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Using patient flow analysis with real-time patient tracking to optimize radiation oncology consultation visits
PURPOSE: Clinical efficiency is a key component of the value-based care model and a driver of patient satisfaction. The purpose of this study was to identify and address inefficiencies at a high-volume radiation oncology clinic. METHODS AND MATERIALS: Patient flow analysis (PFA) was used to create p...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9745696/ https://www.ncbi.nlm.nih.gov/pubmed/36514109 http://dx.doi.org/10.1186/s12913-022-08809-2 |
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author | Mesko, Shane Weng, Julius Das, Prajnan Koong, Albert C. Herman, Joseph M. Elrod-Joplin, Dorothy Kerr, Ashley Aloia, Thomas Frenzel, John French, Katy E. Martinez, Wendi Recinos, Iris Alshaikh, Abdulaziz Daftary, Utpala Moreno, Amy C. Nguyen, Quynh-Nhu |
author_facet | Mesko, Shane Weng, Julius Das, Prajnan Koong, Albert C. Herman, Joseph M. Elrod-Joplin, Dorothy Kerr, Ashley Aloia, Thomas Frenzel, John French, Katy E. Martinez, Wendi Recinos, Iris Alshaikh, Abdulaziz Daftary, Utpala Moreno, Amy C. Nguyen, Quynh-Nhu |
author_sort | Mesko, Shane |
collection | PubMed |
description | PURPOSE: Clinical efficiency is a key component of the value-based care model and a driver of patient satisfaction. The purpose of this study was to identify and address inefficiencies at a high-volume radiation oncology clinic. METHODS AND MATERIALS: Patient flow analysis (PFA) was used to create process maps and optimize the workflow of consultation visits in a gastrointestinal radiation oncology clinic at a large academic cancer center. Metrics such as cycle times, waiting times, and rooming times were assessed by using a real-time patient status function in the electronic medical record for 556 consults and compared between before vs after implementation of the PFA recommendations. RESULTS: The initial PFA revealed four inefficiencies: (1) protracted rooming time, (2) inefficient communications, (3) duplicated tasks, and (4) ambiguous clinical roles. We analyzed 485 consult-visits before the PFA and 71 after the PFA. The PFA recommendations led to reductions in overall median cycle time by 21% (91 min vs 72 min, p < 0.001), in cumulative waiting times by 64% (45 min vs 16 min; p < 0.001), which included waiting room time (14 min vs 5 min; p < 0.001) and wait for physician (20 min vs. 6 min; p < 0.001). Slightly less than one-quarter (22%) of consult visits before the PFA lasted > 2 h vs. 0% after implementation of the recommendations (p < 0.001). Similarly, the proportion of visits requiring < 1 h was 16% before PFA vs 34% afterward (p < 0.001). CONCLUSIONS: PFA can be used to identify clinical inefficiencies and optimize workflows in radiation oncology consultation clinics, and implementing their findings can significantly improve cycle times and waiting times. Potential downstream effects of these interventions include improved patient experience, decreased staff burnout, financial savings, and opportunities for expanding clinical capacity. |
format | Online Article Text |
id | pubmed-9745696 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-97456962022-12-13 Using patient flow analysis with real-time patient tracking to optimize radiation oncology consultation visits Mesko, Shane Weng, Julius Das, Prajnan Koong, Albert C. Herman, Joseph M. Elrod-Joplin, Dorothy Kerr, Ashley Aloia, Thomas Frenzel, John French, Katy E. Martinez, Wendi Recinos, Iris Alshaikh, Abdulaziz Daftary, Utpala Moreno, Amy C. Nguyen, Quynh-Nhu BMC Health Serv Res Research PURPOSE: Clinical efficiency is a key component of the value-based care model and a driver of patient satisfaction. The purpose of this study was to identify and address inefficiencies at a high-volume radiation oncology clinic. METHODS AND MATERIALS: Patient flow analysis (PFA) was used to create process maps and optimize the workflow of consultation visits in a gastrointestinal radiation oncology clinic at a large academic cancer center. Metrics such as cycle times, waiting times, and rooming times were assessed by using a real-time patient status function in the electronic medical record for 556 consults and compared between before vs after implementation of the PFA recommendations. RESULTS: The initial PFA revealed four inefficiencies: (1) protracted rooming time, (2) inefficient communications, (3) duplicated tasks, and (4) ambiguous clinical roles. We analyzed 485 consult-visits before the PFA and 71 after the PFA. The PFA recommendations led to reductions in overall median cycle time by 21% (91 min vs 72 min, p < 0.001), in cumulative waiting times by 64% (45 min vs 16 min; p < 0.001), which included waiting room time (14 min vs 5 min; p < 0.001) and wait for physician (20 min vs. 6 min; p < 0.001). Slightly less than one-quarter (22%) of consult visits before the PFA lasted > 2 h vs. 0% after implementation of the recommendations (p < 0.001). Similarly, the proportion of visits requiring < 1 h was 16% before PFA vs 34% afterward (p < 0.001). CONCLUSIONS: PFA can be used to identify clinical inefficiencies and optimize workflows in radiation oncology consultation clinics, and implementing their findings can significantly improve cycle times and waiting times. Potential downstream effects of these interventions include improved patient experience, decreased staff burnout, financial savings, and opportunities for expanding clinical capacity. BioMed Central 2022-12-13 /pmc/articles/PMC9745696/ /pubmed/36514109 http://dx.doi.org/10.1186/s12913-022-08809-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Mesko, Shane Weng, Julius Das, Prajnan Koong, Albert C. Herman, Joseph M. Elrod-Joplin, Dorothy Kerr, Ashley Aloia, Thomas Frenzel, John French, Katy E. Martinez, Wendi Recinos, Iris Alshaikh, Abdulaziz Daftary, Utpala Moreno, Amy C. Nguyen, Quynh-Nhu Using patient flow analysis with real-time patient tracking to optimize radiation oncology consultation visits |
title | Using patient flow analysis with real-time patient tracking to optimize radiation oncology consultation visits |
title_full | Using patient flow analysis with real-time patient tracking to optimize radiation oncology consultation visits |
title_fullStr | Using patient flow analysis with real-time patient tracking to optimize radiation oncology consultation visits |
title_full_unstemmed | Using patient flow analysis with real-time patient tracking to optimize radiation oncology consultation visits |
title_short | Using patient flow analysis with real-time patient tracking to optimize radiation oncology consultation visits |
title_sort | using patient flow analysis with real-time patient tracking to optimize radiation oncology consultation visits |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9745696/ https://www.ncbi.nlm.nih.gov/pubmed/36514109 http://dx.doi.org/10.1186/s12913-022-08809-2 |
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