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Comparing apples to oranges? Minimizing typological biases to better classify healthcare systems globally

The present study explores the role of typologies as an analytical device in understanding both the theoretical and empirical manifestations of healthcare systems globally. In a first step, we explore the relative benefits and limits of different classificatory logics – inductive vs. deductive – bef...

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Autores principales: Frisina Doetter, Lorraine, Schmid, Achim, de Carvalho, Gabriela, Rothgang, Heinz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10297773/
https://www.ncbi.nlm.nih.gov/pubmed/37383508
http://dx.doi.org/10.1016/j.hpopen.2021.100035
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author Frisina Doetter, Lorraine
Schmid, Achim
de Carvalho, Gabriela
Rothgang, Heinz
author_facet Frisina Doetter, Lorraine
Schmid, Achim
de Carvalho, Gabriela
Rothgang, Heinz
author_sort Frisina Doetter, Lorraine
collection PubMed
description The present study explores the role of typologies as an analytical device in understanding both the theoretical and empirical manifestations of healthcare systems globally. In a first step, we explore the relative benefits and limits of different classificatory logics – inductive vs. deductive – before conducting a review of scholarship on healthcare system classifications. We argue that, in order to capture the role of global actors (international organizations, donor countries etc.) in low-to-upper-middle income economies, classificatory systems must account for potential territorial shifts across the dimensions of financing, service provision and regulation defining all healthcare systems. In its absence, comparative research involving countries of significantly different levels of economic development becomes obfuscated. In an effort to redress this gap in the literature, we lay out how state, societal, market and global actors feature across different dimensions of healthcare systems, putting forth a deductively derived and actor-centered typology.
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spelling pubmed-102977732023-06-28 Comparing apples to oranges? Minimizing typological biases to better classify healthcare systems globally Frisina Doetter, Lorraine Schmid, Achim de Carvalho, Gabriela Rothgang, Heinz Health Policy Open Original Article The present study explores the role of typologies as an analytical device in understanding both the theoretical and empirical manifestations of healthcare systems globally. In a first step, we explore the relative benefits and limits of different classificatory logics – inductive vs. deductive – before conducting a review of scholarship on healthcare system classifications. We argue that, in order to capture the role of global actors (international organizations, donor countries etc.) in low-to-upper-middle income economies, classificatory systems must account for potential territorial shifts across the dimensions of financing, service provision and regulation defining all healthcare systems. In its absence, comparative research involving countries of significantly different levels of economic development becomes obfuscated. In an effort to redress this gap in the literature, we lay out how state, societal, market and global actors feature across different dimensions of healthcare systems, putting forth a deductively derived and actor-centered typology. Elsevier 2021-02-11 /pmc/articles/PMC10297773/ /pubmed/37383508 http://dx.doi.org/10.1016/j.hpopen.2021.100035 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Article
Frisina Doetter, Lorraine
Schmid, Achim
de Carvalho, Gabriela
Rothgang, Heinz
Comparing apples to oranges? Minimizing typological biases to better classify healthcare systems globally
title Comparing apples to oranges? Minimizing typological biases to better classify healthcare systems globally
title_full Comparing apples to oranges? Minimizing typological biases to better classify healthcare systems globally
title_fullStr Comparing apples to oranges? Minimizing typological biases to better classify healthcare systems globally
title_full_unstemmed Comparing apples to oranges? Minimizing typological biases to better classify healthcare systems globally
title_short Comparing apples to oranges? Minimizing typological biases to better classify healthcare systems globally
title_sort comparing apples to oranges? minimizing typological biases to better classify healthcare systems globally
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10297773/
https://www.ncbi.nlm.nih.gov/pubmed/37383508
http://dx.doi.org/10.1016/j.hpopen.2021.100035
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