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Healthcare access: A sequence-sensitive approach

It is widely accepted that healthcare-seeking behaviour is neither limited to nor terminated by access to one single healthcare provider. Yet the sequential conceptualisation of healthcare-seeking processes has not diffused into quantitative research, which continues to analyse healthcare access as...

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Detalles Bibliográficos
Autores principales: Haenssgen, Marco J., Ariana, Proochista
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5769022/
https://www.ncbi.nlm.nih.gov/pubmed/29349202
http://dx.doi.org/10.1016/j.ssmph.2016.11.008
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author Haenssgen, Marco J.
Ariana, Proochista
author_facet Haenssgen, Marco J.
Ariana, Proochista
author_sort Haenssgen, Marco J.
collection PubMed
description It is widely accepted that healthcare-seeking behaviour is neither limited to nor terminated by access to one single healthcare provider. Yet the sequential conceptualisation of healthcare-seeking processes has not diffused into quantitative research, which continues to analyse healthcare access as a “one-off” event. The ensuing lack of understanding healthcare behaviour is problematic in light of the immense burden of premature death especially in low- and middle-income countries. This paper presents an alternative approach. Based on a novel survey instrument, we analyse original survey data from rural India and China that contain 119 unique healthcare pathways among 637 respondents. We offer three applications of how such sequential data can be analysed to enhance our understanding of people's health behaviour. First, descriptive analysis of sequential data enables more a comprehensive representation of people's health behaviours, for example the time spent in various healthcare activities, common healthcare pathways across different groups, or shifts in healthcare provider access during a typical illness. Second, by analysing the effect of mobile technology on healthcare-seeking process characteristics, we demonstrate that conventional, sequence-insensitive indicators are potentially inconsistent and misleading approximations when compared to a more precise, sequence-sensitive measure. Third, we describe how sequential data enable transparent and flexible evaluations of people's healthcare behaviour. The example of a sequence-insensitive evaluation suggests that household wealth has no statistical link to an illustrative “ideal” form of public healthcare utilisation. In contrast, sequence-sensitive evaluations demonstrate that household wealth is associated with an increased likelihood of bypassing referral processes and approaching unregulated and costly informal and private practitioners before accessing a public clinic. Sequential data therefore do not only reveal otherwise neglected locational idiosyncrasies, but they also yield deeper insights into the drivers of people's health behaviours compared to a conventional approach to “access to healthcare.”
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spelling pubmed-57690222018-01-18 Healthcare access: A sequence-sensitive approach Haenssgen, Marco J. Ariana, Proochista SSM Popul Health Article It is widely accepted that healthcare-seeking behaviour is neither limited to nor terminated by access to one single healthcare provider. Yet the sequential conceptualisation of healthcare-seeking processes has not diffused into quantitative research, which continues to analyse healthcare access as a “one-off” event. The ensuing lack of understanding healthcare behaviour is problematic in light of the immense burden of premature death especially in low- and middle-income countries. This paper presents an alternative approach. Based on a novel survey instrument, we analyse original survey data from rural India and China that contain 119 unique healthcare pathways among 637 respondents. We offer three applications of how such sequential data can be analysed to enhance our understanding of people's health behaviour. First, descriptive analysis of sequential data enables more a comprehensive representation of people's health behaviours, for example the time spent in various healthcare activities, common healthcare pathways across different groups, or shifts in healthcare provider access during a typical illness. Second, by analysing the effect of mobile technology on healthcare-seeking process characteristics, we demonstrate that conventional, sequence-insensitive indicators are potentially inconsistent and misleading approximations when compared to a more precise, sequence-sensitive measure. Third, we describe how sequential data enable transparent and flexible evaluations of people's healthcare behaviour. The example of a sequence-insensitive evaluation suggests that household wealth has no statistical link to an illustrative “ideal” form of public healthcare utilisation. In contrast, sequence-sensitive evaluations demonstrate that household wealth is associated with an increased likelihood of bypassing referral processes and approaching unregulated and costly informal and private practitioners before accessing a public clinic. Sequential data therefore do not only reveal otherwise neglected locational idiosyncrasies, but they also yield deeper insights into the drivers of people's health behaviours compared to a conventional approach to “access to healthcare.” Elsevier 2016-11-30 /pmc/articles/PMC5769022/ /pubmed/29349202 http://dx.doi.org/10.1016/j.ssmph.2016.11.008 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Haenssgen, Marco J.
Ariana, Proochista
Healthcare access: A sequence-sensitive approach
title Healthcare access: A sequence-sensitive approach
title_full Healthcare access: A sequence-sensitive approach
title_fullStr Healthcare access: A sequence-sensitive approach
title_full_unstemmed Healthcare access: A sequence-sensitive approach
title_short Healthcare access: A sequence-sensitive approach
title_sort healthcare access: a sequence-sensitive approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5769022/
https://www.ncbi.nlm.nih.gov/pubmed/29349202
http://dx.doi.org/10.1016/j.ssmph.2016.11.008
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