Please use this identifier to cite or link to this item: https://doi.org/10.1136/bmjopen-2020-047330
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
Authors: Rattanavipapong, W
Wang, Y 
Butchon, R
Kittiratchakool, N
Thammatacharee, J
Teerawattananon, Y
Isaranuwatchai, W
Keywords: health economics
health policy
public health
statistics & research methods
Data Analysis
Delivery of Health Care
Hospitals
Humans
Inpatients
Male
Retrospective Studies
Thailand
Universal Health Care
Universal Health Insurance
Issue Date: 28-Jul-2021
Publisher: BMJ
Citation: Rattanavipapong, W, Wang, Y, Butchon, R, Kittiratchakool, N, Thammatacharee, J, Teerawattananon, Y, Isaranuwatchai, W (2021-07-28). Retrospective secondary data analysis to identify high-cost users in inpatient department of hospitals in Thailand, a middle-income country with universal healthcare coverage. BMJ Open 11 (7) : e047330-. ScholarBank@NUS Repository. https://doi.org/10.1136/bmjopen-2020-047330
Abstract: 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.
Source Title: BMJ Open
URI: https://scholarbank.nus.edu.sg/handle/10635/227817
ISSN: 2044-6055,2044-6055
DOI: 10.1136/bmjopen-2020-047330
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