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ROMOP: a light-weight R package for interfacing with OMOP-formatted electronic health record data
OBJECTIVES: Electronic health record (EHR) data are increasingly used for biomedical discoveries. The nature of the data, however, requires expertise in both data science and EHR structure. The Observational Medical Outcomes Partnership (OMOP) common data model (CDM) standardizes the language and st...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6800657/ https://www.ncbi.nlm.nih.gov/pubmed/31633087 http://dx.doi.org/10.1093/jamiaopen/ooy059 |
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author | Glicksberg, Benjamin S Oskotsky, Boris Giangreco, Nicholas Thangaraj, Phyllis M Rudrapatna, Vivek Datta, Debajyoti Frazier, Remi Lee, Nelson Larsen, Rick Tatonetti, Nicholas P Butte, Atul J |
author_facet | Glicksberg, Benjamin S Oskotsky, Boris Giangreco, Nicholas Thangaraj, Phyllis M Rudrapatna, Vivek Datta, Debajyoti Frazier, Remi Lee, Nelson Larsen, Rick Tatonetti, Nicholas P Butte, Atul J |
author_sort | Glicksberg, Benjamin S |
collection | PubMed |
description | OBJECTIVES: Electronic health record (EHR) data are increasingly used for biomedical discoveries. The nature of the data, however, requires expertise in both data science and EHR structure. The Observational Medical Outcomes Partnership (OMOP) common data model (CDM) standardizes the language and structure of EHR data to promote interoperability of EHR data for research. While the OMOP CDM is valuable and more attuned to research purposes, it still requires extensive domain knowledge to utilize effectively, potentially limiting more widespread adoption of EHR data for research and quality improvement. MATERIALS AND METHODS: We have created ROMOP: an R package for direct interfacing with EHR data in the OMOP CDM format. RESULTS: ROMOP streamlines typical EHR-related data processes. Its functions include exploration of data types, extraction and summarization of patient clinical and demographic data, and patient searches using any CDM vocabulary concept. CONCLUSION: ROMOP is freely available under the Massachusetts Institute of Technology (MIT) license and can be obtained from GitHub (http://github.com/BenGlicksberg/ROMOP). We detail instructions for setup and use in the Supplementary Materials. Additionally, we provide a public sandbox server containing synthesized clinical data for users to explore OMOP data and ROMOP (http://romop.ucsf.edu). |
format | Online Article Text |
id | pubmed-6800657 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-68006572019-10-19 ROMOP: a light-weight R package for interfacing with OMOP-formatted electronic health record data Glicksberg, Benjamin S Oskotsky, Boris Giangreco, Nicholas Thangaraj, Phyllis M Rudrapatna, Vivek Datta, Debajyoti Frazier, Remi Lee, Nelson Larsen, Rick Tatonetti, Nicholas P Butte, Atul J JAMIA Open Application Notes OBJECTIVES: Electronic health record (EHR) data are increasingly used for biomedical discoveries. The nature of the data, however, requires expertise in both data science and EHR structure. The Observational Medical Outcomes Partnership (OMOP) common data model (CDM) standardizes the language and structure of EHR data to promote interoperability of EHR data for research. While the OMOP CDM is valuable and more attuned to research purposes, it still requires extensive domain knowledge to utilize effectively, potentially limiting more widespread adoption of EHR data for research and quality improvement. MATERIALS AND METHODS: We have created ROMOP: an R package for direct interfacing with EHR data in the OMOP CDM format. RESULTS: ROMOP streamlines typical EHR-related data processes. Its functions include exploration of data types, extraction and summarization of patient clinical and demographic data, and patient searches using any CDM vocabulary concept. CONCLUSION: ROMOP is freely available under the Massachusetts Institute of Technology (MIT) license and can be obtained from GitHub (http://github.com/BenGlicksberg/ROMOP). We detail instructions for setup and use in the Supplementary Materials. Additionally, we provide a public sandbox server containing synthesized clinical data for users to explore OMOP data and ROMOP (http://romop.ucsf.edu). Oxford University Press 2019-01-04 /pmc/articles/PMC6800657/ /pubmed/31633087 http://dx.doi.org/10.1093/jamiaopen/ooy059 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of the American Medical Informatics Association. 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 | Application Notes Glicksberg, Benjamin S Oskotsky, Boris Giangreco, Nicholas Thangaraj, Phyllis M Rudrapatna, Vivek Datta, Debajyoti Frazier, Remi Lee, Nelson Larsen, Rick Tatonetti, Nicholas P Butte, Atul J ROMOP: a light-weight R package for interfacing with OMOP-formatted electronic health record data |
title | ROMOP: a light-weight R package for interfacing with OMOP-formatted electronic health record data |
title_full | ROMOP: a light-weight R package for interfacing with OMOP-formatted electronic health record data |
title_fullStr | ROMOP: a light-weight R package for interfacing with OMOP-formatted electronic health record data |
title_full_unstemmed | ROMOP: a light-weight R package for interfacing with OMOP-formatted electronic health record data |
title_short | ROMOP: a light-weight R package for interfacing with OMOP-formatted electronic health record data |
title_sort | romop: a light-weight r package for interfacing with omop-formatted electronic health record data |
topic | Application Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6800657/ https://www.ncbi.nlm.nih.gov/pubmed/31633087 http://dx.doi.org/10.1093/jamiaopen/ooy059 |
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