Health Policy Manag.  2023 Sep;33(3):295-310. 10.4332/KJHPA.2023.33.3.295.

The Effect of Long-Term Care Ratings and Benefit Utilization Characteristics on Healthcare Use

• Son KJ
• Oh SJ
• Yoon JM

• KMID: 2549115
• DOI: http://doi.org/10.4332/KJHPA.2023.33.3.295

Abstract

Background
The long-term care (LTC) group has higher rates of chronic disease and disability registration compared to the general older people population. There is a need to provide integrated medical services and care for LTC group. Consequently, this study aimed to identify medical usage patterns based on the ratings of LTC and the characteristics of benefits usage in the LTC group.
Methods
This study employed the National Health Insurance Service Database to analyze the effects of demographic and LTC-related characteristics on medical usage from 2015 to 2019 using a repeated measures analysis. A longitudinal logit model was applied to binary data, while a linear mixed model was utilized for continuous data.
Results
In the case of LTC ratings, a positive correlation was observed with overall medical usage. In terms of LTC benefit usage characteristics, a higher overall level of medical usage was found in the group using home care benefits. Detailed analysis by medical institution classification revealed a maintained correlation between care ratings and the volume of medical usage. However, medical usage by classification varied based on the characteristics of LTC benefit usage.
Conclusion
This study identified a complex interaction between LTC characteristics and medical usage. Predicting the requisite medical services based on the LTC rating presented a challenge. Consequently, it becomes essential for the LTC group to continuously monitor medical and care needs, even after admission into the LTC system. To facilitate this, it is crucial to devise an LTC rating system that accurately reflects medical needs and to broaden the implementation of integrated medical-care policies.

Keyword

Long-term care; Medical service; Medical usage; Repeated measures analysis; Longitudinal logit model; Linear mixed model; Medical institution classification