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Evaluation and Improvement of Bottlenecking in a Multidisciplinary Oncology Clinic: An Electronic Medical Record Intervention
Purpose: Clinic members reported slower patient flow in the mornings at a multidisciplinary oncology clinic. This study identified the causes of clinic bottlenecking via analysis of patient schedules and transit times, then corrected discrepancies through a quality improvement program. Methods: Tran...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cureus
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6609293/ https://www.ncbi.nlm.nih.gov/pubmed/31309008 http://dx.doi.org/10.7759/cureus.4583 |
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author | Ning, Matthew S Dean, Mary K Taylor, Kyle A Arzu, Isidora Fleming, Nicole D Mutyala, Neelesh Suresh, Prakul Lewis, Mark A Tu, Janet Hassid, Victor J Joe, Timisha Byler, Caitlin Bloom, Elizabeth S Shah, Shalin |
author_facet | Ning, Matthew S Dean, Mary K Taylor, Kyle A Arzu, Isidora Fleming, Nicole D Mutyala, Neelesh Suresh, Prakul Lewis, Mark A Tu, Janet Hassid, Victor J Joe, Timisha Byler, Caitlin Bloom, Elizabeth S Shah, Shalin |
author_sort | Ning, Matthew S |
collection | PubMed |
description | Purpose: Clinic members reported slower patient flow in the mornings at a multidisciplinary oncology clinic. This study identified the causes of clinic bottlenecking via analysis of patient schedules and transit times, then corrected discrepancies through a quality improvement program. Methods: Transit times were measured using tracking cards handed out at check-in, marked by each clinic member throughout the encounter, and collected upon discharge. Data were analyzed for differences between morning and afternoon patients, and a Pareto chart was formulated to assess for discrepancies in distribution. Repeat plan-do-study-act (PDSA) cycles were conducted, implementing two changes to redistribute appointments to optimize clinic workflow. Results: A total of 2951 patient appointments were analyzed: 589 at baseline, 277 following an initial intervention, and 2085 following a subsequent intervention. Analysis of patient transit times revealed no significant differences between morning and afternoon patient groups (t-test, p=.13-.99), with no transit interval markedly longer than others (t-test, p=.32-.83). However, upon evaluation of appointment times, a maldistribution was noted with 57% of patients concentrated between 9:00 am to 12:00 pm, accounting for the perception of bottlenecking. An initial intervention offering patients afternoon appointments on a voluntary basis was insufficient for rebalancing distribution (chi-square test, p=.299); however, an electronic medical record (EMR) intervention with rigid appointment templates was successful (chi-square test, p<.001). Conclusion: An imbalance of appointment times contributed to the perception of slow clinic throughput. This study emphasizes the importance of systematically investigating even consensus observations for validity prior to costly interventions. Furthermore, these results support the utility of information technology in optimizing clinic workflow. |
format | Online Article Text |
id | pubmed-6609293 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Cureus |
record_format | MEDLINE/PubMed |
spelling | pubmed-66092932019-07-15 Evaluation and Improvement of Bottlenecking in a Multidisciplinary Oncology Clinic: An Electronic Medical Record Intervention Ning, Matthew S Dean, Mary K Taylor, Kyle A Arzu, Isidora Fleming, Nicole D Mutyala, Neelesh Suresh, Prakul Lewis, Mark A Tu, Janet Hassid, Victor J Joe, Timisha Byler, Caitlin Bloom, Elizabeth S Shah, Shalin Cureus Oncology Purpose: Clinic members reported slower patient flow in the mornings at a multidisciplinary oncology clinic. This study identified the causes of clinic bottlenecking via analysis of patient schedules and transit times, then corrected discrepancies through a quality improvement program. Methods: Transit times were measured using tracking cards handed out at check-in, marked by each clinic member throughout the encounter, and collected upon discharge. Data were analyzed for differences between morning and afternoon patients, and a Pareto chart was formulated to assess for discrepancies in distribution. Repeat plan-do-study-act (PDSA) cycles were conducted, implementing two changes to redistribute appointments to optimize clinic workflow. Results: A total of 2951 patient appointments were analyzed: 589 at baseline, 277 following an initial intervention, and 2085 following a subsequent intervention. Analysis of patient transit times revealed no significant differences between morning and afternoon patient groups (t-test, p=.13-.99), with no transit interval markedly longer than others (t-test, p=.32-.83). However, upon evaluation of appointment times, a maldistribution was noted with 57% of patients concentrated between 9:00 am to 12:00 pm, accounting for the perception of bottlenecking. An initial intervention offering patients afternoon appointments on a voluntary basis was insufficient for rebalancing distribution (chi-square test, p=.299); however, an electronic medical record (EMR) intervention with rigid appointment templates was successful (chi-square test, p<.001). Conclusion: An imbalance of appointment times contributed to the perception of slow clinic throughput. This study emphasizes the importance of systematically investigating even consensus observations for validity prior to costly interventions. Furthermore, these results support the utility of information technology in optimizing clinic workflow. Cureus 2019-05-02 /pmc/articles/PMC6609293/ /pubmed/31309008 http://dx.doi.org/10.7759/cureus.4583 Text en Copyright © 2019, Ning et al. http://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Oncology Ning, Matthew S Dean, Mary K Taylor, Kyle A Arzu, Isidora Fleming, Nicole D Mutyala, Neelesh Suresh, Prakul Lewis, Mark A Tu, Janet Hassid, Victor J Joe, Timisha Byler, Caitlin Bloom, Elizabeth S Shah, Shalin Evaluation and Improvement of Bottlenecking in a Multidisciplinary Oncology Clinic: An Electronic Medical Record Intervention |
title | Evaluation and Improvement of Bottlenecking in a Multidisciplinary Oncology Clinic: An Electronic Medical Record Intervention |
title_full | Evaluation and Improvement of Bottlenecking in a Multidisciplinary Oncology Clinic: An Electronic Medical Record Intervention |
title_fullStr | Evaluation and Improvement of Bottlenecking in a Multidisciplinary Oncology Clinic: An Electronic Medical Record Intervention |
title_full_unstemmed | Evaluation and Improvement of Bottlenecking in a Multidisciplinary Oncology Clinic: An Electronic Medical Record Intervention |
title_short | Evaluation and Improvement of Bottlenecking in a Multidisciplinary Oncology Clinic: An Electronic Medical Record Intervention |
title_sort | evaluation and improvement of bottlenecking in a multidisciplinary oncology clinic: an electronic medical record intervention |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6609293/ https://www.ncbi.nlm.nih.gov/pubmed/31309008 http://dx.doi.org/10.7759/cureus.4583 |
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