Cargando…
Evaluating waiting time with real-world health information in a high-volume cancer center
Wait time and scheduling for outpatient chemotherapy administration depends on various factors including infusion room hours of operation, availability of oncologists, nursing and pharmacy staffing, and physical space limitations. The aim of this study was to use the electronic event log of patients...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7523863/ https://www.ncbi.nlm.nih.gov/pubmed/32991401 http://dx.doi.org/10.1097/MD.0000000000021796 |
_version_ | 1783588447398658048 |
---|---|
author | Kim, Kyu-pyo Park, Yu Rang Lee, Jung Bok Kim, Hae Reong Lyu, Yongman Kim, Jeong-Eun Hong, Yong Sang Lee, Jae-Lyun Kim, Tae Won |
author_facet | Kim, Kyu-pyo Park, Yu Rang Lee, Jung Bok Kim, Hae Reong Lyu, Yongman Kim, Jeong-Eun Hong, Yong Sang Lee, Jae-Lyun Kim, Tae Won |
author_sort | Kim, Kyu-pyo |
collection | PubMed |
description | Wait time and scheduling for outpatient chemotherapy administration depends on various factors including infusion room hours of operation, availability of oncologists, nursing and pharmacy staffing, and physical space limitations. The aim of this study was to use the electronic event log of patients on health information system (HIS) to map and analyze patient flow in advanced metastatic colorectal patients at an academic cancer center. From January 2009 to December 2014, patients who were diagnosed with metastatic colorectal cancer and received outpatient chemotherapy confined to FOLFIRI (fluorouracil, leucovorin, and irinotecan) or FOLFOX (folinic acid, fluorouracil, and oxaliplatin) were identified. From the HIS, patient flow was mapped by collection of event records including blood collection and pretreatment laboratory test, arrival to outpatient clinics, outpatient session (interview, drug accountability and appointment scheduling), and initiation of chemotherapy. A total of 10,638 patients were analyzed for 136,281 outpatient visits. The total office stay time from outpatient registration to initiation of chemotherapy was 92.58 ± 87.96 (mean ± standard deviation) minutes. Each outpatient session lasted 23.75 ± 51.55 minutes. After completing the outpatient session, patients waited 1,657.23 ± 3,027.65 minutes before chemotherapy and 46.66 ± 75.94 minutes within infusion room. Compared to the prior first come first serve rule, the new reservation system showed an improvement in overall waiting time from 2,432.3 ± 4,822.9 to 2,386.7 ± 143.4 minutes; however, waiting time within infusion room slightly increased from 36.68 ± 49.33 to 48.13 ± 46.32 minutes. Our findings indicate that transaction data analytics from HIS can be used to evaluate patient flow within oncology outpatient practice based on real-world hospital data. |
format | Online Article Text |
id | pubmed-7523863 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-75238632020-10-14 Evaluating waiting time with real-world health information in a high-volume cancer center Kim, Kyu-pyo Park, Yu Rang Lee, Jung Bok Kim, Hae Reong Lyu, Yongman Kim, Jeong-Eun Hong, Yong Sang Lee, Jae-Lyun Kim, Tae Won Medicine (Baltimore) 5700 Wait time and scheduling for outpatient chemotherapy administration depends on various factors including infusion room hours of operation, availability of oncologists, nursing and pharmacy staffing, and physical space limitations. The aim of this study was to use the electronic event log of patients on health information system (HIS) to map and analyze patient flow in advanced metastatic colorectal patients at an academic cancer center. From January 2009 to December 2014, patients who were diagnosed with metastatic colorectal cancer and received outpatient chemotherapy confined to FOLFIRI (fluorouracil, leucovorin, and irinotecan) or FOLFOX (folinic acid, fluorouracil, and oxaliplatin) were identified. From the HIS, patient flow was mapped by collection of event records including blood collection and pretreatment laboratory test, arrival to outpatient clinics, outpatient session (interview, drug accountability and appointment scheduling), and initiation of chemotherapy. A total of 10,638 patients were analyzed for 136,281 outpatient visits. The total office stay time from outpatient registration to initiation of chemotherapy was 92.58 ± 87.96 (mean ± standard deviation) minutes. Each outpatient session lasted 23.75 ± 51.55 minutes. After completing the outpatient session, patients waited 1,657.23 ± 3,027.65 minutes before chemotherapy and 46.66 ± 75.94 minutes within infusion room. Compared to the prior first come first serve rule, the new reservation system showed an improvement in overall waiting time from 2,432.3 ± 4,822.9 to 2,386.7 ± 143.4 minutes; however, waiting time within infusion room slightly increased from 36.68 ± 49.33 to 48.13 ± 46.32 minutes. Our findings indicate that transaction data analytics from HIS can be used to evaluate patient flow within oncology outpatient practice based on real-world hospital data. Lippincott Williams & Wilkins 2020-09-25 /pmc/articles/PMC7523863/ /pubmed/32991401 http://dx.doi.org/10.1097/MD.0000000000021796 Text en Copyright © 2020 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0 |
spellingShingle | 5700 Kim, Kyu-pyo Park, Yu Rang Lee, Jung Bok Kim, Hae Reong Lyu, Yongman Kim, Jeong-Eun Hong, Yong Sang Lee, Jae-Lyun Kim, Tae Won Evaluating waiting time with real-world health information in a high-volume cancer center |
title | Evaluating waiting time with real-world health information in a high-volume cancer center |
title_full | Evaluating waiting time with real-world health information in a high-volume cancer center |
title_fullStr | Evaluating waiting time with real-world health information in a high-volume cancer center |
title_full_unstemmed | Evaluating waiting time with real-world health information in a high-volume cancer center |
title_short | Evaluating waiting time with real-world health information in a high-volume cancer center |
title_sort | evaluating waiting time with real-world health information in a high-volume cancer center |
topic | 5700 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7523863/ https://www.ncbi.nlm.nih.gov/pubmed/32991401 http://dx.doi.org/10.1097/MD.0000000000021796 |
work_keys_str_mv | AT kimkyupyo evaluatingwaitingtimewithrealworldhealthinformationinahighvolumecancercenter AT parkyurang evaluatingwaitingtimewithrealworldhealthinformationinahighvolumecancercenter AT leejungbok evaluatingwaitingtimewithrealworldhealthinformationinahighvolumecancercenter AT kimhaereong evaluatingwaitingtimewithrealworldhealthinformationinahighvolumecancercenter AT lyuyongman evaluatingwaitingtimewithrealworldhealthinformationinahighvolumecancercenter AT kimjeongeun evaluatingwaitingtimewithrealworldhealthinformationinahighvolumecancercenter AT hongyongsang evaluatingwaitingtimewithrealworldhealthinformationinahighvolumecancercenter AT leejaelyun evaluatingwaitingtimewithrealworldhealthinformationinahighvolumecancercenter AT kimtaewon evaluatingwaitingtimewithrealworldhealthinformationinahighvolumecancercenter |