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Retrospective secondary data analysis to identify high-cost users in inpatient department of hospitals in Thailand, a middle-income country with universal healthcare coverage

OBJECTIVES: The study aims to identify high-cost users (HCUs) in the inpatient departments of hospitals in Thailand including their common characteristics, patterns of healthcare utilisation and expenditure compared with low-cost users, and to explore potential factors associated with HCUs so the he...

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Autores principales: Rattanavipapong, Waranya, Wang, Yi, Butchon, Rukmanee, Kittiratchakool, Nitichen, Thammatacharee, Jadej, Teerawattananon, Yot, Isaranuwatchai, Wanrudee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8319992/
https://www.ncbi.nlm.nih.gov/pubmed/34321299
http://dx.doi.org/10.1136/bmjopen-2020-047330
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author Rattanavipapong, Waranya
Wang, Yi
Butchon, Rukmanee
Kittiratchakool, Nitichen
Thammatacharee, Jadej
Teerawattananon, Yot
Isaranuwatchai, Wanrudee
author_facet Rattanavipapong, Waranya
Wang, Yi
Butchon, Rukmanee
Kittiratchakool, Nitichen
Thammatacharee, Jadej
Teerawattananon, Yot
Isaranuwatchai, Wanrudee
author_sort Rattanavipapong, Waranya
collection PubMed
description OBJECTIVES: The study aims to identify high-cost users (HCUs) in the inpatient departments of hospitals in Thailand including their common characteristics, patterns of healthcare utilisation and expenditure compared with low-cost users, and to explore potential factors associated with HCUs so the healthcare system can be prepared to support the HCUs including those who have increased chances of becoming HCUs. DESIGN AND SETTING: A retrospective secondary data analysis using hospitalisation data from Thailand’s Universal Coverage Scheme (UCS) obtained from the National Health Security Office over a 5-year period from October 2014 to September 2019 (fiscal year 2014–2018). PARTICIPANTS: Study participants included Thai citizens who had at least one inpatient admission to hospitals under the UCS over the study period. RESULTS: Over the 5-year period, the top 5% of the hospitalised population (or HCUs) consumed almost 50% of the health expenditure each year. HCUs were more likely to have longer hospital stays, a higher annual number of visits and be admitted to multiple hospitals each year when compared with the low-cost users (the bottom 50% of the hospitalised population). The study further reported that the chance of becoming an HCU is associated with several factors such as increasing age, being male, having a comorbidity and being admitted to hospitals in Bangkok. CONCLUSIONS: This study confirmed that the HCU phenomenon existed in Thailand, where a majority of inpatient care spending is concentrated in the top 5% of the hospitalised population. The study findings call attention to potential initiatives that can help monitor the magnitude and trend of HCUs and develop policies to prevent HCUs.
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spelling pubmed-83199922021-08-02 Retrospective secondary data analysis to identify high-cost users in inpatient department of hospitals in Thailand, a middle-income country with universal healthcare coverage Rattanavipapong, Waranya Wang, Yi Butchon, Rukmanee Kittiratchakool, Nitichen Thammatacharee, Jadej Teerawattananon, Yot Isaranuwatchai, Wanrudee BMJ Open Health Policy OBJECTIVES: The study aims to identify high-cost users (HCUs) in the inpatient departments of hospitals in Thailand including their common characteristics, patterns of healthcare utilisation and expenditure compared with low-cost users, and to explore potential factors associated with HCUs so the healthcare system can be prepared to support the HCUs including those who have increased chances of becoming HCUs. DESIGN AND SETTING: A retrospective secondary data analysis using hospitalisation data from Thailand’s Universal Coverage Scheme (UCS) obtained from the National Health Security Office over a 5-year period from October 2014 to September 2019 (fiscal year 2014–2018). PARTICIPANTS: Study participants included Thai citizens who had at least one inpatient admission to hospitals under the UCS over the study period. RESULTS: Over the 5-year period, the top 5% of the hospitalised population (or HCUs) consumed almost 50% of the health expenditure each year. HCUs were more likely to have longer hospital stays, a higher annual number of visits and be admitted to multiple hospitals each year when compared with the low-cost users (the bottom 50% of the hospitalised population). The study further reported that the chance of becoming an HCU is associated with several factors such as increasing age, being male, having a comorbidity and being admitted to hospitals in Bangkok. CONCLUSIONS: This study confirmed that the HCU phenomenon existed in Thailand, where a majority of inpatient care spending is concentrated in the top 5% of the hospitalised population. The study findings call attention to potential initiatives that can help monitor the magnitude and trend of HCUs and develop policies to prevent HCUs. BMJ Publishing Group 2021-07-27 /pmc/articles/PMC8319992/ /pubmed/34321299 http://dx.doi.org/10.1136/bmjopen-2020-047330 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
spellingShingle Health Policy
Rattanavipapong, Waranya
Wang, Yi
Butchon, Rukmanee
Kittiratchakool, Nitichen
Thammatacharee, Jadej
Teerawattananon, Yot
Isaranuwatchai, Wanrudee
Retrospective secondary data analysis to identify high-cost users in inpatient department of hospitals in Thailand, a middle-income country with universal healthcare coverage
title Retrospective secondary data analysis to identify high-cost users in inpatient department of hospitals in Thailand, a middle-income country with universal healthcare coverage
title_full Retrospective secondary data analysis to identify high-cost users in inpatient department of hospitals in Thailand, a middle-income country with universal healthcare coverage
title_fullStr Retrospective secondary data analysis to identify high-cost users in inpatient department of hospitals in Thailand, a middle-income country with universal healthcare coverage
title_full_unstemmed Retrospective secondary data analysis to identify high-cost users in inpatient department of hospitals in Thailand, a middle-income country with universal healthcare coverage
title_short Retrospective secondary data analysis to identify high-cost users in inpatient department of hospitals in Thailand, a middle-income country with universal healthcare coverage
title_sort retrospective secondary data analysis to identify high-cost users in inpatient department of hospitals in thailand, a middle-income country with universal healthcare coverage
topic Health Policy
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8319992/
https://www.ncbi.nlm.nih.gov/pubmed/34321299
http://dx.doi.org/10.1136/bmjopen-2020-047330
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