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Information Technology for Clinical, Translational and Comparative Effectiveness Research

C. Daniel, R. Choquet
2014 IMIA Yearbook of Medical Informatics  
Two other papers exemplify the growing role of formal representation of clinical data -in metadata repositories -and knowledge -in ontologies -for supporting the process of reusing data for clinical research  ...  The first paper tackles the challenge of extracting accurate phenotypes from Electronic Healthcare Records (EHRs).  ...  Acknowledgement We would like to acknowledge the support of Martina Hutter and the reviewers in the selection process of the IMIA Yearbook.  ... 
doi:10.15265/iy-2014-0040 pmid:25123747 pmcid:PMC4287061 fatcat:dgf5qqmvbfd5rfk6j3y2kjuvgm

Developing a data element repository to support EHR-driven phenotype algorithm authoring and execution

Guoqian Jiang, Richard C. Kiefer, Luke V. Rasmussen, Harold R. Solbrig, Huan Mo, Jennifer A. Pacheco, Jie Xu, Enid Montague, William K. Thompson, Joshua C. Denny, Christopher G. Chute, Jyotishman Pathak
2016 Journal of Biomedical Informatics  
In conjunction with the HL7 Health Quality Measures Format (HQMF), QDM contains core elements that make it a promising model for representing EHR-driven phenotype algorithms for clinical research.  ...  The objective of the present study is to develop and evaluate a data element repository (DER) for providing machine-readable QDM data element service APIs to support phenotype algorithm authoring and execution  ...  Acknowledgments The manuscript is an expanded version of a podium abstract presented in the AMIA Clinical Research Informatics (CRI) 2015 conference.  ... 
doi:10.1016/j.jbi.2016.07.008 pmid:27392645 pmcid:PMC5490836 fatcat:xuk6zqpgfjfkbmadicpiryecky

Mining the ultimate phenome repository

Nigam H Shah
2013 Nature Biotechnology  
And because it can make use of information buried in electronic medical records, it offers a strategy for mining data generated in routine clinical practice.  ...  Combining genotyping and the data locked in medical records yields a large number of known genotype-phenotype associations.  ...  One important application of electronic medical record data is for genetics research, as in the PheWAS of Denny et al. 2 .  ... 
doi:10.1038/nbt.2757 pmid:24316646 pmcid:PMC4036679 fatcat:sptsn7kv6vg47bbpssfcvgqj24

PheKB: a catalog and workflow for creating electronic phenotype algorithms for transportability

Jacqueline C Kirby, Peter Speltz, Luke V Rasmussen, Melissa Basford, Omri Gottesman, Peggy L Peissig, Jennifer A Pacheco, Gerard Tromp, Jyotishman Pathak, David S Carrell, Stephen B Ellis, Todd Lingren (+6 others)
2016 JAMIA Journal of the American Medical Informatics Association  
Conclusion By providing a central repository, PheKB enables improved development, transportability, and validity of algorithms for research-grade phenotypes using health care generated data.  ...  Objective Health care generated data have become an important source for clinical and genomic research.  ...  ACKNOWLEDGEMENTS We gratefully acknowledge Stephanie Pretel (NIH/NLM/NCBI) for assistance and discussion for the development of the Data Dictionary/Data Validation.  ... 
doi:10.1093/jamia/ocv202 pmid:27026615 pmcid:PMC5070514 fatcat:g6dacrtw45elvj53vk7aztddh4

Desiderata for the development of next-generation electronic health record phenotype libraries

Martin Chapman, Shahzad Mumtaz, Luke V Rasmussen, Andreas Karwath, Georgios V Gkoutos, Chuang Gao, Dan Thayer, Jennifer A Pacheco, Helen Parkinson, Rachel L Richesson, Emily Jefferson, Spiros Denaxas (+1 others)
2021 GigaScience  
The provision of high-quality phenotype definitions enables electronic health record data to be more effectively used in medical domains.  ...  Methods A group of researchers examined work to date on phenotype models, implementation, and validation, as well as contemporary phenotype libraries developed as a part of their own phenomics communities  ...  Acknowledgements The authors wish to acknowledge the involvement of Dr. Susheel Varma (HDR UK) and Dr. Elliot Fairweather (King's College London) in the development of this work.  ... 
doi:10.1093/gigascience/giab059 pmid:34508578 pmcid:PMC8434766 fatcat:2c7cdzpygfbynldtkqhqqapkgu

The Mouse Genome Database: integration of and access to knowledge about the laboratory mouse

Judith A. Blake, Carol J. Bult, Janan T. Eppig, James A. Kadin, Joel E. Richardson
2013 Nucleic Acids Research  
vertebrate genomes and new loads of phenotype data from high-throughput phenotyping projects.  ...  MGD curates and maintains the comprehensive listing of functional annotations for mouse genes using the Gene Ontology, and MGD curates and integrates comprehensive phenotype annotations including associations  ...  MGD also supports electronic data contributions directly from individual researchers. Any type of data that MGD maintains can be submitted as an electronic contribution.  ... 
doi:10.1093/nar/gkt1225 pmid:24285300 pmcid:PMC3964950 fatcat:iszlulio2zaw3kc7qmd3t22jmy

Considerations for Improving the Portability of Electronic Health Record-Based Phenotype Algorithms

Luke V Rasmussen, Pascal S Brandt, Guoqian Jiang, Richard C Kiefer, Jennifer A Pacheco, Prakash Adekkanattu, Jessica S Ancker, Fei Wang, Zhenxing Xu, Jyotishman Pathak, Yuan Luo
2020 AMIA Annual Symposium Proceedings  
With the increased adoption of electronic health records, data collected for routine clinical care is used for health outcomes and population sciences research, including the identification of phenotypes  ...  These include using a common data model, standardized representation of the phenotype algorithm logic, and technical solutions to facilitate federated execution of queries.  ...  The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.  ... 
pmid:32308871 pmcid:PMC7153055 fatcat:zltyrmxh6vbbzcswutxwibd2cq

The Effectiveness of Transfer Learning in Electronic Health Records Data

Sébastien Dubois, Nathanael Romano, Kenneth Jung, Nigam Shah, David C. Kale
2017 International Conference on Learning Representations  
The application of machine learning to clinical data from Electronic Health Records is limited by the scarcity of meaningful labels.  ...  We explore the transfer of knowledge from source tasks in which training labels are plentiful but of limited clinical value to more meaningful target tasks that have few labels.  ...  DATA AND TASK SETUP We extracted patient data spanning 2009 through 2014 from the Stanford Translational Research Integrated Database Environment (STRIDE) (Lowe et al., 2009) , a repository of de-identified  ... 
dblp:conf/iclr/DuboisRJSK17 fatcat:73r3cwfnwfgbzncommwbc62oem

Feasibility of Using EN 13606 Clinical Archetypes for Defining Computable Phenotypes

Archana Tapuria, Dipak Kalra, Vasa Curcin
2020 Studies in Health Technology and Informatics  
Computable phenotypes are gaining importance as structured and reproducible method of using electronic health data to identify people with certain clinical conditions.  ...  These archetypes can be mapped for comparison with the openEHR models. Binding to external clinical terminology is fully supported.  ...  Acknowledgement: This research is supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at Guy's and St Thomas' NHS Foundation Trust and King's College London.  ... 
doi:10.3233/shti200156 pmid:32570380 fatcat:64ej3d3xcnfrjikby7xyj3apaq

Electronic health records based phenotyping in next-generation clinical trials: a perspective from the NIH Health Care Systems Collaboratory: Table 1

Rachel L Richesson, W Ed Hammond, Meredith Nahm, Douglas Wixted, Gregory E Simon, Jennifer G Robinson, Alan E Bauck, Denise Cifelli, Michelle M Smerek, John Dickerson, Reesa L Laws, Rosemary A Madigan (+3 others)
2013 JAMIA Journal of the American Medical Informatics Association  
, and methods for validating both the definition and execution of electronic health records based phenotypes.  ...  Widespread sharing of data from electronic health records and patient-reported outcomes can strengthen the national capacity for conducting cost-effective clinical trials and allow research to be embedded  ...  The Strategic Health IT Advanced Research Projects' Secondary Use of Electronic Medical Record Data (SHARPn) Box 1 Use cases for electronic health record (EHR)-based phenotyping in the NIH Collaboratory  ... 
doi:10.1136/amiajnl-2013-001926 pmid:23956018 pmcid:PMC3861929 fatcat:r2xylr5devcorjb42uealbrqwu

B1MG D3.7 - Documented best practices in sharing and linking phenotypic and genetic data - 1v0

Jeroen Belien, Catia Pinto, Maarten Ligtvoet, Milena Urbini, Pim Volkert, Wei Gu, Michela Tebaldi, Attila Patocs, K.Joeri van der Velde, Marielle E van Gijn, Jan O Korbel, Antonella Padella (+5 others)
2021 Zenodo  
This is the first version of documented best practices in sharing and linking phenotypic and genetic data.  ...  It identifies and describes best practices on sharing and linking phenotypic and genetic data in both the healthcare sector and in the research setting.  ...  /consortium/library/search.php 79 Summary: Research Electronic Data Capture The REDCap Shared Library is a repository for REDCap data collection instruments and forms that can be downloaded and used by  ... 
doi:10.5281/zenodo.5018520 fatcat:5riuzciexnbypgdvmeumdxvyim

Integrating electronic health record information to support integrated care: Practical application of ontologies to improve the accuracy of diabetes disease registers

Siaw-Teng Liaw, Jane Taggart, Hairong Yu, Simon de Lusignan, Craig Kuziemsky, Andrew Hayen
2014 Journal of Biomedical Informatics  
Background: Information in Electronic Health Records (EHRs) are being promoted for use in clinical decision support, patient registers, measurement and improvement of integration and quality of care, and  ...  This clinical and pragmatic application of ontologies to EHR data improves the integration of data and the potential for better use of data to improve the quality of care.  ...  In comparison, the prevalence of the T2DM reported using RFV alone was only 5.8%.  ... 
doi:10.1016/j.jbi.2014.07.016 pmid:25089026 fatcat:p7r5rr4ykfeuppkh5rxw4itvam

The Mammalian Phenotype Ontology as a unifying standard for experimental and high-throughput phenotyping data

Cynthia L. Smith, Janan T. Eppig
2012 Mammalian Genome  
Using the ontology structure, data are retrieved inclusively, i.e., data annotated to chosen terms and to terms subordinate in the hierarchy.  ...  The Mammalian Phenotype Ontology (MP) is a structured vocabulary for describing mammalian phenotypes and serves as a critical tool for efficient annotation and comprehensive retrieval of phenotype data  ...  Babiuk for helpful comments on the manuscript. This work was funded by the National Institutes of Health, National Human Genome Research Institute (NHGRI) Grant HG000330.  ... 
doi:10.1007/s00335-012-9421-3 pmid:22961259 pmcid:PMC3463787 fatcat:ygcz5rtafnbo7a7exo764r5vsu

Sample and data sharing: Observations from a central data repository

Mary-Anne Ardini, Huaqin Pan, Ying Qin, Philip C. Cooley
2014 Clinical Biochemistry  
From 2003 to 2013, RTI International served as the data repository for the National Institute of Diabetes, Digestive and Kidney Diseases (NIDDK).  ...  In this paper, we recap aspects of establishing the mechanism; detail the challenges and limitations of data and sample sharing, and explore the future of resource sharing in light of the evolving environment  ...  Acknowledgments This work was supported by National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), Bethesda, MD 29892, USA, contract number HHSN267200800016C  ... 
doi:10.1016/j.clinbiochem.2013.11.014 pmid:24291049 pmcid:PMC3959283 fatcat:i27owxxuyjavralre5u7mqxoaq

Learning Contextual Hierarchical Structure of Medical Concepts with Poincairé Embeddings to Clarify Phenotypes

Brett K. Beaulieu-Jones, Isaac S. Kohane, Andrew L. Beam
2018 Biocomputing 2019  
Biomedical association studies are increasingly done using clinical concepts, and in particular diagnostic codes from clinical data repositories as phenotypes.  ...  These embeddings allow for comparison between clinical concepts or for straightforward input to machine learning models.  ...  [20] [21] [22] Increases in genetic testing and the availability of clinical data repositories (Electronic Health Record, Administrative Claims, large-scale Cohort) have enabled PheWAS association studies  ... 
doi:10.1142/9789813279827_0002 fatcat:2sozobsxrvf4jdlbpunmn7o7vy
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