Center for Population Health and Aging, Duke University, Durham, North Carolina 27708, USA.
J Am Geriatr Soc. 2012 Feb;60(2):323-7. doi: 10.1111/j.1532-5415.2011.03786.x. Epub 2012 Jan 27.
To use the Medicare Files of Service Use (MFSU) to evaluate patterns in the incidence of aging-related diseases in the U.S. elderly population.
Age-specific incidence rates of 19 aging-related diseases were evaluated using the National Long Term Care Survey (NLTCS) and the Surveillance, Epidemiology, and End Results (SEER) Registry data, both linked to MFSU (NLTCS-M and SEER-M, respectively), using an algorithm developed for individual date at onset evaluation.
A random sample from the entire U.S. elderly population (Medicare beneficiaries) was used in NLTCS, and the SEER Registry data covers 26% of the U.S. population.
Thirty-four thousand seventy-seven individuals from NLTCS-M and 2,154,598 from SEER-M.
Individual medical histories were reconstructed using information on diagnoses coded in MFSU, dates of medical services and procedures, and Medicare enrollment and disenrollment.
The majority of diseases (e.g., prostate cancer, asthma, and diabetes mellitus) had a monotonic decline (or decline after a short period of increase) in incidence with age. A monotonic increase in incidence with age with a subsequent leveling off and decline was observed for myocardial infarction, stroke, heart failure, ulcer, and Alzheimer's disease. An inverted U-shaped age pattern was detected for lung and colon carcinomas, Parkinson's disease, and renal failure. The results obtained from the NLTCS-M and SEER-M were in agreement (excluding an excess for circulatory diseases in the NLTCS-M). A sensitivity analysis proved the stability of the incidence rates evaluated.
The developed computational approaches applied to the nationally representative Medicare-based data sets allow reconstruction of age patterns of disease incidence in the U.S. elderly population at the national level with unprecedented statistical accuracy and stability with respect to systematic biases.
利用医疗保险服务使用档案（MFSU）评估美国老年人群中与年龄相关疾病的发病模式。
使用国家长期护理调查（NLTCS）和监测、流行病学和最终结果（SEER）登记处的数据，通过专门为个体发病日期评估开发的算法，在 MFSU 中评估 19 种与年龄相关疾病的特定年龄发病率（NLTCS-M 和 SEER-M 分别）。
NLTCS 中使用了来自整个美国老年人群（医疗保险受益人）的随机样本，SEER 登记处的数据覆盖了美国 26%的人口。
NLTCS-M 中的 34077 人和 SEER-M 中的 2154598 人。
使用 MFSU 中编码的诊断、医疗服务和程序的日期、医疗保险登记和退保日期等信息重建个人病史。
大多数疾病（例如前列腺癌、哮喘和糖尿病）的发病率随年龄呈单调下降（或在短暂增加后下降）。心肌梗死、中风、心力衰竭、溃疡和阿尔茨海默病的发病率随年龄呈单调增加，随后趋于平稳并下降。肺癌和结肠癌、帕金森病和肾衰竭的发病率呈倒 U 型年龄模式。从 NLTCS-M 和 SEER-M 中获得的结果是一致的（排除了 NLTCS-M 中循环系统疾病的过度）。敏感性分析证明了评估发病率的稳定性。
应用于基于全国代表性医疗保险的数据集的开发计算方法允许以前所未有的统计准确性和对系统偏差的稳定性，在全国范围内重建美国老年人群中疾病发病率的年龄模式。
