Yoon Sunmoo, Wilcox Adam B, Bakken Suzanne
Columbia University.
EGEMS (Wash DC). 2013 May 31;1(1):1021. doi: 10.13063/2327-9214.1021. eCollection 2013.
To address the electronic health data fragmentation that is a methodological limitation of comparative effectiveness research (CER), the Washington Heights Inwood Informatics Infrastructure for Comparative Effectiveness Research (WICER) project is creating a patient-centered research data warehouse (RDW) by linking electronic clinical data (ECD) from New York Presbyterian Hospital's clinical data warehouse with ECD from ambulatory care, long-term care, and home health settings and the WICER community health survey (CHS). The purposes of the research were to identify areas of overlap between the WICER CHS and two other surveys that include health behavior data (the Behavioral Risk Factor Surveillance System (BRFSS) Survey and the New York City Community Health Survey (NYC CHS)) and to identify gaps in the current WICER RDW that have the potential to affect patient-centered CER.
We compared items across the three surveys at the item and conceptual levels. We also compared WICER RDW (ECD and WICER CHS), BRFSS, and NYC CHS to the County Health Ranking framework.
We found that 22 percent of WICER items were exact matches with BRFSS and that there were no exact matches between WICER CHS and NYC CHS items not also contained in BRFSS.
The results suggest that BRFSS and, to a lesser extent, NYC CHS have the potential to serve as population comparisons for WICER CHS for some health behavior-related data and thus may be particularly useful for considering the generalizability of CER study findings. Except for one measure related to health behavior (motor vehicle crash deaths), the WICER RDW's comprehensive coverage supports the mortality, morbidity, and clinical care measures specified in the County Health Ranking framework but is deficient in terms of some socioeconomic factors and descriptions of the physical environment as captured in BRFSS. Linkage of these data in the WICER RDW through geocoding can potentially facilitate patient-centered CER that integrates important socioeconomic and physical environment influences on health outcomes. The research methods and findings may be relevant to others interested in either integrating health behavior data into RDWs to support patient-centered CER or conducting population-level comparisons.
为解决电子健康数据碎片化这一比较效果研究(CER)的方法学局限,华盛顿高地茵伍德比较效果研究信息基础设施(WICER)项目正在创建一个以患者为中心的研究数据仓库(RDW),方法是将纽约长老会医院临床数据仓库中的电子临床数据(ECD)与门诊护理、长期护理和家庭健康环境中的ECD以及WICER社区健康调查(CHS)相链接。本研究的目的是确定WICER CHS与另外两项包含健康行为数据的调查(行为风险因素监测系统(BRFSS)调查和纽约市社区健康调查(NYC CHS))之间的重叠领域,并确定当前WICER RDW中可能影响以患者为中心的CER的差距。
我们在项目和概念层面比较了三项调查中的项目。我们还将WICER RDW(ECD和WICER CHS)、BRFSS和NYC CHS与县健康排名框架进行了比较。
我们发现,WICER项目中有22%的项目与BRFSS完全匹配,且WICER CHS与NYC CHS项目(BRFSS中未包含的项目)之间没有完全匹配项。
结果表明,BRFSS以及在较小程度上NYC CHS有可能作为WICER CHS在一些与健康行为相关数据方面的人群对照,因此对于考虑CER研究结果的可推广性可能特别有用。除了一项与健康行为相关的指标(机动车碰撞死亡)外,WICER RDW的全面覆盖支持了县健康排名框架中规定的死亡率、发病率和临床护理指标,但在一些社会经济因素以及BRFSS中所涵盖的物理环境描述方面存在不足。通过地理编码将这些数据在WICER RDW中进行链接,有可能促进以患者为中心的CER,该研究整合了重要的社会经济和物理环境对健康结果的影响。研究方法和结果可能与其他有兴趣将健康行为数据整合到RDW中以支持以患者为中心的CER或进行人群水平比较的人相关。