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Extraction and analysis of discrete synoptic pathology report data using R

BACKGROUND: Synoptic pathology reports can serve as a rich source of cancer information, particularly when the content is available as discrete electronic data fields. Our institution generates such reports as part of a province wide program in Ontario but the resulting data is not easily extracted...

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Autor principal: Boag, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4687157/
https://www.ncbi.nlm.nih.gov/pubmed/26730352
http://dx.doi.org/10.4103/2153-3539.170649
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author Boag, Alexander
author_facet Boag, Alexander
author_sort Boag, Alexander
collection PubMed
description BACKGROUND: Synoptic pathology reports can serve as a rich source of cancer information, particularly when the content is available as discrete electronic data fields. Our institution generates such reports as part of a province wide program in Ontario but the resulting data is not easily extracted and analyzed at the local level. METHODS: A low cost system was developed using the open sourced and freely available R scripting/data analysis environment to parse synoptic report results into a dataframe and perform basic summary statistics. RESULTS: As a pilot project text reports from 427 prostate needle biopsies were successfully read into R and the data elements split out and converted into appropriated data classes for analysis. CONCLUSION: This approach provides a simple solution at minimal cost that can make discrete synoptic report data readily available for quality assurance and research activities.
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spelling pubmed-46871572016-01-04 Extraction and analysis of discrete synoptic pathology report data using R Boag, Alexander J Pathol Inform Technical Note BACKGROUND: Synoptic pathology reports can serve as a rich source of cancer information, particularly when the content is available as discrete electronic data fields. Our institution generates such reports as part of a province wide program in Ontario but the resulting data is not easily extracted and analyzed at the local level. METHODS: A low cost system was developed using the open sourced and freely available R scripting/data analysis environment to parse synoptic report results into a dataframe and perform basic summary statistics. RESULTS: As a pilot project text reports from 427 prostate needle biopsies were successfully read into R and the data elements split out and converted into appropriated data classes for analysis. CONCLUSION: This approach provides a simple solution at minimal cost that can make discrete synoptic report data readily available for quality assurance and research activities. Medknow Publications & Media Pvt Ltd 2015-11-27 /pmc/articles/PMC4687157/ /pubmed/26730352 http://dx.doi.org/10.4103/2153-3539.170649 Text en Copyright: © 2015 Journal of Pathology Informatics http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.
spellingShingle Technical Note
Boag, Alexander
Extraction and analysis of discrete synoptic pathology report data using R
title Extraction and analysis of discrete synoptic pathology report data using R
title_full Extraction and analysis of discrete synoptic pathology report data using R
title_fullStr Extraction and analysis of discrete synoptic pathology report data using R
title_full_unstemmed Extraction and analysis of discrete synoptic pathology report data using R
title_short Extraction and analysis of discrete synoptic pathology report data using R
title_sort extraction and analysis of discrete synoptic pathology report data using r
topic Technical Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4687157/
https://www.ncbi.nlm.nih.gov/pubmed/26730352
http://dx.doi.org/10.4103/2153-3539.170649
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