development; Disease; Eating; Evaluation; Evaluation Studies; Fatigue; Focus Groups; Goals; Health; Individual; Informatics; Information Systems; Intervention; Interview; Knowledge; Libraries; Methodology; Methods; Monitor; Moods; Outcome; Pain; Participant; Patients; Pattern; Perception; Population; Productivity; Provider; Public Health Informatics; Quality of life; Reporting; Research; Self Determination; Self Management; Signs and Symptoms; Soy Sauce; Specialist; Standardization; Steam; Strategic Planning; Strategic vision; Surveys; Symptoms; Time; Time Series Analysis; Time trend; United States National Institutes of Health; United States National Library of Medicine; Validation; Visit; Visualization; Woman; Women' s Health; Work; base; data streams; data visualization; design; endometriosis; experience; experimental study; girls; interest; novel; peer; population based; recruit; reproductive; shared decision making; statistical learning; theories; usability; user centered design

PROJECT SUMMARY Endometriosis is a chronic condition which is estimated to affect 10% of women in reproductive age. It has a very high burden on quality of life and productivity, and the self-management needs of women living with the disease are multiple. This project aims to design, develop, and evaluate a data-science enabled personal health library called PhendoPHL to support the self-management needs of women living with endometriosis. Grounded in self-determination theory, and informed by user-centered design methods PhendoPHL will enable exploration of health patterns through interactive visualizations of integrated clinical and self-tracked data, identify temporal personalized patterns and comparison to population norms through novel data-science methods, and provide actionable visualizations of data for shared decision making during patient-provider encounters. PhendoPHL builds on our existing work in novel informatics methods for endometriosis, and the extensive experience of our research team in designing and evaluating novel informatics interventions. The proposed work also fills a research gap in personal health informatics: the development and validation of novel computational methods to identify personalized and population- based patterns in clinical and self-monitoring data; both types of data which are critical to successful self- management and challenging from a computational standpoint because they are temporal, heterogeneous, and sparse. Using a mixed-methods evaluation study (standardized surveys, logfile analysis, Critical Incident Technique interviews, focus groups), we will study PhendoPHL’s usability, assess the factors critical to user engagement and perceived impact on self-determination and shared decision making, and the generalizability to other reproductive chronic conditions in women’s health.

项目摘要 子宫内膜异位症是一种慢性疾病，估计影响10%的育龄妇女。它有一个 对生活质量和生产力造成很大负担， 疾病是多种多样的。该项目旨在设计、开发和评估一个支持数据科学的个人 名为PhendoPHL的健康图书馆，以支持患有艾滋病的妇女的自我管理需求 子宫内膜异位症以自我决定理论为基础，以用户为中心的设计方法为基础 PendoPHL将通过整合的交互式可视化来探索健康模式 临床和自我跟踪数据，识别时间个性化模式并与人群标准进行比较 通过新颖的数据科学方法，并为共享决策提供可操作的数据可视化 在病人和提供者的接触中。PendoPHL建立在我们现有的新信息学工作的基础上 子宫内膜异位症的方法，以及我们的研究团队在设计和评估子宫内膜异位症的方法方面的丰富经验， 新的信息学干预。拟议的工作还填补了个人健康信息学的研究空白： 开发和验证新的计算方法，以确定个性化和群体- 基于临床和自我监测数据的模式;这两种类型的数据对成功的自我监测至关重要， 管理和挑战，因为它们是时间的，异构的， 而且稀疏。使用混合方法评估研究（标准化调查、日志文件分析、关键 事件技术访谈，焦点小组），我们将研究PhendoPHL的可用性，评估因素 对用户参与和对自决和共同决策的感知影响至关重要， 妇女健康中其他生殖慢性病的普遍性。