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A Method for Balancing Provider Schedules in Outpatient Specialty Clinics

Background. Variability in outpatient specialty clinic schedules contributes to numerous adverse effects including chaotic clinic settings, provider burnout, increased patient waiting times, and inefficient use of resources. This research measures the benefit of balancing provider schedules in an ou...

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Autores principales: Berg, Bjorn P., Erdogan, S. Ayca, Lobo, Jennifer Mason, Pendleton, Kathryn
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7592316/
https://www.ncbi.nlm.nih.gov/pubmed/33178888
http://dx.doi.org/10.1177/2381468320963063
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author Berg, Bjorn P.
Erdogan, S. Ayca
Lobo, Jennifer Mason
Pendleton, Kathryn
author_facet Berg, Bjorn P.
Erdogan, S. Ayca
Lobo, Jennifer Mason
Pendleton, Kathryn
author_sort Berg, Bjorn P.
collection PubMed
description Background. Variability in outpatient specialty clinic schedules contributes to numerous adverse effects including chaotic clinic settings, provider burnout, increased patient waiting times, and inefficient use of resources. This research measures the benefit of balancing provider schedules in an outpatient specialty clinic. Design. We developed a constrained optimization model to minimize the variability in provider schedules in an outpatient specialty clinic. Schedule variability was defined as the variance in the number of providers scheduled for clinic during each hour the clinic is open. We compared the variance in the number of providers scheduled per hour resulting from the constrained optimization schedule with the actual schedule for three reference scenarios used in practice at M Health Fairview’s Clinics and Surgery Center as a case study. Results. Compared to the actual schedules, use of constrained optimization modeling reduced the variance in the number of providers scheduled per hour by 92% (1.70–0.14), 88% (1.98–0.24), and 94% (1.98–0.12). When compared with the reference scenarios, the total, and per provider, assigned clinic hours remained the same. Use of constrained optimization modeling also reduced the maximum number of providers scheduled during each of the actual schedules for each of the reference scenarios. The constrained optimization schedules utilized 100% of the available clinic time compared to the reference scenario schedules where providers were scheduled during 87%, 92%, and 82% of the open clinic time, respectively. Limitations. The scheduling model’s use requires a centralized provider scheduling process in the clinic. Conclusions. Constrained optimization can help balance provider schedules in outpatient specialty clinics, thereby reducing the risk of negative effects associated with highly variable clinic settings.
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spelling pubmed-75923162020-11-10 A Method for Balancing Provider Schedules in Outpatient Specialty Clinics Berg, Bjorn P. Erdogan, S. Ayca Lobo, Jennifer Mason Pendleton, Kathryn MDM Policy Pract Article Background. Variability in outpatient specialty clinic schedules contributes to numerous adverse effects including chaotic clinic settings, provider burnout, increased patient waiting times, and inefficient use of resources. This research measures the benefit of balancing provider schedules in an outpatient specialty clinic. Design. We developed a constrained optimization model to minimize the variability in provider schedules in an outpatient specialty clinic. Schedule variability was defined as the variance in the number of providers scheduled for clinic during each hour the clinic is open. We compared the variance in the number of providers scheduled per hour resulting from the constrained optimization schedule with the actual schedule for three reference scenarios used in practice at M Health Fairview’s Clinics and Surgery Center as a case study. Results. Compared to the actual schedules, use of constrained optimization modeling reduced the variance in the number of providers scheduled per hour by 92% (1.70–0.14), 88% (1.98–0.24), and 94% (1.98–0.12). When compared with the reference scenarios, the total, and per provider, assigned clinic hours remained the same. Use of constrained optimization modeling also reduced the maximum number of providers scheduled during each of the actual schedules for each of the reference scenarios. The constrained optimization schedules utilized 100% of the available clinic time compared to the reference scenario schedules where providers were scheduled during 87%, 92%, and 82% of the open clinic time, respectively. Limitations. The scheduling model’s use requires a centralized provider scheduling process in the clinic. Conclusions. Constrained optimization can help balance provider schedules in outpatient specialty clinics, thereby reducing the risk of negative effects associated with highly variable clinic settings. SAGE Publications 2020-10-20 /pmc/articles/PMC7592316/ /pubmed/33178888 http://dx.doi.org/10.1177/2381468320963063 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Article
Berg, Bjorn P.
Erdogan, S. Ayca
Lobo, Jennifer Mason
Pendleton, Kathryn
A Method for Balancing Provider Schedules in Outpatient Specialty Clinics
title A Method for Balancing Provider Schedules in Outpatient Specialty Clinics
title_full A Method for Balancing Provider Schedules in Outpatient Specialty Clinics
title_fullStr A Method for Balancing Provider Schedules in Outpatient Specialty Clinics
title_full_unstemmed A Method for Balancing Provider Schedules in Outpatient Specialty Clinics
title_short A Method for Balancing Provider Schedules in Outpatient Specialty Clinics
title_sort method for balancing provider schedules in outpatient specialty clinics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7592316/
https://www.ncbi.nlm.nih.gov/pubmed/33178888
http://dx.doi.org/10.1177/2381468320963063
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