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Coordination of Intraoperative Neurophysiologic Monitoring Technologist and Surgery Schedules.

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Title: Coordination of Intraoperative Neurophysiologic Monitoring Technologist and Surgery Schedules.
Authors: Huang, Yu-Li1,2 huang.yuli@mayo.edu, Bansal, Ankit3, Berg, Bjorn P.4, Tommaso, Christopher P.5, Laughlin, Ruple S.5
Source: Journal of Medical Systems. Oct2022, Vol. 46 Issue 10, p1-11. 11p. 1 Black and White Photograph, 1 Diagram, 3 Charts, 4 Graphs.
Subjects: Health services accessibility, Surgery, Intraoperative monitoring, Medical appointments, Working hours, Health care rationing
Abstract: Resource coordination in surgical scheduling remains challenging in health care delivery systems. This is especially the case in highly-specialized settings such as coordinating Intraoperative Neurophysiologic Monitoring (IONM) resources. Inefficient coordination yields higher costs, limited access to care, and creates constraints to surgical quality and outcomes. To maximize utilization of IONM resources, optimization-based algorithms are proposed to effectively schedule IONM surgical cases and technologists and evaluate staffing needs. Data with 10 days of case volumes, their surgery durations, and technologist staffing was used to demonstrate method effectiveness. An iterative optimization-based model that determines both optimal surgery and technologist start time (operational scenario 4) was built in an Excel spreadsheet along with Excel's Solver settings. It was compared with current practice (operational scenario 1) and optimization solution on only surgery start time (operational scenario 2) or technologist start time (operational scenario 3). Comparisons are made with respect to technologist overtime and under-utilization time. The results conclude that scenario 4 significantly reduces overtime by 74% and under-utilization time by 86% as well as technologist needs by 10%. For practices that do not have flexibility to alter surgeon preference on surgery start time or IONM technologist staffing levels, both scenarios 2 and 3 also result in substantial reductions in technologist overtime and under-utilization. Moreover, IONM technologist staffing options are discussed to accommodate technologist preferences and set constraints for surgical case scheduling. All optimization-based approaches presented in this paper are able to improve utilization of IONM resources and ultimately improve the coordination and efficiency of highly-specialized resources. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Medical Systems is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Coordination of Intraoperative Neurophysiologic Monitoring Technologist and Surgery Schedules.
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  Data: <searchLink fieldCode="AR" term="%22Huang%2C+Yu-Li%22">Huang, Yu-Li</searchLink><relatesTo>1,2</relatesTo><i> huang.yuli@mayo.edu</i><br /><searchLink fieldCode="AR" term="%22Bansal%2C+Ankit%22">Bansal, Ankit</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Berg%2C+Bjorn+P%2E%22">Berg, Bjorn P.</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Tommaso%2C+Christopher+P%2E%22">Tommaso, Christopher P.</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Laughlin%2C+Ruple+S%2E%22">Laughlin, Ruple S.</searchLink><relatesTo>5</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Medical+Systems%22">Journal of Medical Systems</searchLink>. Oct2022, Vol. 46 Issue 10, p1-11. 11p. 1 Black and White Photograph, 1 Diagram, 3 Charts, 4 Graphs.
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  Data: <searchLink fieldCode="DE" term="%22Health+services+accessibility%22">Health services accessibility</searchLink><br /><searchLink fieldCode="DE" term="%22Surgery%22">Surgery</searchLink><br /><searchLink fieldCode="DE" term="%22Intraoperative+monitoring%22">Intraoperative monitoring</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+appointments%22">Medical appointments</searchLink><br /><searchLink fieldCode="DE" term="%22Working+hours%22">Working hours</searchLink><br /><searchLink fieldCode="DE" term="%22Health+care+rationing%22">Health care rationing</searchLink>
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  Data: Resource coordination in surgical scheduling remains challenging in health care delivery systems. This is especially the case in highly-specialized settings such as coordinating Intraoperative Neurophysiologic Monitoring (IONM) resources. Inefficient coordination yields higher costs, limited access to care, and creates constraints to surgical quality and outcomes. To maximize utilization of IONM resources, optimization-based algorithms are proposed to effectively schedule IONM surgical cases and technologists and evaluate staffing needs. Data with 10 days of case volumes, their surgery durations, and technologist staffing was used to demonstrate method effectiveness. An iterative optimization-based model that determines both optimal surgery and technologist start time (operational scenario 4) was built in an Excel spreadsheet along with Excel's Solver settings. It was compared with current practice (operational scenario 1) and optimization solution on only surgery start time (operational scenario 2) or technologist start time (operational scenario 3). Comparisons are made with respect to technologist overtime and under-utilization time. The results conclude that scenario 4 significantly reduces overtime by 74% and under-utilization time by 86% as well as technologist needs by 10%. For practices that do not have flexibility to alter surgeon preference on surgery start time or IONM technologist staffing levels, both scenarios 2 and 3 also result in substantial reductions in technologist overtime and under-utilization. Moreover, IONM technologist staffing options are discussed to accommodate technologist preferences and set constraints for surgical case scheduling. All optimization-based approaches presented in this paper are able to improve utilization of IONM resources and ultimately improve the coordination and efficiency of highly-specialized resources. [ABSTRACT FROM AUTHOR]
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  Label:
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  Data: <i>Copyright of Journal of Medical Systems is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Oct2022
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