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Factors associated with patients’ mobility rates within the provinces of Iran

BACKGROUND: The absence of a referral system and patients’ freedom to choose among service providers in Iran have led to increased patient mobility, which continues to concern health policymakers in the country. This study aimed to determine factors associated with patient mobility rates within the...

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Autores principales: Hekmat, Somayeh Noori, Haghdoost, Ali Akbar, Zamaninasab, Zahra, Rahimisadegh, Rohaneh, Dehnavieh, Fatemeh, Emadi, Samira
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9764717/
https://www.ncbi.nlm.nih.gov/pubmed/36539751
http://dx.doi.org/10.1186/s12913-022-08972-6
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author Hekmat, Somayeh Noori
Haghdoost, Ali Akbar
Zamaninasab, Zahra
Rahimisadegh, Rohaneh
Dehnavieh, Fatemeh
Emadi, Samira
author_facet Hekmat, Somayeh Noori
Haghdoost, Ali Akbar
Zamaninasab, Zahra
Rahimisadegh, Rohaneh
Dehnavieh, Fatemeh
Emadi, Samira
author_sort Hekmat, Somayeh Noori
collection PubMed
description BACKGROUND: The absence of a referral system and patients’ freedom to choose among service providers in Iran have led to increased patient mobility, which continues to concern health policymakers in the country. This study aimed to determine factors associated with patient mobility rates within the provinces of Iran. METHODS: This cross-sectional study was conducted in Iran. Data on the place of residence of patients admitted to Iranian public hospitals were collected during August 2017 to determine the status of patient mobility within each province. The sample size were 537,786 patients were hospitalized in public hospitals in Iran during August 2017. The patient mobility ratio was calculated for each of Iran’s provinces by producing a patient mobility matrix. Then, a model of factors affecting patient mobility was identified by regression analysis. All the analyses were performed using STATA14 software. RESULTS: In the study period, 585,681 patients were admitted to public hospitals in Iran, of which 69,692 patients were referred to the hospital from another city and 51,789 of them were admitted to public hospitals in the capital of the province. The highest levels of intra-provincial patient mobility were attributed to southern and eastern provinces, and the lowest levels were observed in the north and west of Iran. Implementation of negative binomial regression indicated that, among the examined parameters, the distribution of specialist physicians and the human development index had the highest impact on intra-provincial patient mobility. CONCLUSION: The distribution of specialists throughout different country areas plays a determining role in patient mobility. In many cases, redistributing hospital beds is impossible, but adopting different human resource policies could prevent unnecessary patient mobility through equitable redistribution of specialists among different cities. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-022-08972-6.
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spelling pubmed-97647172022-12-21 Factors associated with patients’ mobility rates within the provinces of Iran Hekmat, Somayeh Noori Haghdoost, Ali Akbar Zamaninasab, Zahra Rahimisadegh, Rohaneh Dehnavieh, Fatemeh Emadi, Samira BMC Health Serv Res Research BACKGROUND: The absence of a referral system and patients’ freedom to choose among service providers in Iran have led to increased patient mobility, which continues to concern health policymakers in the country. This study aimed to determine factors associated with patient mobility rates within the provinces of Iran. METHODS: This cross-sectional study was conducted in Iran. Data on the place of residence of patients admitted to Iranian public hospitals were collected during August 2017 to determine the status of patient mobility within each province. The sample size were 537,786 patients were hospitalized in public hospitals in Iran during August 2017. The patient mobility ratio was calculated for each of Iran’s provinces by producing a patient mobility matrix. Then, a model of factors affecting patient mobility was identified by regression analysis. All the analyses were performed using STATA14 software. RESULTS: In the study period, 585,681 patients were admitted to public hospitals in Iran, of which 69,692 patients were referred to the hospital from another city and 51,789 of them were admitted to public hospitals in the capital of the province. The highest levels of intra-provincial patient mobility were attributed to southern and eastern provinces, and the lowest levels were observed in the north and west of Iran. Implementation of negative binomial regression indicated that, among the examined parameters, the distribution of specialist physicians and the human development index had the highest impact on intra-provincial patient mobility. CONCLUSION: The distribution of specialists throughout different country areas plays a determining role in patient mobility. In many cases, redistributing hospital beds is impossible, but adopting different human resource policies could prevent unnecessary patient mobility through equitable redistribution of specialists among different cities. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-022-08972-6. BioMed Central 2022-12-20 /pmc/articles/PMC9764717/ /pubmed/36539751 http://dx.doi.org/10.1186/s12913-022-08972-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Hekmat, Somayeh Noori
Haghdoost, Ali Akbar
Zamaninasab, Zahra
Rahimisadegh, Rohaneh
Dehnavieh, Fatemeh
Emadi, Samira
Factors associated with patients’ mobility rates within the provinces of Iran
title Factors associated with patients’ mobility rates within the provinces of Iran
title_full Factors associated with patients’ mobility rates within the provinces of Iran
title_fullStr Factors associated with patients’ mobility rates within the provinces of Iran
title_full_unstemmed Factors associated with patients’ mobility rates within the provinces of Iran
title_short Factors associated with patients’ mobility rates within the provinces of Iran
title_sort factors associated with patients’ mobility rates within the provinces of iran
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9764717/
https://www.ncbi.nlm.nih.gov/pubmed/36539751
http://dx.doi.org/10.1186/s12913-022-08972-6
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