Four State Disability and Health Data Analysis Collaboration

四个州残疾和健康数据分析合作

• 批准号: 10685367
• 负责人: Terry T-K Huang
• 金额: $ 24万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-30 至 2024-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10685367
• 关键词: Four; State; Disability; Health; Data

ABSTRACT Since 2010, clinical medicine has benefited from a rapid surge of clinical research on chronic diseases using data from electronic health records (EHRs). EHRs are appealing because they can offer large sample sizes, timely information, and a wealth of clinical, diagnostic, and laboratory information. However, while millions of patient records are included in large EHR databases, there is poor understanding about the completeness, validity and reliability of information that can be extracted from EHR records on patient populations, and data from EHR networks are not population-representative, constraining their utility for population health surveillance. In this proposal, we propose to leverage our longstanding expertise in developing EHR surveillance indicators, work we have done in partnership with the NYC Health department, and expand the partnership to include the New York State Department of Health and investigators from the NYU Comprehensive Cancer Center. Our goal is to design and test the feasibility of a model surveillance report that includes performance measures and quality of cancer prevention and control in ambulatory care. Indicators will be developed using rules-based testing approaches, and then validated using well-established chart review methods to assess sensitivity and specificity.. We offer: (1) access to a very large EHR network that actively uses the same OMOP CDM employed by the entire PCORNet distributed research network (11 sites) across the country, providing opportunities for future scalability; (2) access to EHR data covering a large proportion of residents living in a large metropolitan area, including high proportions of underinsured, low income, racially/ethnically diverse patients; and (3) an investigation team with extensive prior experience analyzing OMOP CDM electronic health databases and performing population health surveillance. Conducting this study in the diverse, urban environment of NYC offers potential to characterize disparities in at-risk populations

抽象的 自2010年以来，临床医学从慢性疾病的临床研究中迅速激增。 来自电子健康记录（EHRS）的数据。 EHR很有吸引力，因为它们可以提供大量样本量， 及时的信息以及大量的临床，诊断和实验室信息。但是，虽然数百万 患者记录包含在大型EHR数据库中，对完整性的了解很差 可以从EHR记录中提取的有关患者人群和数据的信息的有效性和可靠性 来自EHR网络不是人口代表性的，限制了人口健康的效用 监视。在此提案中，我们建议利用我们长期以来发展EHR的专业知识 监视指标，我们与纽约市卫生部门合作完成的工作，并扩展 合作伙伴关系包括纽约州卫生部和纽约大学的调查人员 综合癌症中心。我们的目标是设计和测试模型监视报告的可行性 包括绩效指标和预防癌症和控制质量。指标将 使用基于规则的测试方法开发，然后使用良好的图表审查进行验证 评估灵敏度和特异性的方法。我们提供：（1）访问一个非常大的EHR网络，该网络积极地 使用整个PCORNET分布式研究网络（11个站点）使用的OMOP CDM 该国为未来的可伸缩性提供了机会； （2）访问EHR数据，涵盖了很大一部分 居住在大都市地区的居民，包括大量投资不足的低收入， 种族/种族多样的患者； （3）具有丰富先前经验分析的调查团队 OMOP CDM电子健康数据库和进行人口健康监视。进行这项研究 在各种各样的城市环境中