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PatientExploreR: an extensible application for dynamic visualization of patient clinical history from electronic health records in the OMOP common data model

MOTIVATION: Electronic health records (EHRs) are quickly becoming omnipresent in healthcare, but interoperability issues and technical demands limit their use for biomedical and clinical research. Interactive and flexible software that interfaces directly with EHR data structured around a common dat...

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Autores principales: Glicksberg, Benjamin S, Oskotsky, Boris, Thangaraj, Phyllis M, Giangreco, Nicholas, Badgeley, Marcus A, Johnson, Kipp W, Datta, Debajyoti, Rudrapatna, Vivek A, Rappoport, Nadav, Shervey, Mark M, Miotto, Riccardo, Goldstein, Theodore C, Rutenberg, Eugenia, Frazier, Remi, Lee, Nelson, Israni, Sharat, Larsen, Rick, Percha, Bethany, Li, Li, Dudley, Joel T, Tatonetti, Nicholas P, Butte, Atul J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6821222/
https://www.ncbi.nlm.nih.gov/pubmed/31214700
http://dx.doi.org/10.1093/bioinformatics/btz409
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author Glicksberg, Benjamin S
Oskotsky, Boris
Thangaraj, Phyllis M
Giangreco, Nicholas
Badgeley, Marcus A
Johnson, Kipp W
Datta, Debajyoti
Rudrapatna, Vivek A
Rappoport, Nadav
Shervey, Mark M
Miotto, Riccardo
Goldstein, Theodore C
Rutenberg, Eugenia
Frazier, Remi
Lee, Nelson
Israni, Sharat
Larsen, Rick
Percha, Bethany
Li, Li
Dudley, Joel T
Tatonetti, Nicholas P
Butte, Atul J
author_facet Glicksberg, Benjamin S
Oskotsky, Boris
Thangaraj, Phyllis M
Giangreco, Nicholas
Badgeley, Marcus A
Johnson, Kipp W
Datta, Debajyoti
Rudrapatna, Vivek A
Rappoport, Nadav
Shervey, Mark M
Miotto, Riccardo
Goldstein, Theodore C
Rutenberg, Eugenia
Frazier, Remi
Lee, Nelson
Israni, Sharat
Larsen, Rick
Percha, Bethany
Li, Li
Dudley, Joel T
Tatonetti, Nicholas P
Butte, Atul J
author_sort Glicksberg, Benjamin S
collection PubMed
description MOTIVATION: Electronic health records (EHRs) are quickly becoming omnipresent in healthcare, but interoperability issues and technical demands limit their use for biomedical and clinical research. Interactive and flexible software that interfaces directly with EHR data structured around a common data model (CDM) could accelerate more EHR-based research by making the data more accessible to researchers who lack computational expertise and/or domain knowledge. RESULTS: We present PatientExploreR, an extensible application built on the R/Shiny framework that interfaces with a relational database of EHR data in the Observational Medical Outcomes Partnership CDM format. PatientExploreR produces patient-level interactive and dynamic reports and facilitates visualization of clinical data without any programming required. It allows researchers to easily construct and export patient cohorts from the EHR for analysis with other software. This application could enable easier exploration of patient-level data for physicians and researchers. PatientExploreR can incorporate EHR data from any institution that employs the CDM for users with approved access. The software code is free and open source under the MIT license, enabling institutions to install and users to expand and modify the application for their own purposes. AVAILABILITY AND IMPLEMENTATION: PatientExploreR can be freely obtained from GitHub: https://github.com/BenGlicksberg/PatientExploreR. We provide instructions for how researchers with approved access to their institutional EHR can use this package. We also release an open sandbox server of synthesized patient data for users without EHR access to explore: http://patientexplorer.ucsf.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-68212222019-11-04 PatientExploreR: an extensible application for dynamic visualization of patient clinical history from electronic health records in the OMOP common data model Glicksberg, Benjamin S Oskotsky, Boris Thangaraj, Phyllis M Giangreco, Nicholas Badgeley, Marcus A Johnson, Kipp W Datta, Debajyoti Rudrapatna, Vivek A Rappoport, Nadav Shervey, Mark M Miotto, Riccardo Goldstein, Theodore C Rutenberg, Eugenia Frazier, Remi Lee, Nelson Israni, Sharat Larsen, Rick Percha, Bethany Li, Li Dudley, Joel T Tatonetti, Nicholas P Butte, Atul J Bioinformatics Applications Notes MOTIVATION: Electronic health records (EHRs) are quickly becoming omnipresent in healthcare, but interoperability issues and technical demands limit their use for biomedical and clinical research. Interactive and flexible software that interfaces directly with EHR data structured around a common data model (CDM) could accelerate more EHR-based research by making the data more accessible to researchers who lack computational expertise and/or domain knowledge. RESULTS: We present PatientExploreR, an extensible application built on the R/Shiny framework that interfaces with a relational database of EHR data in the Observational Medical Outcomes Partnership CDM format. PatientExploreR produces patient-level interactive and dynamic reports and facilitates visualization of clinical data without any programming required. It allows researchers to easily construct and export patient cohorts from the EHR for analysis with other software. This application could enable easier exploration of patient-level data for physicians and researchers. PatientExploreR can incorporate EHR data from any institution that employs the CDM for users with approved access. The software code is free and open source under the MIT license, enabling institutions to install and users to expand and modify the application for their own purposes. AVAILABILITY AND IMPLEMENTATION: PatientExploreR can be freely obtained from GitHub: https://github.com/BenGlicksberg/PatientExploreR. We provide instructions for how researchers with approved access to their institutional EHR can use this package. We also release an open sandbox server of synthesized patient data for users without EHR access to explore: http://patientexplorer.ucsf.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2019-11-01 2019-06-19 /pmc/articles/PMC6821222/ /pubmed/31214700 http://dx.doi.org/10.1093/bioinformatics/btz409 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Glicksberg, Benjamin S
Oskotsky, Boris
Thangaraj, Phyllis M
Giangreco, Nicholas
Badgeley, Marcus A
Johnson, Kipp W
Datta, Debajyoti
Rudrapatna, Vivek A
Rappoport, Nadav
Shervey, Mark M
Miotto, Riccardo
Goldstein, Theodore C
Rutenberg, Eugenia
Frazier, Remi
Lee, Nelson
Israni, Sharat
Larsen, Rick
Percha, Bethany
Li, Li
Dudley, Joel T
Tatonetti, Nicholas P
Butte, Atul J
PatientExploreR: an extensible application for dynamic visualization of patient clinical history from electronic health records in the OMOP common data model
title PatientExploreR: an extensible application for dynamic visualization of patient clinical history from electronic health records in the OMOP common data model
title_full PatientExploreR: an extensible application for dynamic visualization of patient clinical history from electronic health records in the OMOP common data model
title_fullStr PatientExploreR: an extensible application for dynamic visualization of patient clinical history from electronic health records in the OMOP common data model
title_full_unstemmed PatientExploreR: an extensible application for dynamic visualization of patient clinical history from electronic health records in the OMOP common data model
title_short PatientExploreR: an extensible application for dynamic visualization of patient clinical history from electronic health records in the OMOP common data model
title_sort patientexplorer: an extensible application for dynamic visualization of patient clinical history from electronic health records in the omop common data model
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6821222/
https://www.ncbi.nlm.nih.gov/pubmed/31214700
http://dx.doi.org/10.1093/bioinformatics/btz409
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