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System dynamics modelling of health workforce planning to address future challenges of Thailand’s Universal Health Coverage

BACKGROUND: System dynamics (SD) modelling can inform policy decisions under Thailand's Universal Health Coverage. We report on this thinking approach to Thailand's strategic health workforce planning for the next 20 years (2018–2037). METHODS: A series of group model building (GMB) sessio...

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Autores principales: Leerapan, Borwornsom, Teekasap, Pard, Urwannachotima, Nipaporn, Jaichuen, Wararat, Chiangchaisakulthai, Kwanpracha, Udomaksorn, Khunjira, Meeyai, Aronrag, Noree, Thinakorn, Sawaengdee, Krisada
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7943938/
https://www.ncbi.nlm.nih.gov/pubmed/33691723
http://dx.doi.org/10.1186/s12960-021-00572-5
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author Leerapan, Borwornsom
Teekasap, Pard
Urwannachotima, Nipaporn
Jaichuen, Wararat
Chiangchaisakulthai, Kwanpracha
Udomaksorn, Khunjira
Meeyai, Aronrag
Noree, Thinakorn
Sawaengdee, Krisada
author_facet Leerapan, Borwornsom
Teekasap, Pard
Urwannachotima, Nipaporn
Jaichuen, Wararat
Chiangchaisakulthai, Kwanpracha
Udomaksorn, Khunjira
Meeyai, Aronrag
Noree, Thinakorn
Sawaengdee, Krisada
author_sort Leerapan, Borwornsom
collection PubMed
description BACKGROUND: System dynamics (SD) modelling can inform policy decisions under Thailand's Universal Health Coverage. We report on this thinking approach to Thailand's strategic health workforce planning for the next 20 years (2018–2037). METHODS: A series of group model building (GMB) sessions involving 110 participants from multi-sectors of Thailand's health systems was conducted in 2017 and 2018. We facilitated policymakers, administrators, practitioners and other stakeholders to co-create a causal loop diagram (CLD) representing a shared understanding of why the health workforce's demands and supplies in Thailand were mismatched. A stock and flow diagram (SFD) was also co-created for testing the consequences of policy options by simulation modelling. RESULTS: The simulation modelling found hospital utilisation created a vicious cycle of constantly increasing demands for hospital care and a constant shortage of healthcare providers. Moreover, hospital care was not designed for effectively dealing with the future demands of ageing populations and prevalent chronic illness. Hence, shifting emphasis to professions that can provide primary care, intermediate care, long-term care, palliative care, and end-of-life care can be more effective. CONCLUSIONS: Our SD modelling confirmed that shifting the care models to address the changing health demands can be a high-leverage policy of health workforce planning, although very difficult to implement in the short term. of health workforce planning, although very difficult to implement in the short term.
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spelling pubmed-79439382021-03-10 System dynamics modelling of health workforce planning to address future challenges of Thailand’s Universal Health Coverage Leerapan, Borwornsom Teekasap, Pard Urwannachotima, Nipaporn Jaichuen, Wararat Chiangchaisakulthai, Kwanpracha Udomaksorn, Khunjira Meeyai, Aronrag Noree, Thinakorn Sawaengdee, Krisada Hum Resour Health Research BACKGROUND: System dynamics (SD) modelling can inform policy decisions under Thailand's Universal Health Coverage. We report on this thinking approach to Thailand's strategic health workforce planning for the next 20 years (2018–2037). METHODS: A series of group model building (GMB) sessions involving 110 participants from multi-sectors of Thailand's health systems was conducted in 2017 and 2018. We facilitated policymakers, administrators, practitioners and other stakeholders to co-create a causal loop diagram (CLD) representing a shared understanding of why the health workforce's demands and supplies in Thailand were mismatched. A stock and flow diagram (SFD) was also co-created for testing the consequences of policy options by simulation modelling. RESULTS: The simulation modelling found hospital utilisation created a vicious cycle of constantly increasing demands for hospital care and a constant shortage of healthcare providers. Moreover, hospital care was not designed for effectively dealing with the future demands of ageing populations and prevalent chronic illness. Hence, shifting emphasis to professions that can provide primary care, intermediate care, long-term care, palliative care, and end-of-life care can be more effective. CONCLUSIONS: Our SD modelling confirmed that shifting the care models to address the changing health demands can be a high-leverage policy of health workforce planning, although very difficult to implement in the short term. of health workforce planning, although very difficult to implement in the short term. BioMed Central 2021-03-10 /pmc/articles/PMC7943938/ /pubmed/33691723 http://dx.doi.org/10.1186/s12960-021-00572-5 Text en © The Author(s) 2021 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/. The Creative Commons Public Domain Dedication waiver (http://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
Leerapan, Borwornsom
Teekasap, Pard
Urwannachotima, Nipaporn
Jaichuen, Wararat
Chiangchaisakulthai, Kwanpracha
Udomaksorn, Khunjira
Meeyai, Aronrag
Noree, Thinakorn
Sawaengdee, Krisada
System dynamics modelling of health workforce planning to address future challenges of Thailand’s Universal Health Coverage
title System dynamics modelling of health workforce planning to address future challenges of Thailand’s Universal Health Coverage
title_full System dynamics modelling of health workforce planning to address future challenges of Thailand’s Universal Health Coverage
title_fullStr System dynamics modelling of health workforce planning to address future challenges of Thailand’s Universal Health Coverage
title_full_unstemmed System dynamics modelling of health workforce planning to address future challenges of Thailand’s Universal Health Coverage
title_short System dynamics modelling of health workforce planning to address future challenges of Thailand’s Universal Health Coverage
title_sort system dynamics modelling of health workforce planning to address future challenges of thailand’s universal health coverage
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7943938/
https://www.ncbi.nlm.nih.gov/pubmed/33691723
http://dx.doi.org/10.1186/s12960-021-00572-5
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