The coming age of data-driven medicine: translational bioinformatics' next frontier.
Author(s): Shah, Nigam H, Tenenbaum, Jessica D
DOI: 10.1136/amiajnl-2012-000969
Author(s): Shah, Nigam H, Tenenbaum, Jessica D
DOI: 10.1136/amiajnl-2012-000969
Author(s): Ohno-Machado, Lucila
DOI: 10.1136/amiajnl-2012-001052
Inadequate participant recruitment is a major problem facing clinical research. Recent studies have demonstrated that electronic health record (EHR)-based, point-of-care, clinical trial alerts (CTA) can improve participant recruitment to certain clinical research studies. Despite their promise, much remains to be learned about the use of CTAs. Our objective was to study whether repeated exposure to such alerts leads to declining user responsiveness and to characterize its extent if present to [...]
Author(s): Embi, Peter J, Leonard, Anthony C
DOI: 10.1136/amiajnl-2011-000743
To characterise empirical instances of Unified Medical Language System (UMLS) Metathesaurus term strings in a large clinical corpus, and to illustrate what types of term characteristics are generalisable across data sources.
Author(s): Wu, Stephen T, Liu, Hongfang, Li, Dingcheng, Tao, Cui, Musen, Mark A, Chute, Christopher G, Shah, Nigam H
DOI: 10.1136/amiajnl-2011-000744
Quality control and harmonization of data is a vital and challenging undertaking for any successful data coordination center and a responsibility shared between the multiple sites that produce, integrate, and utilize the data. Here we describe a coordinated effort between scientists and data managers in the Cancer Family Registries to implement a data governance infrastructure consisting of both organizational and technical solutions. The technical solution uses a rule-based validation system [...]
Author(s): McGarvey, Peter B, Ladwa, Sweta, Oberti, Mauricio, Dragomir, Anca Dana, Hedlund, Erin K, Tanenbaum, David Michael, Suzek, Baris E, Madhavan, Subha
DOI: 10.1136/amiajnl-2011-000546
To address the challenge of balancing privacy with the need to create cross-site research registry records on individual patients, while matching the data for a given patient as he or she moves between participating sites. To evaluate the strategy of generating anonymous identifiers based on real identifiers in such a way that the chances of a shared patient being accurately identified were maximized, and the chances of incorrectly joining two [...]
Author(s): Weber, Susan C, Lowe, Henry, Das, Amar, Ferris, Todd
DOI: 10.1136/amiajnl-2011-000329
National organizations historically focused on increasing use of effective services are now attempting to identify and discourage use of low-value services. Electronic health records (EHRs) could be used to measure use of low-value services, but few studies have examined this. The aim of the study was to: (1) determine if EHR data can be used to identify women eligible for an extended Pap testing interval; (2) determine the proportion of [...]
Author(s): Mathias, Jason S, Gossett, Dana, Baker, David W
DOI: 10.1136/amiajnl-2011-000536
Clinical research informatics is the rapidly evolving sub-discipline within biomedical informatics that focuses on developing new informatics theories, tools, and solutions to accelerate the full translational continuum: basic research to clinical trials (T1), clinical trials to academic health center practice (T2), diffusion and implementation to community practice (T3), and 'real world' outcomes (T4). We present a conceptual model based on an informatics-enabled clinical research workflow, integration across heterogeneous data sources [...]
Author(s): Kahn, Michael G, Weng, Chunhua
DOI: 10.1136/amiajnl-2012-000968
The objective of this study is to develop an approach to evaluate the quality of terminological annotations on the value set (ie, enumerated value domain) components of the common data elements (CDEs) in the context of clinical research using both unified medical language system (UMLS) semantic types and groups.
Author(s): Jiang, Guoqian, Solbrig, Harold R, Chute, Christopher G
DOI: 10.1136/amiajnl-2011-000739
Profiling the allocation and trend of research activity is of interest to funding agencies, administrators, and researchers. However, the lack of a common classification system hinders the comprehensive and systematic profiling of research activities. This study introduces ontology-based annotation as a method to overcome this difficulty. Analyzing over a decade of funding data and publication data, the trends of disease research are profiled across topics, across institutions, and over time.
Author(s): Liu, Yi, Coulet, Adrien, LePendu, Paea, Shah, Nigam H
DOI: 10.1136/amiajnl-2011-000631