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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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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. |
format | Online Article Text |
id | pubmed-10297773 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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