ArticleBMJ open2021
Retrospective secondary data analysis to identify high-cost users in inpatient department of hospitals in Thailand, a middle-income country with universal healthcare coverage.
Article in BMJ open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Obesity, Physical Activity and Occurrence of High Medical Expenditures at One-Year Follow-Up Among Japanese Beneficiaries of Employment-Based Health Insurances: An Analysis Based on a Nationwide Health Checkup Questionnaire.Healthcare (Basel, Switzerland) · 2026Article
- Treatment costs and determinants in PMBMC public health · 2026Article
- High-cost users still came to hospitals during the COVID-19 pandemic during first wave data in Thailand: secondary data analysis.BMC public health · 2024Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe 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
settingA 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).
participantsStudy participants included Thai citizens who had at least one inpatient admission to hospitals under the UCS over the study period.
resultsOver 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.
conclusionsThis 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.