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Discovering patterns in outpatient neurology appointments using state sequence analysis
BACKGROUND: Outpatient services in the UK, and in particular outpatient neurology services, are under considerable pressure with an ever-increasing gap between capacity and demand. To improve services, we first need to understand the current situation. This study aims to explore the patterns of appo...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10626691/ https://www.ncbi.nlm.nih.gov/pubmed/37926834 http://dx.doi.org/10.1186/s12913-023-10218-y |
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author | Biggin, Fran Ashcroft, Quinta Howcroft, Timothy Knight, Jo Emsley, Hedley |
author_facet | Biggin, Fran Ashcroft, Quinta Howcroft, Timothy Knight, Jo Emsley, Hedley |
author_sort | Biggin, Fran |
collection | PubMed |
description | BACKGROUND: Outpatient services in the UK, and in particular outpatient neurology services, are under considerable pressure with an ever-increasing gap between capacity and demand. To improve services, we first need to understand the current situation. This study aims to explore the patterns of appointment type seen in outpatient neurology, in order to identify potential opportunities for change. METHODS: We use State Sequence Analysis (SSA) on routinely collected data from a single neurology outpatient clinic. SSA is an exploratory methodology which allows patterns within sequences of appointments to be discovered. We analyse sequences of appointments for the 18 months following a new appointment. Using SSA we create groups of similar appointment sequence patterns, and then analyse these clusters to determine if there are particular sequences common to different diagnostic categories. RESULTS: Of 1315 patients 887 patients had only one appointment. Among the 428 patients who had more than one appointment a 6 monthly cycle of appointments was apparent. SSA revealed that there were 11 distinct clusters of appointment sequence patterns. Further analysis showed that there are 3 diagnosis categories which have significant influence over which cluster a patient falls into: seizure/epilepsy, movement disorders, and headache. CONCLUSIONS: Neurology outpatient appointment sequences show great diversity, but there are some patterns which are common to specific diagnostic categories. Information about these common patterns could be used to inform the structure of future outpatient appointments. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-023-10218-y. |
format | Online Article Text |
id | pubmed-10626691 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-106266912023-11-07 Discovering patterns in outpatient neurology appointments using state sequence analysis Biggin, Fran Ashcroft, Quinta Howcroft, Timothy Knight, Jo Emsley, Hedley BMC Health Serv Res Research BACKGROUND: Outpatient services in the UK, and in particular outpatient neurology services, are under considerable pressure with an ever-increasing gap between capacity and demand. To improve services, we first need to understand the current situation. This study aims to explore the patterns of appointment type seen in outpatient neurology, in order to identify potential opportunities for change. METHODS: We use State Sequence Analysis (SSA) on routinely collected data from a single neurology outpatient clinic. SSA is an exploratory methodology which allows patterns within sequences of appointments to be discovered. We analyse sequences of appointments for the 18 months following a new appointment. Using SSA we create groups of similar appointment sequence patterns, and then analyse these clusters to determine if there are particular sequences common to different diagnostic categories. RESULTS: Of 1315 patients 887 patients had only one appointment. Among the 428 patients who had more than one appointment a 6 monthly cycle of appointments was apparent. SSA revealed that there were 11 distinct clusters of appointment sequence patterns. Further analysis showed that there are 3 diagnosis categories which have significant influence over which cluster a patient falls into: seizure/epilepsy, movement disorders, and headache. CONCLUSIONS: Neurology outpatient appointment sequences show great diversity, but there are some patterns which are common to specific diagnostic categories. Information about these common patterns could be used to inform the structure of future outpatient appointments. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-023-10218-y. BioMed Central 2023-11-06 /pmc/articles/PMC10626691/ /pubmed/37926834 http://dx.doi.org/10.1186/s12913-023-10218-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 Biggin, Fran Ashcroft, Quinta Howcroft, Timothy Knight, Jo Emsley, Hedley Discovering patterns in outpatient neurology appointments using state sequence analysis |
title | Discovering patterns in outpatient neurology appointments using state sequence analysis |
title_full | Discovering patterns in outpatient neurology appointments using state sequence analysis |
title_fullStr | Discovering patterns in outpatient neurology appointments using state sequence analysis |
title_full_unstemmed | Discovering patterns in outpatient neurology appointments using state sequence analysis |
title_short | Discovering patterns in outpatient neurology appointments using state sequence analysis |
title_sort | discovering patterns in outpatient neurology appointments using state sequence analysis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10626691/ https://www.ncbi.nlm.nih.gov/pubmed/37926834 http://dx.doi.org/10.1186/s12913-023-10218-y |
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