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Structured Data Capture for Oncology
Lack of interoperability is one of the greatest challenges facing healthcare informatics. Recent interoperability efforts have focused primarily on data transmission and generally ignore data capture standardization. Structured Data Capture (SDC) is an open-source technical framework that enables th...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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American Society of Clinical Oncology
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8140793/ https://www.ncbi.nlm.nih.gov/pubmed/33591796 http://dx.doi.org/10.1200/CCI.20.00103 |
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author | Goel, Alexander K. Campbell, Walter Scott Moldwin, Richard |
author_facet | Goel, Alexander K. Campbell, Walter Scott Moldwin, Richard |
author_sort | Goel, Alexander K. |
collection | PubMed |
description | Lack of interoperability is one of the greatest challenges facing healthcare informatics. Recent interoperability efforts have focused primarily on data transmission and generally ignore data capture standardization. Structured Data Capture (SDC) is an open-source technical framework that enables the capture and exchange of standardized and structured data in interoperable data entry forms (DEFs) at the point of care. Some of SDC’s primary use cases concern complex oncology data such as anatomic pathology, biomarkers, and clinical oncology data collection and reporting. Its interoperability goals are the preservation of semantic, contextual, and structural integrity of the captured data throughout the data’s lifespan. SDC documents are written in eXtensible Markup Language (XML) and are therefore computer readable, yet technology agnostic—SDC can be implemented by any EHR vendor or registry. Any SDC-capable system can render an SDC XML file into a DEF, receive and parse an SDC transmission, and regenerate the original SDC form as a DEF or synoptic report with the response data intact. SDC is therefore able to facilitate interoperable data capture and exchange for patient care, clinical trials, cancer surveillance and public health needs, clinical research, and computable care guidelines. The usability of SDC-captured oncology data is enhanced when the SDC data elements are mapped to standard terminologies. For example, an SDC map to Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) enables aggregation of SDC data with other related data sets and permits advanced queries and groupings on the basis of SNOMED CT concept attributes and description logic. SDC supports terminology maps using separate map files or as terminology codes embedded in an SDC document. |
format | Online Article Text |
id | pubmed-8140793 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | American Society of Clinical Oncology |
record_format | MEDLINE/PubMed |
spelling | pubmed-81407932022-02-16 Structured Data Capture for Oncology Goel, Alexander K. Campbell, Walter Scott Moldwin, Richard JCO Clin Cancer Inform REVIEW ARTICLES Lack of interoperability is one of the greatest challenges facing healthcare informatics. Recent interoperability efforts have focused primarily on data transmission and generally ignore data capture standardization. Structured Data Capture (SDC) is an open-source technical framework that enables the capture and exchange of standardized and structured data in interoperable data entry forms (DEFs) at the point of care. Some of SDC’s primary use cases concern complex oncology data such as anatomic pathology, biomarkers, and clinical oncology data collection and reporting. Its interoperability goals are the preservation of semantic, contextual, and structural integrity of the captured data throughout the data’s lifespan. SDC documents are written in eXtensible Markup Language (XML) and are therefore computer readable, yet technology agnostic—SDC can be implemented by any EHR vendor or registry. Any SDC-capable system can render an SDC XML file into a DEF, receive and parse an SDC transmission, and regenerate the original SDC form as a DEF or synoptic report with the response data intact. SDC is therefore able to facilitate interoperable data capture and exchange for patient care, clinical trials, cancer surveillance and public health needs, clinical research, and computable care guidelines. The usability of SDC-captured oncology data is enhanced when the SDC data elements are mapped to standard terminologies. For example, an SDC map to Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) enables aggregation of SDC data with other related data sets and permits advanced queries and groupings on the basis of SNOMED CT concept attributes and description logic. SDC supports terminology maps using separate map files or as terminology codes embedded in an SDC document. American Society of Clinical Oncology 2021-02-16 /pmc/articles/PMC8140793/ /pubmed/33591796 http://dx.doi.org/10.1200/CCI.20.00103 Text en © 2021 by American Society of Clinical Oncology https://creativecommons.org/licenses/by/4.0/Licensed under the Creative Commons Attribution 4.0 License: https://creativecommons.org/licenses/by/4.0/ |
spellingShingle | REVIEW ARTICLES Goel, Alexander K. Campbell, Walter Scott Moldwin, Richard Structured Data Capture for Oncology |
title | Structured Data Capture for Oncology |
title_full | Structured Data Capture for Oncology |
title_fullStr | Structured Data Capture for Oncology |
title_full_unstemmed | Structured Data Capture for Oncology |
title_short | Structured Data Capture for Oncology |
title_sort | structured data capture for oncology |
topic | REVIEW ARTICLES |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8140793/ https://www.ncbi.nlm.nih.gov/pubmed/33591796 http://dx.doi.org/10.1200/CCI.20.00103 |
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