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Statistical complexity of reasons for encounter in high users of out of hours primary care: analysis of a national service

BACKGROUND: Managing demand for urgent and unscheduled care is a major problem for health services globally. A particular issue is that some patients appear to make heavy use of services, including primary care out of hours. We hypothesised that greater variation (statistical complexity) in reasons...

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Autores principales: Stegink, Sarah, Elliott, Alison M., Burton, Christopher
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6368808/
https://www.ncbi.nlm.nih.gov/pubmed/30736776
http://dx.doi.org/10.1186/s12913-019-3938-z
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author Stegink, Sarah
Elliott, Alison M.
Burton, Christopher
author_facet Stegink, Sarah
Elliott, Alison M.
Burton, Christopher
author_sort Stegink, Sarah
collection PubMed
description BACKGROUND: Managing demand for urgent and unscheduled care is a major problem for health services globally. A particular issue is that some patients appear to make heavy use of services, including primary care out of hours. We hypothesised that greater variation (statistical complexity) in reasons for attending primary care out of hours services may be a useful marker of patients at high risk of ongoing heavy service use. METHODS: We analysed an anonymised dataset of contacts with the primary care out of hours care for Scotland in 2011. This contained 120,395 contacts from 13,981 high-using patients who made 5 or more contacts during a calendar year. We allocated the stated reason for each encounter into one of 14 categories. For each patient we calculated measures of statistical complexity of reasons for encounter including the count of different categories, Herfindahl index and statistical entropy of either the categories themselves, or the category transitions. We examined the association of these measures of statistical complexity with patient and healthcare use characteristics. RESULTS: The high users comprised 2.4% of adults using the service and accounted for 15% of all contacts. Statistical complexity (as entropy of categories) increased with number of contacts but was not substantially influenced by either patient age or sex. This lack of association with age was unexpected as with increasing multi-morbidity one would expect greater variability in reason for encounter. Between 5 and 10 consultations, higher entropy was associated with a reduced likelihood of further consultations. In contrast, the occurrence of one or more contacts for a mental health problem was associated with increased likelihood of further consultations. CONCLUSION: Complexity of reason for encounter can be estimated in an out of hours primary care setting. Similar levels of statistical complexity are seen in younger and older adults (suggesting that it is more to do with consultation behaviour than morbidity) but it is not a predictor of ongoing high use of urgent care. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12913-019-3938-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-63688082019-02-15 Statistical complexity of reasons for encounter in high users of out of hours primary care: analysis of a national service Stegink, Sarah Elliott, Alison M. Burton, Christopher BMC Health Serv Res Research Article BACKGROUND: Managing demand for urgent and unscheduled care is a major problem for health services globally. A particular issue is that some patients appear to make heavy use of services, including primary care out of hours. We hypothesised that greater variation (statistical complexity) in reasons for attending primary care out of hours services may be a useful marker of patients at high risk of ongoing heavy service use. METHODS: We analysed an anonymised dataset of contacts with the primary care out of hours care for Scotland in 2011. This contained 120,395 contacts from 13,981 high-using patients who made 5 or more contacts during a calendar year. We allocated the stated reason for each encounter into one of 14 categories. For each patient we calculated measures of statistical complexity of reasons for encounter including the count of different categories, Herfindahl index and statistical entropy of either the categories themselves, or the category transitions. We examined the association of these measures of statistical complexity with patient and healthcare use characteristics. RESULTS: The high users comprised 2.4% of adults using the service and accounted for 15% of all contacts. Statistical complexity (as entropy of categories) increased with number of contacts but was not substantially influenced by either patient age or sex. This lack of association with age was unexpected as with increasing multi-morbidity one would expect greater variability in reason for encounter. Between 5 and 10 consultations, higher entropy was associated with a reduced likelihood of further consultations. In contrast, the occurrence of one or more contacts for a mental health problem was associated with increased likelihood of further consultations. CONCLUSION: Complexity of reason for encounter can be estimated in an out of hours primary care setting. Similar levels of statistical complexity are seen in younger and older adults (suggesting that it is more to do with consultation behaviour than morbidity) but it is not a predictor of ongoing high use of urgent care. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12913-019-3938-z) contains supplementary material, which is available to authorized users. BioMed Central 2019-02-08 /pmc/articles/PMC6368808/ /pubmed/30736776 http://dx.doi.org/10.1186/s12913-019-3938-z Text en © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Stegink, Sarah
Elliott, Alison M.
Burton, Christopher
Statistical complexity of reasons for encounter in high users of out of hours primary care: analysis of a national service
title Statistical complexity of reasons for encounter in high users of out of hours primary care: analysis of a national service
title_full Statistical complexity of reasons for encounter in high users of out of hours primary care: analysis of a national service
title_fullStr Statistical complexity of reasons for encounter in high users of out of hours primary care: analysis of a national service
title_full_unstemmed Statistical complexity of reasons for encounter in high users of out of hours primary care: analysis of a national service
title_short Statistical complexity of reasons for encounter in high users of out of hours primary care: analysis of a national service
title_sort statistical complexity of reasons for encounter in high users of out of hours primary care: analysis of a national service
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6368808/
https://www.ncbi.nlm.nih.gov/pubmed/30736776
http://dx.doi.org/10.1186/s12913-019-3938-z
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