Trajectories of Long-Term Care Expenditure During the Last 5?Years of Life in Japan: A Nationwide Retrospective Cohort Study
Trajectories of Long-Term Care Expenditure During the Last 5?Years of Life in Japan: A Nationwide Retrospective Cohort Study
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日本过去 5 年的长期护理支出轨迹:一项全国范围的回顾性队列研究
DOI:
10.1016/j.jamda.2021.01.084
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发表时间:
2021
影响因子:
7.6
通讯作者:
Tamiya Nanako
中科院分区:
文献类型:
--
作者:
Jin Xueying;Abe Kazuhiro;Taniguchi Yuta;Watanabe Taeko;Miyawaki Atsushi;Tamiya Nanako
ObjectivesDespite the significant utilization of long-term care (LTC) services at the end of life, evidence on the trajectory of LTC expenditure in later life is scarce. This study aims to identify distinct trajectories of LTC expenditure in the last 5 years of life and to examine whether these trajectories differ according to cause of death.DesignA nationwide retrospective longitudinal cohort study based on linked data of National LTC Claims and the Japan's National Vital Statistic.Setting and ParticipantsParticipants comprised decedents aged 70 years or older and who died in 2017.MethodsWe assessed 5 years of monthly LTC expenditure among participants and applied group-based trajectory model to identify distinct trajectories of LTC expenditure. Subsequently multinominal logistic regression analysis was performed to investigate how these trajectories vary according to cause of death.ResultsAmong 1,124,335 decedents, 4 distinct trajectories of LTC expenditure were identified: persistently low (58.5%), late increase (9.8%), progressive increase then late decrease (8.8%), and persistently high (22.9%). Approximately 80.7% of total LTC expenditure was spent by the persistently high group. After adjustment for age and sex; deaths due to age-related physical debility and dementia were associated with persistently high LTC expenditure.Conclusions and ImplicationsOngoing discussions of LTC policy and reducing LTC expenditure may be more effective when emphasizing persistently high spenders. In addition, budget allocation for LTC at the end of life should be combined with data for health conditions.