Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Goel, Alexander K., Campbell, Walter Scott, Moldwin, Richard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society of Clinical Oncology 2021
Materias:
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
_version_ 1783696245977513984
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
work_keys_str_mv AT goelalexanderk structureddatacaptureforoncology
AT campbellwalterscott structureddatacaptureforoncology
AT moldwinrichard structureddatacaptureforoncology