Building the Informatics Infrastructure for Comparative Effectiveness Research (CER) A Review of the Literature

被引:17
|
作者
Lopez, Marianne Hamilton [1 ]
Holve, Erin [1 ]
Sarkar, Indra Neil [2 ]
Segal, Courtney [1 ]
机构
[1] AcademyHlth, Washington, DC 20036 USA
[2] Univ Vermont, Ctr Clin & Translat Sci, Burlington, VT USA
基金
美国医疗保健研究与质量局;
关键词
comparative effectiveness research; clinical informatics; electronic clinical data; electronic health records; data sharing; ELECTRONIC MEDICAL-RECORDS; HEALTH-SERVICES RESEARCH; AUTOMATIC DE-IDENTIFICATION; CLINICAL-RESEARCH; TRANSLATIONAL RESEARCH; INTEGRATING BIOLOGY; QUALITY IMPROVEMENT; EXTRACTION SYSTEM; PUBLIC-HEALTH; SHARING DATA;
D O I
10.1097/MLR.0b013e318259becd
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
Background: Technological advances in clinical informatics have made large amounts of data accessible and potentially useful for research. As a result, a burgeoning literature addresses efforts to bridge the fields of health services research and biomedical informatics. The Electronic Data Methods Forum review examines peer-reviewed literature at the intersection of comparative effectiveness research and clinical informatics. The authors are specifically interested in characterizing this literature and identifying cross-cutting themes and gaps in the literature. Methods: A 3-step systematic literature search was conducted, including a structured search of PubMed, manual reviews of articles from selected publication lists, and manual reviews of research activities based on prospective electronic clinical data. Two thousand four hundred thirty-five citations were identified as potentially relevant. Ultimately, a full-text review was performed for 147 peer-reviewed papers. Results: One hundred thirty-two articles were selected for inclusion in the review. Of these, 88 articles are the focus of the discussion in this paper. Three types of articles were identified, including papers that: (1) provide historical context or frameworks for using clinical informatics for research, (2) describe platforms and projects, and (3) discuss issues, challenges, and applications of natural language processing. In addition, 2 cross-cutting themes emerged: the challenges of conducting research in the absence of standardized ontologies and data collection; and unique data governance concerns related to the transfer, storage, deidentification, and access to electronic clinical data. Finally, the authors identified several current gaps on important topics such as the use of clinical informatics for cohort identification, cloud computing, and single point access to research data.
引用
收藏
页码:S38 / S48
页数:11
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