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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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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. |
format | Online Article Text |
id | pubmed-8892022 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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