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Do healthcare services behave as complex systems? Analysis of patterns of attendance and implications for service delivery

BACKGROUND: The science of complex systems has been proposed as a way of understanding health services and the demand for them, but there is little quantitative evidence to support this. We analysed patterns of healthcare use in different urgent care settings to see if they showed two characteristic...

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Autores principales: Burton, Christopher, Elliott, Alison, Cochran, Amanda, Love, Tom
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6127924/
https://www.ncbi.nlm.nih.gov/pubmed/30189866
http://dx.doi.org/10.1186/s12916-018-1132-5
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author Burton, Christopher
Elliott, Alison
Cochran, Amanda
Love, Tom
author_facet Burton, Christopher
Elliott, Alison
Cochran, Amanda
Love, Tom
author_sort Burton, Christopher
collection PubMed
description BACKGROUND: The science of complex systems has been proposed as a way of understanding health services and the demand for them, but there is little quantitative evidence to support this. We analysed patterns of healthcare use in different urgent care settings to see if they showed two characteristic statistical features of complex systems: heavy-tailed distributions (including the inverse power law) and generative burst patterns. METHODS: We conducted three linked studies. In study 1 we analysed the distribution of number of contacts per patient with an urgent care service in two settings: emergency department (ED) and primary care out-of-hours (PCOOH) services. We hypothesised that these distributions should be heavy-tailed (inverse power law or log-normal) in keeping with typical complex systems. In study 2 we analysed the distribution of bursts of contact with urgent care services by individuals: correlated bursts of activity occur in complex systems and represent a mechanism by which overall heavy-tailed distributions arise. In study 3 we replicated the approach of study 1 using data systematically identified from published sources. RESULTS: Study 1 involved data from a PCOOH service in Scotland (725,000) adults, 1.1 million contacts) and an ED in New Zealand (60,000 adults, 98,000 contacts). The total number of contacts per individual in each dataset was statistically indistinguishable from an inverse power law (p > 0.05) above 4 contacts for the PCOOH data and 3 contacts for the ED data. Study 2 found the distribution of contact bursts closely followed a heavy-tailed distribution (p < 0.008), indicating the presence of correlated bursts. Study 3 identified data from 17 studies across 8 countries and found distributions similar to study 1 in all of them. CONCLUSIONS: Urgent healthcare use displays characteristic statistical features of large complex systems. These studies provide strong quantitative evidence that healthcare services behave as complex systems and have important implications for urgent care. Interventions to manage demand must address drivers for consultation across the whole system: focusing on only the highest users (in the tail of the distribution) will have limited impact on efficiency. Bursts of attendance — and ways to shorten them — represent promising targets for managing demand.
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spelling pubmed-61279242018-09-10 Do healthcare services behave as complex systems? Analysis of patterns of attendance and implications for service delivery Burton, Christopher Elliott, Alison Cochran, Amanda Love, Tom BMC Med Research Article BACKGROUND: The science of complex systems has been proposed as a way of understanding health services and the demand for them, but there is little quantitative evidence to support this. We analysed patterns of healthcare use in different urgent care settings to see if they showed two characteristic statistical features of complex systems: heavy-tailed distributions (including the inverse power law) and generative burst patterns. METHODS: We conducted three linked studies. In study 1 we analysed the distribution of number of contacts per patient with an urgent care service in two settings: emergency department (ED) and primary care out-of-hours (PCOOH) services. We hypothesised that these distributions should be heavy-tailed (inverse power law or log-normal) in keeping with typical complex systems. In study 2 we analysed the distribution of bursts of contact with urgent care services by individuals: correlated bursts of activity occur in complex systems and represent a mechanism by which overall heavy-tailed distributions arise. In study 3 we replicated the approach of study 1 using data systematically identified from published sources. RESULTS: Study 1 involved data from a PCOOH service in Scotland (725,000) adults, 1.1 million contacts) and an ED in New Zealand (60,000 adults, 98,000 contacts). The total number of contacts per individual in each dataset was statistically indistinguishable from an inverse power law (p > 0.05) above 4 contacts for the PCOOH data and 3 contacts for the ED data. Study 2 found the distribution of contact bursts closely followed a heavy-tailed distribution (p < 0.008), indicating the presence of correlated bursts. Study 3 identified data from 17 studies across 8 countries and found distributions similar to study 1 in all of them. CONCLUSIONS: Urgent healthcare use displays characteristic statistical features of large complex systems. These studies provide strong quantitative evidence that healthcare services behave as complex systems and have important implications for urgent care. Interventions to manage demand must address drivers for consultation across the whole system: focusing on only the highest users (in the tail of the distribution) will have limited impact on efficiency. Bursts of attendance — and ways to shorten them — represent promising targets for managing demand. BioMed Central 2018-09-07 /pmc/articles/PMC6127924/ /pubmed/30189866 http://dx.doi.org/10.1186/s12916-018-1132-5 Text en © The Author(s). 2018 Open AccessThis 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
Burton, Christopher
Elliott, Alison
Cochran, Amanda
Love, Tom
Do healthcare services behave as complex systems? Analysis of patterns of attendance and implications for service delivery
title Do healthcare services behave as complex systems? Analysis of patterns of attendance and implications for service delivery
title_full Do healthcare services behave as complex systems? Analysis of patterns of attendance and implications for service delivery
title_fullStr Do healthcare services behave as complex systems? Analysis of patterns of attendance and implications for service delivery
title_full_unstemmed Do healthcare services behave as complex systems? Analysis of patterns of attendance and implications for service delivery
title_short Do healthcare services behave as complex systems? Analysis of patterns of attendance and implications for service delivery
title_sort do healthcare services behave as complex systems? analysis of patterns of attendance and implications for service delivery
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6127924/
https://www.ncbi.nlm.nih.gov/pubmed/30189866
http://dx.doi.org/10.1186/s12916-018-1132-5
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