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重新审视临近死亡与医疗保健支出增加的关系:对老年人的15年面板分析

Proximity to death and health care expenditure increase revisited: A 15-year panel analysis of elderly persons.

作者信息

von Wyl Viktor

机构信息

Epidemiology, Biostatistics & Prevention Institute, University of Zurich, Hirschengraben, 84, CH-8001, Zurich, Switzerland.

出版信息

Health Econ Rev. 2019 Mar 11;9(1):9. doi: 10.1186/s13561-019-0224-z.

DOI:10.1186/s13561-019-0224-z
PMID:30859485
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6734245/
Abstract

BACKGROUND

Health care expenditures (HCE) are known to steepen with increasing age, but the contributions of biological age, morbidity, or proximity to death as cost drivers are debated. Age-associated HCE growth can be studied across two dimensions: within fixed groups of persons with the same birth year followed over time (birth cohort), or the same age classes (e.g. 66 to 70 year olds) at different time points (age-class analysis). Using health insurance claims data including morbidity and mortality information, HCE growth was analyzed in Swiss mandatory health insurance for the years 1996 to 2011 and compared across the two age dimensions.

RESULTS

Deflated HCE were analyzed for 104,000 persons from three birth cohorts (1921-25, 1926-30, 1931-35). Two-part regression models were adjusted for proximity-to-death (death within same or next calendar year) and morbidity indicators (hospitalization, high drug expenditures, and pharmaceutical cost groups from 2006 onwards). When analyzing HCE growth within birth cohorts, controlling for survival and morbidity status decreased age-associated HCE estimates by 31% to 51% compared to crude age averages. The total HCE volume share of decedents rose from 19% to 31% in the 1931-35 birth cohort and from 28% to 51% for the 1921-25 birth cohort. The analysis of same age classes (e.g. 71-75 year olds) over different years revealed no HCE growth (steepening) in excess of deflation for groups aged 75 years or less, and only moderate HCE growth for those ≥76 years. For the 76+ age classes, the population fraction of decedents decreased by -3% (age 76-80) and -15% (age 81-85) over time, whilst the total HCE volume share of decedent-associated HCE increased by +16% and +9%, with an HCE growth of +3.2% and +2.5% per year.

CONCLUSIONS

HCE growth was dominated by end-of-life HCE, but residual age-associated HCE growth remained pertinent, the extent of which however depended on morbidity indicator definitions. A better understanding of shifts in chronic disease prevalence with rising age, as well as associated HCE and survival impacts of treatment will be key for further refining future HCE projections.

摘要

背景

众所周知,医疗保健支出(HCE)会随着年龄增长而急剧增加,但生物年龄、发病率或临近死亡作为成本驱动因素的作用仍存在争议。与年龄相关的HCE增长可以从两个维度进行研究:在同一出生年份的固定人群组中随时间追踪(出生队列),或者在不同时间点的同一年龄组(如66至70岁)(年龄组分析)。利用包含发病率和死亡率信息的健康保险理赔数据,对1996年至2011年瑞士强制性健康保险中的HCE增长进行了分析,并在两个年龄维度上进行了比较。

结果

对来自三个出生队列(1921 - 25、1926 - 30、1931 - 35)的104,000人进行了经通胀调整后的HCE分析。采用两部分回归模型,对临近死亡情况(同一年或次年死亡)和发病率指标(住院、高药物支出以及2006年起的药品成本组)进行了调整。在分析出生队列中的HCE增长时,与粗年龄平均值相比,控制生存和发病状况后,与年龄相关的HCE估计值降低了31%至51%。在1931 - 35出生队列中,死者的HCE总量占比从19%升至31%,在1921 - 25出生队列中从28%升至51%。对不同年份的同一年龄组(如71 - 75岁)进行分析发现,75岁及以下组的HCE增长(加剧)未超过通胀调整幅度;76岁及以上组的HCE增长较为适度。对于76岁及以上年龄组,随着时间推移,死者的人口占比下降了-3%(76 - 80岁)和-15%(81 - 85岁),而与死者相关的HCE总量占比分别增加了+16%和+9%,每年的HCE增长率分别为+3.2%和+2.5%。

结论

HCE增长主要由临终HCE主导,但与年龄相关的残余HCE增长仍然显著,其程度取决于发病率指标的定义。更好地理解随着年龄增长慢性病患病率的变化,以及治疗对HCE和生存的相关影响,将是进一步完善未来HCE预测的关键。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29e1/6734245/d5a1f9f449d7/13561_2019_224_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29e1/6734245/3d218190c26b/13561_2019_224_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29e1/6734245/f99e05f0595d/13561_2019_224_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29e1/6734245/e0d848009ec9/13561_2019_224_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29e1/6734245/58b5ffff0127/13561_2019_224_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29e1/6734245/37d176b99bbc/13561_2019_224_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29e1/6734245/d5a1f9f449d7/13561_2019_224_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29e1/6734245/3d218190c26b/13561_2019_224_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29e1/6734245/f99e05f0595d/13561_2019_224_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29e1/6734245/e0d848009ec9/13561_2019_224_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29e1/6734245/58b5ffff0127/13561_2019_224_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29e1/6734245/37d176b99bbc/13561_2019_224_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29e1/6734245/d5a1f9f449d7/13561_2019_224_Fig6_HTML.jpg

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