A Survey of Informatics Platforms That Enable Distributed Comparative Effectiveness Research Using Multi-institutional Heterogenous Clinical Data

被引:22
|
作者
Sittig, Dean F. [1 ]
Hazlehurst, Brian L. [2 ]
Brown, Jeffrey [3 ]
Murphy, Shawn [4 ]
Rosenman, Marc [5 ,6 ]
Tarczy-Hornoch, Peter [7 ]
Wilcox, Adam B. [8 ]
机构
[1] Univ Texas Hlth Sci Ctr, Sch Biomed Informat, Houston, TX USA
[2] Kaiser Permanente Ctr Hlth Res, Portland, OR USA
[3] Harvard Pilgrim Hlth Care Inst, Dept Populat Med, Boston, MA USA
[4] Harvard Univ, Sch Med, Boston, MA USA
[5] Regenstrief Inst Hlth Care, Indianapolis, IN 46202 USA
[6] Indiana Univ Sch Med, Indianapolis, IN USA
[7] Univ Washington, Div Biomed & Hlth Informat, Seattle, WA 98195 USA
[8] Columbia Univ, Dept Biomed Informat, New York, NY 10027 USA
基金
美国医疗保健研究与质量局;
关键词
methods; comparative effectiveness research; organization and administration; medical informatics; HEALTH DATA-NETWORKS; MEDICAL-RECORD; PATIENT-CARE; DESIGN; SYSTEM; MODEL;
D O I
10.1097/MLR.0b013e318259c02b
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Comparative effectiveness research (CER) has the potential to transform the current health care delivery system by identifying the most effective medical and surgical treatments, diagnostic tests, disease prevention methods, and ways to deliver care for specific clinical conditions. To be successful, such research requires the identification, capture, aggregation, integration, and analysis of disparate data sources held by different institutions with diverse representations of the relevant clinical events. In an effort to address these diverse demands, there have been multiple new designs and implementations of informatics platforms that provide access to electronic clinical data and the governance infrastructure required for interinstitutional CER. The goal of this manuscript is to help investigators understand why these informatics platforms are required and to compare and contrast 6 large-scale, recently funded, CER-focused informatics platform development efforts. We utilized an 8-dimension, sociotechnical model of health information technology to help guide our work. We identified 6 generic steps that are necessary in any distributed, multi-institutional CER project: data identification, extraction, modeling, aggregation, analysis, and dissemination. We expect that over the next several years these projects will provide answers to many important, and heretofore unanswerable, clinical research questions.
引用
收藏
页码:S49 / S59
页数:11
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