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Using discrete choice model to elicit preference for health-care priority setting
BACKGROUND: Regarding lack of resources in the health-care sector, prioritization of these resources is inevitable. The objective of the current study was to elicit public preference in prioritizing and allocating health resources using a discrete choice experiment technique, which is currently the...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer - Medknow
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6615128/ https://www.ncbi.nlm.nih.gov/pubmed/31334269 http://dx.doi.org/10.4103/jehp.jehp_404_18 |
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author | Jouyani, Yaser Hadiyan, Mohammad Salehi, Masoud Souri, Ali |
author_facet | Jouyani, Yaser Hadiyan, Mohammad Salehi, Masoud Souri, Ali |
author_sort | Jouyani, Yaser |
collection | PubMed |
description | BACKGROUND: Regarding lack of resources in the health-care sector, prioritization of these resources is inevitable. The objective of the current study was to elicit public preference in prioritizing and allocating health resources using a discrete choice experiment technique, which is currently the most commonly applied method in this field of researches. METHODS: In this discrete choice study, five attributes were selected through interview with 25 health experts to elicit people preferences in Tehran (Iran) in 2017. Eighteen choice tasks were arranged within 3 blocks, and this would be achieved with a sample size of 579. Choice data were modeled using generalized estimating equation method and STATA 14 software. RESULTS: Five attributes including level of emergency, severity of disease, communicable, benefit from treatment, and age are the most important attributes in the prioritizing health resources from the expert's point of view. As well as among these attributes, communicable (odds ratio = 2.81) is the most important attributes from the public's point of view. CONCLUSION: The results of this study could be very useful for prioritizing resources which is one of the most challenging measurements of the health system. By identifying the importance of each patient's characteristic, patients can be categorized in groups with different priorities, as well as the diagnosis-related group system, based on which resources are allocated. |
format | Online Article Text |
id | pubmed-6615128 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Wolters Kluwer - Medknow |
record_format | MEDLINE/PubMed |
spelling | pubmed-66151282019-07-22 Using discrete choice model to elicit preference for health-care priority setting Jouyani, Yaser Hadiyan, Mohammad Salehi, Masoud Souri, Ali J Educ Health Promot Original Article BACKGROUND: Regarding lack of resources in the health-care sector, prioritization of these resources is inevitable. The objective of the current study was to elicit public preference in prioritizing and allocating health resources using a discrete choice experiment technique, which is currently the most commonly applied method in this field of researches. METHODS: In this discrete choice study, five attributes were selected through interview with 25 health experts to elicit people preferences in Tehran (Iran) in 2017. Eighteen choice tasks were arranged within 3 blocks, and this would be achieved with a sample size of 579. Choice data were modeled using generalized estimating equation method and STATA 14 software. RESULTS: Five attributes including level of emergency, severity of disease, communicable, benefit from treatment, and age are the most important attributes in the prioritizing health resources from the expert's point of view. As well as among these attributes, communicable (odds ratio = 2.81) is the most important attributes from the public's point of view. CONCLUSION: The results of this study could be very useful for prioritizing resources which is one of the most challenging measurements of the health system. By identifying the importance of each patient's characteristic, patients can be categorized in groups with different priorities, as well as the diagnosis-related group system, based on which resources are allocated. Wolters Kluwer - Medknow 2019-06-27 /pmc/articles/PMC6615128/ /pubmed/31334269 http://dx.doi.org/10.4103/jehp.jehp_404_18 Text en Copyright: © 2019 Journal of Education and Health Promotion http://creativecommons.org/licenses/by-nc-sa/4.0 This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms. |
spellingShingle | Original Article Jouyani, Yaser Hadiyan, Mohammad Salehi, Masoud Souri, Ali Using discrete choice model to elicit preference for health-care priority setting |
title | Using discrete choice model to elicit preference for health-care priority setting |
title_full | Using discrete choice model to elicit preference for health-care priority setting |
title_fullStr | Using discrete choice model to elicit preference for health-care priority setting |
title_full_unstemmed | Using discrete choice model to elicit preference for health-care priority setting |
title_short | Using discrete choice model to elicit preference for health-care priority setting |
title_sort | using discrete choice model to elicit preference for health-care priority setting |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6615128/ https://www.ncbi.nlm.nih.gov/pubmed/31334269 http://dx.doi.org/10.4103/jehp.jehp_404_18 |
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