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An architecture for research computing in health to support clinical and translational investigators with electronic patient data
OBJECTIVE: Obtaining electronic patient data, especially from electronic health record (EHR) systems, for clinical and translational research is difficult. Multiple research informatics systems exist but navigating the numerous applications can be challenging for scientists. This article describes A...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8690260/ https://www.ncbi.nlm.nih.gov/pubmed/34850911 http://dx.doi.org/10.1093/jamia/ocab266 |
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author | Campion, Thomas R Sholle, Evan T Pathak, Jyotishman Johnson, Stephen B Leonard, John P Cole, Curtis L |
author_facet | Campion, Thomas R Sholle, Evan T Pathak, Jyotishman Johnson, Stephen B Leonard, John P Cole, Curtis L |
author_sort | Campion, Thomas R |
collection | PubMed |
description | OBJECTIVE: Obtaining electronic patient data, especially from electronic health record (EHR) systems, for clinical and translational research is difficult. Multiple research informatics systems exist but navigating the numerous applications can be challenging for scientists. This article describes Architecture for Research Computing in Health (ARCH), our institution’s approach for matching investigators with tools and services for obtaining electronic patient data. MATERIALS AND METHODS: Supporting the spectrum of studies from populations to individuals, ARCH delivers a breadth of scientific functions—including but not limited to cohort discovery, electronic data capture, and multi-institutional data sharing—that manifest in specific systems—such as i2b2, REDCap, and PCORnet. Through a consultative process, ARCH staff align investigators with tools with respect to study design, data sources, and cost. Although most ARCH services are available free of charge, advanced engagements require fee for service. RESULTS: Since 2016 at Weill Cornell Medicine, ARCH has supported over 1200 unique investigators through more than 4177 consultations. Notably, ARCH infrastructure enabled critical coronavirus disease 2019 response activities for research and patient care. DISCUSSION: ARCH has provided a technical, regulatory, financial, and educational framework to support the biomedical research enterprise with electronic patient data. Collaboration among informaticians, biostatisticians, and clinicians has been critical to rapid generation and analysis of EHR data. CONCLUSION: A suite of tools and services, ARCH helps match investigators with informatics systems to reduce time to science. ARCH has facilitated research at Weill Cornell Medicine and may provide a model for informatics and research leaders to support scientists elsewhere. |
format | Online Article Text |
id | pubmed-8690260 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-86902602022-01-05 An architecture for research computing in health to support clinical and translational investigators with electronic patient data Campion, Thomas R Sholle, Evan T Pathak, Jyotishman Johnson, Stephen B Leonard, John P Cole, Curtis L J Am Med Inform Assoc Research and Applications OBJECTIVE: Obtaining electronic patient data, especially from electronic health record (EHR) systems, for clinical and translational research is difficult. Multiple research informatics systems exist but navigating the numerous applications can be challenging for scientists. This article describes Architecture for Research Computing in Health (ARCH), our institution’s approach for matching investigators with tools and services for obtaining electronic patient data. MATERIALS AND METHODS: Supporting the spectrum of studies from populations to individuals, ARCH delivers a breadth of scientific functions—including but not limited to cohort discovery, electronic data capture, and multi-institutional data sharing—that manifest in specific systems—such as i2b2, REDCap, and PCORnet. Through a consultative process, ARCH staff align investigators with tools with respect to study design, data sources, and cost. Although most ARCH services are available free of charge, advanced engagements require fee for service. RESULTS: Since 2016 at Weill Cornell Medicine, ARCH has supported over 1200 unique investigators through more than 4177 consultations. Notably, ARCH infrastructure enabled critical coronavirus disease 2019 response activities for research and patient care. DISCUSSION: ARCH has provided a technical, regulatory, financial, and educational framework to support the biomedical research enterprise with electronic patient data. Collaboration among informaticians, biostatisticians, and clinicians has been critical to rapid generation and analysis of EHR data. CONCLUSION: A suite of tools and services, ARCH helps match investigators with informatics systems to reduce time to science. ARCH has facilitated research at Weill Cornell Medicine and may provide a model for informatics and research leaders to support scientists elsewhere. Oxford University Press 2021-11-30 /pmc/articles/PMC8690260/ /pubmed/34850911 http://dx.doi.org/10.1093/jamia/ocab266 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_modelThis article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) |
spellingShingle | Research and Applications Campion, Thomas R Sholle, Evan T Pathak, Jyotishman Johnson, Stephen B Leonard, John P Cole, Curtis L An architecture for research computing in health to support clinical and translational investigators with electronic patient data |
title | An architecture for research computing in health to support clinical and translational investigators with electronic patient data |
title_full | An architecture for research computing in health to support clinical and translational investigators with electronic patient data |
title_fullStr | An architecture for research computing in health to support clinical and translational investigators with electronic patient data |
title_full_unstemmed | An architecture for research computing in health to support clinical and translational investigators with electronic patient data |
title_short | An architecture for research computing in health to support clinical and translational investigators with electronic patient data |
title_sort | architecture for research computing in health to support clinical and translational investigators with electronic patient data |
topic | Research and Applications |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8690260/ https://www.ncbi.nlm.nih.gov/pubmed/34850911 http://dx.doi.org/10.1093/jamia/ocab266 |
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