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Information Technology for Clinical, Translational and Comparative Effectiveness Research

C. Daniel, R. Choquet
2014 IMIA Yearbook of Medical Informatics  
The first paper tackles the challenge of extracting accurate phenotypes from Electronic Healthcare Records (EHRs).  ...  When EHRs linked to genetic data have the potential to shift the research focus from research driven patient recruitment to phenotyping in large population, a key issue is to lower patient re-identification  ...  A successful eMERGE project demonstrated that Electronic medical records (EMRs) hold large numbers of clinical phenotypes such as disease (cases) and nondisease (controls), and quantitative traits of medical  ... 
doi:10.15265/iy-2014-0040 pmid:25123747 pmcid:PMC4287061 fatcat:dgf5qqmvbfd5rfk6j3y2kjuvgm

Secondary use of clinical data: The Vanderbilt approach

Ioana Danciu, James D. Cowan, Melissa Basford, Xiaoming Wang, Alexander Saip, Susan Osgood, Jana Shirey-Rice, Jacqueline Kirby, Paul A. Harris
2014 Journal of Biomedical Informatics  
This work provides a summary of our approach in the secondary use of clinical data for research domain, including a description of key components and a list of lessons learned, designed to assist others  ...  The Vanderbilt research data warehouse framework consists of identified and de-identified clinical data repositories, fee-forservice custom services, and tools built atop the data layer to assist researchers  ...  Large-scale, integrated data repositories are foundational for work in many of these areas, resulting in a growing number of academic medical centers assembling big data programs to support the local research  ... 
doi:10.1016/j.jbi.2014.02.003 pmid:24534443 pmcid:PMC4133331 fatcat:y6i3uq4u3rdhhp5mp2fpq5fue4

The Role of Electronic Health Records in Advancing Genomic Medicine

Jodell E. Linder, Lisa Bastarache, Jacob J. Hughey, Josh F. Peterson
2021 Annual review of genomics and human genetics (Print)  
Genomic and phenomic data, accrued across large populations through biobanks linked to EHRs, have enabled the study of genetic variation at a phenome-wide scale.  ...  Recent advances in genomic technology and widespread adoption of electronic health records (EHRs) have accelerated the development of genomic medicine, bringing promising research findings from genome  ...  supported by grants U01 HG011166 and U01 HG010232 from the National Human Genome Research Institute and award UL1 TR002243 from the Clinical and Translational Science Awards program of the National Center for  ... 
doi:10.1146/annurev-genom-121120-125204 pmid:34038146 pmcid:PMC9297710 fatcat:lyr3r6nimrcptfvy3qown5vdkq

The Mass General Brigham Biobank Portal: an i2b2-based data repository linking disparate and high-dimensional patient data to support multimodal analytics

Victor M Castro, Vivian Gainer, Nich Wattanasin, Barbara Benoit, Andrew Cagan, Bhaswati Ghosh, Sergey Goryachev, Reeta Metta, Heekyong Park, David Wang, Michael Mendis, Martin Rees (+2 others)
2021 JAMIA Journal of the American Medical Informatics Association  
Twenty machine learning computed phenotypes are calculated on a weekly basis. There are currently 1220 active investigators who have run 58 793 patient queries and exported 10 257 analysis files.  ...  The data are made readily available to investigators in a data portal where they can easily construct and export customized datasets for analysis.  ...  The i2b2 data model is described as a metamodel in that it defines a database schema for storing large-scale health data with the patient as the single point of reference.  ... 
doi:10.1093/jamia/ocab264 pmid:34849976 pmcid:PMC8922162 fatcat:oprsltea35fr3lxa6a76u5skri

Patient-reported outcomes in a large community-based pain medicine practice: evaluation for use in phenotype modeling

David A. Juckett, Fred N. Davis, Mark Gostine, Philip Reed, Rebecca Risko
2015 BMC Medical Informatics and Decision Making  
An academic, community medicine partnership was established to build a phenotype-to-outcome model targeting chronic pain.  ...  This model will be used to drive clinical decision support for pain medicine in the community setting.  ...  .; and Eric Kasten and Bridget Messaros of MSU-BRIC for their consultations and assistance in this project.  ... 
doi:10.1186/s12911-015-0164-4 pmid:26017305 pmcid:PMC4446111 fatcat:kscvqho3mbdjrkpndsbh7nr3r4

Processing of Electronic Health Records using Deep Learning: A review [article]

Venet Osmani, Li Li, Matteo Danieletto, Benjamin Glicksberg, Joel Dudley, Oscar Mayora
2018 arXiv   pre-print
Except for availability of Big Data, both medical data from healthcare institutions (such as EMR data) and data generated from health and wellbeing devices (such as personal trackers), a significant contribution  ...  Availability of large amount of clinical data is opening up new research avenues in a number of fields.  ...  Recently, researchers developed a deep learning framework applied to a large-scale EMR database called Deep Patient [49] to construct predictive models for diseases across multiple domains, including  ... 
arXiv:1804.01758v1 fatcat:op5hsclwrvflxcbhfhidwmodyu

Using Ontologies to Identify Patients with Diabetes in Electronic Health Records

Hairong Yu, Siaw-Teng Liaw, Jane Taggart, Alireza Rahimi Khorzoughi
2013 International Semantic Web Conference  
Our study aims to improve the selection of diabetes patients for clinical trials or medical research.  ...  This paper describes a work in progress that explores the applicability of ontologies to solve problems in the medical domain.  ...  repository of the electronic Practice Based Research Network (ePBRN).  ... 
dblp:conf/semweb/YuLTK13 fatcat:3kazjxzi5baufc3cjvo2haovca

Challenges in Personalized Nutrition and Health

Meghna Verma, Raquel Hontecillas, Nuria Tubau-Juni, Vida Abedi, Josep Bassaganya-Riera
2018 Frontiers in Nutrition  
Thus, a unique comprehensive strategy that can automate data driven analytical model building, could be employed by focusing on the unique iterative integration of large-scale clinical record mining, -  ...  building a personalized nutrition computational infrastructure; the lack of standardization in format of the data utilized in electronic health records raises, (iii) the need for data standardization  ... 
doi:10.3389/fnut.2018.00117 pmid:30555829 pmcid:PMC6281760 fatcat:xd52ejz2rree3lb5fadd74dqcq

Information Technology for Clinical, Translational and Comparative Effectiveness Research

R. Choquet, C. Daniel
2013 IMIA Yearbook of Medical Informatics  
health care data for research are becoming a reality through concrete platforms and projects.  ...  were retained for peer-review.  ...  building and mining large scale in silico cohorts and next generation registries, iii) ethical issues related to privacy and potential return to participants.  ... 
doi:10.1055/s-0038-1638854 fatcat:py3mkovjivfuth4v3ts22ohj5m

The Promise of Big Data and Digital Solutions in Building a Cardiovascular Learning System: Opportunities and Barriers

Makoto Mori, Rohan Khera, Zhenqiu Lin, Joseph S Ross, Wade Schulz, Harlan M Krumholz
2020 Methodist DeBakey Cardiovascular Journal  
The learning health system is a conceptual model for continuous learning and knowledge generation rooted in the daily practice of medicine.  ...  While companies such as Google and Amazon use dynamic learning systems that learn iteratively through every customer interaction, this efficiency has not materialized on a comparable scale in health systems  ...  repository.  ... 
doi:10.14797/mdcj-16-3-212 pmid:33133357 pmcid:PMC7587314 fatcat:prtziucfd5fqdisv7sm5n3cove

EHR Big Data Deep Phenotyping

L. J. Frey, L. Lenert, G. Lopez-Campos
2014 IMIA Yearbook of Medical Informatics  
The growth of genomic data and adoption of Electronic Health Records (EHR) in medicine provides a unique opportunity to integrate phenotype and genotype data into medical records.  ...  The big data solution, using flexible markup, provides a route to improved utilization of processing power for organizing patient records in genotype and phenotype research.  ...  The Unified Medical Language System (UMLS) [12] provides a repository of vocabularies with which to consistently markup medical records.  ... 
doi:10.15265/iy-2014-0006 pmid:25123744 pmcid:PMC4287080 fatcat:oadqazqyqvbd5fv7acuw3vzgxq

Building a Biomedical Cyberinfrastructure for Collaborative Research

Peter A. Schad, Lee Rivers Mobley, Carol M. Hamilton
2011 American Journal of Preventive Medicine  
National Institutes of Health support for these efforts has produced the PhenX Toolkit, an assembled catalog of standard measures for use in GWAS and other large-scale genomic research efforts, and the  ...  RTI Spatial Impact Factor Database (SIFD), a comprehensive repository of georeferenced variables and extensive metadata that conforms to OGC standards.  ...  Conceptual cyberinfrastructure Notes: EMRs = electronic medical records; GWAS = genome-wide association studies. Figure 1 . 1 Figure 1.  ... 
doi:10.1016/j.amepre.2011.01.018 pmid:21521587 pmcid:PMC5817638 fatcat:dudio5hulnhv7cbfo34sbmwlse

A Review of Automatic Phenotyping Approaches using Electronic Health Records

Hadeel Alzoubi, Raid Alzubi, Naeem Ramzan, Daune West, Tawfik Al-Hadhrami, Mamoun Alazab
2019 Electronics  
In order to utilize EHRs for medical observational research a range of algorithms for automatically identifying individuals with a specific phenotype have been developed.  ...  Electronic Health Records (EHR) are a rich repository of valuable clinical information that exist in primary and secondary care databases.  ...  Introduction Electronic health records (EHR) are a rich repository of valuable clinical information that exist in primary and secondary care databases [1] .  ... 
doi:10.3390/electronics8111235 fatcat:6wygemixhvgoxkhjqrmmjs3ynq

The biorepository portal toolkit: an honest brokered, modular service oriented software tool set for biospecimen-driven translational research

Alex S. Felmeister, Aaron J. Masino, Tyler J. Rivera, Adam C. Resnick, Jeffrey W. Pennington
2016 BMC Genomics  
We specifically set out to build rich annotation of biospecimens with longitudinal clinical data; BRP/REDCap integration for multi-institutional repositories; EMR integration; further annotated specimens  ...  with genomic data specific to a domain; build application hooks for experiments at the specimen level integrated with analytic software; while protecting privacy per the Office of Civil Rights (OCR) and  ...  EMR integration Integrating or retrieving data from the Electronic Medical Record (EMR) is a growing need for users of the toolkit.  ... 
doi:10.1186/s12864-016-2797-9 pmid:27535360 pmcid:PMC5001241 fatcat:z67lq4lqxzhzdi5yma2htkmxl4

The Electronic Medical Records and Genomics (eMERGE) Network: past, present and future

Omri Gottesman, Helena Kuivaniemi, Gerard Tromp, W. Andrew Faucett, Rongling Li, Teri A. Manolio, Saskia C. Sanderson, Joseph Kannry, Randi Zinberg, Melissa A. Basford, Murray Brilliant, David J. Carey (+19 others)
2013 Genetics in Medicine  
the development of methods and best practices for using the electronic medical record as a tool for genomic research.  ...  electronic medical records can be used successfully for genomic research.  ...  ACKNOWLEDGMENTS The eMERGE Network is funded by the NHGRI, with additional funding from the National Institute of General Medical Sciences through the following grants: U01HG004438 to Johns Hopkins  ... 
doi:10.1038/gim.2013.72 pmid:23743551 pmcid:PMC3795928 fatcat:onqmiqi3trcxjga45pncvquts4
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