Big science, big data, and a big role for biomedical informatics.
Author(s): Ohno-Machado, Lucila
DOI: 10.1136/amiajnl-2012-001052
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
The spread of case-control genome-wide association studies (GWASs) has stimulated the development of new variable selection methods and predictive models. We introduce a novel Bayesian model search algorithm, Binary Outcome Stochastic Search (BOSS), which addresses the model selection problem when the number of predictors far exceeds the number of binary responses.
Author(s): Russu, Alberto, Malovini, Alberto, Puca, Annibale A, Bellazzi, Riccardo
DOI: 10.1136/amiajnl-2011-000741
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
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
Competing tools are available online to assess the risk of developing certain conditions of interest, such as cardiovascular disease. While predictive models have been developed and validated on data from cohort studies, little attention has been paid to ensure the reliability of such predictions for individuals, which is critical for care decisions. The goal was to develop a patient-driven adaptive prediction technique to improve personalized risk estimation for clinical decision [...]
Author(s): Jiang, Xiaoqian, Boxwala, Aziz A, El-Kareh, Robert, Kim, Jihoon, Ohno-Machado, Lucila
DOI: 10.1136/amiajnl-2011-000751
OBJECTIVE: Clinical summarization, the process by which relevant patient information is electronically summarized and presented at the point of care, is of increasing importance given the increasing volume of clinical data in electronic health record systems (EHRs). There is a paucity of research on electronic clinical summarization, including the capabilities of currently available EHR systems. METHODS: We compared different aspects of general clinical summary screens used in twelve different EHR [...]
Author(s): Laxmisan, Archana, McCoy, Allison B, Wright, Adam, Sittig, Dean F
DOI: 10.4338/ACI-2011-11-RA-0066
Studies on the impact and value of health information technology (HIT) have often focused on outcome measures that are counts of such things as hospital admissions or the number of laboratory tests per patient. These measures with their highly skewed distributions (high frequency of 0s and 1s) are more appropriately analyzed with count data models than the much more frequently used variations of ordinary least squares (OLS). Use of a [...]
Author(s): Du, Jing, Park, Young-Taek, Theera-Ampornpunt, Nawanan, McCullough, Jeffrey S, Speedie, Stuart M
DOI: 10.1136/amiajnl-2011-000256