High-cost users still came to hospitals during the COVID-19 pandemic during first wave data in Thailand: secondary data analysis

Abstract

Abstract Background The phenomenon of high-cost users (HCUs) in health care occurs when a small proportion of patients account for a large proportion of health care expenditures. By understanding this phenomenon during the COVID-19 pandemic, tailored interventions can be provided to ensure that patients receive the care they need and reduce the burden on the health system. Objectives This study aimed to determine (1) whether the HCUs phenomenon occurred during the pandemic in Thailand by exploring the pattern of inpatient health expenditures over time from 2016 to 2021; (2) the patient characteristics of HCUs; (3) the top 5 primary diagnoses of HCUs; and (4) the potential predictors associated with being an HCU. Methods The secondary data analysis was conducted via inpatient department (IPD) e-Claim data from the National Health Security Office for the Universal Coverage Scheme, which provides health care to ~ 80% of the Thai population. Health care expenditure over time was calculated, and the characteristics of the population were examined via descriptive analysis. Multinomial logistic regression was applied to explore the potential predictors associated with being an HCU. Results The characteristics of HCUs remained relatively the same from 2016 to 2021. In terms of the proportion of male (55%) to female patients (45%), the age ranged from 55 to 57 years, with an estimated 8-day length of hospital stay and 7 admissions per year, and the average health care cost per patient was ≥ USD 2,860 (100,000 THB). The low-cost users (LCUs) group (the bottom 50% of the population), had more female patients (55%), a younger age ranging from 27 to 33 years, a 3-day length of stay, 1‒2 admissions per year, and a lower average health care cost per patient, which was less than USD 315 (≤ 11,000 THB). Conclusion The HCUs phenomenon still existed even with limited health care accessibility or lockdown measures implemented during the COVID-19 pandemic. This finding could indicate the uniqueness of the need for health services by HCUs, which differ from those of other population groups. By understanding the trends of health care utilization and expenditure, along with potential predictors associated with being an HCU, policies can be introduced to ensure the appropriate allocation of health resources to the right people in need of the right care during future pandemics.

Keywords

• COVID-19
• Big Data
• High-Cost Users
• Thailand
• Health Expenditure
• Data Science