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Development of a semi-automated method for subspecialty case distribution and prediction of intraoperative consultations in surgical pathology

BACKGROUND: In many surgical pathology laboratories, operating room schedules are prospectively reviewed to determine specimen distribution to different subspecialty services and to predict the number and nature of potential intraoperative consultations for which prior medical records and slides req...

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Autores principales: Gonzalez, Raul S., Long, Daniel, Hameed, Omar
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/PMC4498314/
https://www.ncbi.nlm.nih.gov/pubmed/26167384
http://dx.doi.org/10.4103/2153-3539.159439
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author Gonzalez, Raul S.
Long, Daniel
Hameed, Omar
author_facet Gonzalez, Raul S.
Long, Daniel
Hameed, Omar
author_sort Gonzalez, Raul S.
collection PubMed
description BACKGROUND: In many surgical pathology laboratories, operating room schedules are prospectively reviewed to determine specimen distribution to different subspecialty services and to predict the number and nature of potential intraoperative consultations for which prior medical records and slides require review. At our institution, such schedules were manually converted into easily interpretable, surgical pathology-friendly reports to facilitate these activities. This conversion, however, was time-consuming and arguably a non-value-added activity. OBJECTIVE: Our goal was to develop a semi-automated method of generating these reports that improved their readability while taking less time to perform than the manual method. MATERIALS AND METHODS: A dynamic Microsoft Excel workbook was developed to automatically convert published operating room schedules into different tabular formats. Based on the surgical procedure descriptions in the schedule, a list of linked keywords and phrases was utilized to sort cases by subspecialty and to predict potential intraoperative consultations. After two trial-and-optimization cycles, the method was incorporated into standard practice. RESULTS: The workbook distributed cases to appropriate subspecialties and accurately predicted intraoperative requests. Users indicated that they spent 1–2 h fewer per day on this activity than before, and team members preferred the formatting of the newer reports. Comparison of the manual and semi-automatic predictions showed that the mean daily difference in predicted versus actual intraoperative consultations underwent no statistically significant changes before and after implementation for most subspecialties. CONCLUSIONS: A well-designed, lean, and simple information technology solution to determine subspecialty case distribution and prediction of intraoperative consultations in surgical pathology is approximately as accurate as the gold standard manual method and requires less time and effort to generate.
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spelling pubmed-44983142015-07-12 Development of a semi-automated method for subspecialty case distribution and prediction of intraoperative consultations in surgical pathology Gonzalez, Raul S. Long, Daniel Hameed, Omar J Pathol Inform Original Article BACKGROUND: In many surgical pathology laboratories, operating room schedules are prospectively reviewed to determine specimen distribution to different subspecialty services and to predict the number and nature of potential intraoperative consultations for which prior medical records and slides require review. At our institution, such schedules were manually converted into easily interpretable, surgical pathology-friendly reports to facilitate these activities. This conversion, however, was time-consuming and arguably a non-value-added activity. OBJECTIVE: Our goal was to develop a semi-automated method of generating these reports that improved their readability while taking less time to perform than the manual method. MATERIALS AND METHODS: A dynamic Microsoft Excel workbook was developed to automatically convert published operating room schedules into different tabular formats. Based on the surgical procedure descriptions in the schedule, a list of linked keywords and phrases was utilized to sort cases by subspecialty and to predict potential intraoperative consultations. After two trial-and-optimization cycles, the method was incorporated into standard practice. RESULTS: The workbook distributed cases to appropriate subspecialties and accurately predicted intraoperative requests. Users indicated that they spent 1–2 h fewer per day on this activity than before, and team members preferred the formatting of the newer reports. Comparison of the manual and semi-automatic predictions showed that the mean daily difference in predicted versus actual intraoperative consultations underwent no statistically significant changes before and after implementation for most subspecialties. CONCLUSIONS: A well-designed, lean, and simple information technology solution to determine subspecialty case distribution and prediction of intraoperative consultations in surgical pathology is approximately as accurate as the gold standard manual method and requires less time and effort to generate. Medknow Publications & Media Pvt Ltd 2015-06-29 /pmc/articles/PMC4498314/ /pubmed/26167384 http://dx.doi.org/10.4103/2153-3539.159439 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 Original Article
Gonzalez, Raul S.
Long, Daniel
Hameed, Omar
Development of a semi-automated method for subspecialty case distribution and prediction of intraoperative consultations in surgical pathology
title Development of a semi-automated method for subspecialty case distribution and prediction of intraoperative consultations in surgical pathology
title_full Development of a semi-automated method for subspecialty case distribution and prediction of intraoperative consultations in surgical pathology
title_fullStr Development of a semi-automated method for subspecialty case distribution and prediction of intraoperative consultations in surgical pathology
title_full_unstemmed Development of a semi-automated method for subspecialty case distribution and prediction of intraoperative consultations in surgical pathology
title_short Development of a semi-automated method for subspecialty case distribution and prediction of intraoperative consultations in surgical pathology
title_sort development of a semi-automated method for subspecialty case distribution and prediction of intraoperative consultations in surgical pathology
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4498314/
https://www.ncbi.nlm.nih.gov/pubmed/26167384
http://dx.doi.org/10.4103/2153-3539.159439
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