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Searching Full-Text Anatomic Pathology Reports Using Business Intelligence Software

Although the laboratory information system has largely solved the problem of storing anatomic pathology reports and disseminating their contents across the healthcare system, the retrospective query of anatomic pathology reports remains an area for improvement across laboratory information system ve...

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Detalles Bibliográficos
Autores principales: Arvisais-Anhalt, Simone, Lehmann, Christoph U., Bishop, Justin A., Balani, Jyoti, Boutte, Laurie, Morales, Marjorie, Park, Jason Y., Araj, Ellen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8892022/
https://www.ncbi.nlm.nih.gov/pubmed/35251753
http://dx.doi.org/10.1016/j.jpi.2022.100014
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author Arvisais-Anhalt, Simone
Lehmann, Christoph U.
Bishop, Justin A.
Balani, Jyoti
Boutte, Laurie
Morales, Marjorie
Park, Jason Y.
Araj, Ellen
author_facet Arvisais-Anhalt, Simone
Lehmann, Christoph U.
Bishop, Justin A.
Balani, Jyoti
Boutte, Laurie
Morales, Marjorie
Park, Jason Y.
Araj, Ellen
author_sort Arvisais-Anhalt, Simone
collection PubMed
description Although the laboratory information system has largely solved the problem of storing anatomic pathology reports and disseminating their contents across the healthcare system, the retrospective query of anatomic pathology reports remains an area for improvement across laboratory information system vendors. Our institution desired the ability to query our repository of anatomic pathology reports for clinical, operational, research, and educational purposes. To address this need, we developed a full-text anatomic pathology search tool using the business intelligence software, Tableau. Our search tool allows users to query the 333,685 anatomic pathology reports from our institutional clinical relational database using the business intelligence tool’s built-in regular expression functionality. Users securely access the search tool using any web browser, thereby avoiding the cost of installing or maintaining software on users’ computers. This tool is laboratory information system vendor agnostic and as many institutions already subscribe to business intelligence software, we believe this solution could be easily reproduced at other institutions and in other clinical departments.
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spelling pubmed-88920222022-03-04 Searching Full-Text Anatomic Pathology Reports Using Business Intelligence Software Arvisais-Anhalt, Simone Lehmann, Christoph U. Bishop, Justin A. Balani, Jyoti Boutte, Laurie Morales, Marjorie Park, Jason Y. Araj, Ellen J Pathol Inform Original Research Article Although the laboratory information system has largely solved the problem of storing anatomic pathology reports and disseminating their contents across the healthcare system, the retrospective query of anatomic pathology reports remains an area for improvement across laboratory information system vendors. Our institution desired the ability to query our repository of anatomic pathology reports for clinical, operational, research, and educational purposes. To address this need, we developed a full-text anatomic pathology search tool using the business intelligence software, Tableau. Our search tool allows users to query the 333,685 anatomic pathology reports from our institutional clinical relational database using the business intelligence tool’s built-in regular expression functionality. Users securely access the search tool using any web browser, thereby avoiding the cost of installing or maintaining software on users’ computers. This tool is laboratory information system vendor agnostic and as many institutions already subscribe to business intelligence software, we believe this solution could be easily reproduced at other institutions and in other clinical departments. Elsevier 2022-02-07 /pmc/articles/PMC8892022/ /pubmed/35251753 http://dx.doi.org/10.1016/j.jpi.2022.100014 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Research Article
Arvisais-Anhalt, Simone
Lehmann, Christoph U.
Bishop, Justin A.
Balani, Jyoti
Boutte, Laurie
Morales, Marjorie
Park, Jason Y.
Araj, Ellen
Searching Full-Text Anatomic Pathology Reports Using Business Intelligence Software
title Searching Full-Text Anatomic Pathology Reports Using Business Intelligence Software
title_full Searching Full-Text Anatomic Pathology Reports Using Business Intelligence Software
title_fullStr Searching Full-Text Anatomic Pathology Reports Using Business Intelligence Software
title_full_unstemmed Searching Full-Text Anatomic Pathology Reports Using Business Intelligence Software
title_short Searching Full-Text Anatomic Pathology Reports Using Business Intelligence Software
title_sort searching full-text anatomic pathology reports using business intelligence software
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8892022/
https://www.ncbi.nlm.nih.gov/pubmed/35251753
http://dx.doi.org/10.1016/j.jpi.2022.100014
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