Abstract：
:The Research Electronic Data Capture (REDCap) data management platform was developed in 2004 to address an institutional need at Vanderbilt University, then shared with a limited number of adopting sites beginning in 2006. Given bi-directional benefit in early sharing experiments, we created a broader consortium sharing and support model for any academic, non-profit, or government partner wishing to adopt the software. Our sharing framework and consortium-based support model have evolved over time along with the size of the consortium (currently more than 3200 REDCap partners across 128 countries). While the "REDCap Consortium" model represents only one example of how to build and disseminate a software platform, lessons learned from our approach may assist other research institutions seeking to build and disseminate innovative technologies.
journal_name
J Biomed Informjournal_title
Journal of biomedical informaticsauthors
Harris PA,Taylor R,Minor BL,Elliott V,Fernandez M,O'Neal L,McLeod L,Delacqua G,Delacqua F,Kirby J,Duda SN,REDCap Consortium.doi
10.1016/j.jbi.2019.103208subject
Has Abstractpub_date
2019-07-01 00:00:00pages
103208eissn
1532-0464issn
1532-0480pii
S1532-0464(19)30126-1journal_volume
95pub_type
杂志文章abstract：:The term registry is widely used to refer to any database storing clinical information collected as a byproduct of patient care. Despite the use of this single characterizing term (registry), these databases exist in various forms and support functions ranging from biomedical informatics and clinical research, to publ...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2008.01.009
更新日期：2008-12-01 00:00:00
abstract：:To extract biomedical information about bio-entities from the huge amount of biomedical literature, the first key step is recognizing their names in these literatures, which remains a challenging task due to the irregularities and ambiguities in bio-entities nomenclature. The recognition performances of the current po...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2008.01.002
更新日期：2008-08-01 00:00:00
abstract：:As a result of recent advances in cancer research and "precision medicine" approaches, i.e. the idea of treating each patient with the right drug at the right time, more and more cancer patients are being cured, or might have to cope with a life with cancer. For many people, cancer survival today means living with a c...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2019.103342
更新日期：2020-01-01 00:00:00
abstract：:Medical error is a leading cause of patient death in the United States. Among the different types of medical errors, harm to patients caused by doctors missing early signs of deterioration is especially challenging to address due to the heterogeneity of patients' physiological patterns. In this study, we implemented r...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2020.103425
更新日期：2020-07-01 00:00:00
abstract：:Quantitative gait analysis allows clinicians to assess the inherent gait variability over time which is a functional marker to aid in the diagnosis of disabilities or diseases such as frailty, the onset of cognitive decline and neurodegenerative diseases, among others. However, despite the accuracy achieved by the cur...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2016.07.009
更新日期：2016-08-01 00:00:00
abstract：:The major challenge in influenza vaccination is to predict vaccine efficacy. The purpose of this study was to design a model to enable successful prediction of the outcome of influenza vaccination based on real historical medical data. A non-linear neural network approach was used, and its performance compared to logi...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2010.04.011
更新日期：2010-10-01 00:00:00
abstract：:Rare diseases are often hard and long to be diagnosed precisely, and most of them lack approved treatment. For some complex rare diseases, precision medicine approach is further required to stratify patients into homogeneous subgroups based on the clinical, biological or molecular features. In such situation, deep phe...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2019.103308
更新日期：2019-12-01 00:00:00
abstract：OBJECTIVE:To develop an effective and scalable individual-level patient cost prediction method by automatically learning hidden temporal patterns from multivariate time series data in patient insurance claims using a convolutional neural network (CNN) architecture. METHODS:We used three years of medical and pharmacy c...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2020.103565
更新日期：2020-11-01 00:00:00
abstract：:Data analytics is routinely used to support biomedical research in all areas, with particular focus on the most relevant clinical conditions, such as cancer. Bioinformatics approaches, in particular, have been used to characterize the molecular aspects of diseases. In recent years, numerous studies have been performed...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章,评审
doi：10.1016/j.jbi.2020.103466
更新日期：2020-07-01 00:00:00
abstract：BACKGROUND:Identifying key variables such as disorders within the clinical narratives in electronic health records has wide-ranging applications within clinical practice and biomedical research. Previous research has demonstrated reduced performance of disorder named entity recognition (NER) and normalization (or groun...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2015.07.010
更新日期：2015-10-01 00:00:00
abstract：:The 2014 i2b2/UTHealth natural language processing shared task featured a track focused on the de-identification of longitudinal medical records. For this track, we de-identified a set of 1304 longitudinal medical records describing 296 patients. This corpus was de-identified under a broad interpretation of the HIPAA ...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2015.07.020
更新日期：2015-12-01 00:00:00
abstract：:The explosive growth of biomedical literature has created a rich source of knowledge, such as that on protein-protein interactions (PPIs) and drug-drug interactions (DDIs), locked in unstructured free text. Biomedical relation classification aims to automatically detect and classify biomedical relations, which has gre...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章,评审
doi：10.1016/j.jbi.2019.103294
更新日期：2019-11-01 00:00:00
abstract：:Identification of co-referent entity mentions inside text has significant importance for other natural language processing (NLP) tasks (e.g. event linking). However, this task, known as co-reference resolution, remains a complex problem, partly because of the confusion over different evaluation metrics and partly beca...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2013.03.007
更新日期：2013-06-01 00:00:00
abstract：:Cancer surveillance data are collected every year in the United States via the National Program of Cancer Registries (NPCR) and the Surveillance, Epidemiology and End Results (SEER) Program of the National Cancer Institute (NCI). General trends are closely monitored to measure the nation's progress against cancer. The...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2016.03.027
更新日期：2016-06-01 00:00:00
abstract：:One of the main reasons that leads to a low adoption rate of telemedicine systems is poor usability. An aspect that influences usability during the reporting of findings is the input mode, e.g., if a free-text (FT) or a structured report (SR) interface is employed. The objective of our study is to compare the usabilit...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2014.07.002
更新日期：2014-12-01 00:00:00
abstract：OBJECTIVE:Evaluate the quality of clinical order practice patterns machine-learned from clinician cohorts stratified by patient mortality outcomes. MATERIALS AND METHODS:Inpatient electronic health records from 2010 to 2013 were extracted from a tertiary academic hospital. Clinicians (n = 1822) were stratified into lo...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2018.09.005
更新日期：2018-10-01 00:00:00
abstract：OBJECTIVE:We have developed an automated knowledge base peer feedback system as part of an effort to facilitate the creation and refinement of sound clinical knowledge content within an enterprise-wide knowledge base. The program collects clinical data stored in our Clinical Data Repository during usage of a physician ...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2007.05.006
更新日期：2008-02-01 00:00:00
abstract：:The threat of bioterrorism has stimulated interest in enhancing public health surveillance to detect disease outbreaks more rapidly than is currently possible. To advance research on improving the timeliness of outbreak detection, the Defense Advanced Research Project Agency sponsored the Bio-event Advanced Leading In...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2004.11.007
更新日期：2005-04-01 00:00:00
abstract：:Many interventions to improve the success of information technology (IT) implementations are grounded in behavioral science, using theories, and models to identify conditions and determinants of successful use. However, each model in the IT literature has evolved to address specific theoretical problems of particular ...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章,评审
doi：10.1016/j.jbi.2003.09.002
更新日期：2003-06-01 00:00:00
abstract：:In this paper, a Hidden Semi-Markov Model (HSMM) based approach is proposed to evaluate and monitor body motion during a rehabilitation training program. The approach extracts clinically relevant motion features from skeleton joint trajectories, acquired by the RGB-D camera, and provides a score for the subject's perf...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2017.12.012
更新日期：2018-02-01 00:00:00
abstract：BACKGROUND:The majority of current medical CBIR systems perform retrieval based only on "imaging signatures" generated by extracting pixel-level quantitative features, and only rarely has a feedback mechanism been incorporated to improve retrieval performance. In addition, current medical CBIR approaches do not routine...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2018.07.002
更新日期：2018-08-01 00:00:00
abstract：:An open research question when leveraging ontological knowledge is when to treat different concepts separately from each other and when to aggregate them. For instance, concepts for the terms "paroxysmal cough" and "nocturnal cough" might be aggregated in a kidney disease study, but should be left separate in a pneumo...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2012.01.002
更新日期：2012-06-01 00:00:00
abstract：:Three-dimensional (3D) visualization of preoperative and intraoperative medical information becomes more and more important in minimally invasive surgery. We develop a 3D interactive surgical visualization system using mobile spatial information acquisition and autostereoscopic display for surgeons to observe surgical...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2017.05.014
更新日期：2017-07-01 00:00:00
abstract：UNLABELLED:Responding to public health emergencies requires rapid and accurate assessment of workforce availability under adverse and changing circumstances. However, public health information systems to support resource management during both routine and emergency operations are currently lacking. We applied scenario-...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2011.07.004
更新日期：2011-12-01 00:00:00
abstract：:Drug therapeutic indications and side-effects are both measurable patient phenotype changes in response to the treatment. Inferring potential drug therapeutic indications and identifying clinically interesting drug side-effects are both important and challenging tasks. Previous studies have utilized either chemical st...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2014.03.014
更新日期：2014-10-01 00:00:00
abstract：OBJECTIVE:To classify and characterize the variables commonly used to measure the impact of Information Technology (IT) adoption in health care, as well as settings and IT interventions tested, and to guide future research. MATERIALS AND METHODS:We conducted a descriptive study screening a sample of 236 studies from a...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2016.07.018
更新日期：2016-10-01 00:00:00
abstract：:In Electronic Health Records (EHRs), much of valuable information regarding patients' conditions is embedded in free text format. Natural language processing (NLP) techniques have been developed to extract clinical information from free text. One challenge faced in clinical NLP is that the meaning of clinical entities...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2015.02.010
更新日期：2015-04-01 00:00:00
abstract：:Named entity recognition is an extremely important and fundamental task of biomedical text mining. Biomedical named entities include mentions of proteins, genes, DNA, RNA, etc which often have complex structures, but it is challenging to identify and classify such entities. Machine learning methods like CRF, MEMM and ...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2008.12.012
更新日期：2009-10-01 00:00:00
abstract：:With rapid adoption of Electronic Health Records (EHR) in China, an increasing amount of clinical data has been available to support clinical research. Clinical data secondary use usually requires de-identification of personal information to protect patient privacy. Since manually de-identification of free clinical te...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2017.07.017
更新日期：2017-09-01 00:00:00
abstract：:Modern biomedical research relies on the semantic integration of heterogeneous data sources to find data correlations. Researchers access multiple datasets of disparate origin, and identify elements-e.g. genes, compounds, pathways-that lead to interesting correlations. Normally, they must refer to additional public da...
journal_title：Journal of biomedical informatics
pub_type： 杂志文章
doi：10.1016/j.jbi.2016.02.004
更新日期：2016-04-01 00:00:00
