Methodological Development of a Health Forcasting Model

健康预测模型的方法开发

• 批准号: 6453003
• 负责人: Kenneth G. Manton
• 金额: $ 14.57万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-05-15 至 2002-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6453003
• 关键词: Medicare /Medicaid; behavioral /social science research tag; chronic disease /disorder; health; health care service utilization; health economics; health services research tag; health surveys; human data; human mortality; human old age (65+); human population dynamics; longitudinal human study; mathematical model; model design /development; statistics /biometry

Declines have been documented in the functional status and mortality of the U.S. elderly population in the 1982 to 1994 National Long Term Care Surveys (NLTCS). These are likely due to a mix of demographic socio- economic, and biotechnical changes occurring in the U.S. over time and in different birth cohorts. Important among these are increased understanding of how aging and chronic disease operate in elderly cohorts, and over time, due both to different early life experiences, and health care access over time, and to advances in biomedical technology and the ability to treat chronic diseases at later stages than previously possible. Such changes are, in part, stimulated by basic research showing physical changes associated with aging are more "plastic" than previously thought. In the proposed research we will model changes in the mortality and the health of the U.S. elderly population as a function of health trends, and advances in biomedical technology and research, as mediated through Medicare which pays for most health services used by U.S. elderly beneficiaries. This will require methodological innovations in population based multivariate models describing the effects of disease dependency, and in assessing cost consequences of diseases in the current and future U.S. elderly populations. Maximum likelihood procedures will be used to combine demographic, social, economic, actuarial, and health survey data to estimate parameters of stochastic population processes. The data used includes the longitudinally linked NLTCS of the U.S. population aged 65+, linked to Medicare mortality and service use records. Ancillary data sources on age specific population disease incidence and prevalence will also be used as well as data on the likely effects of new treatments on the U.S. elderly population. Several other surveys will be used to improve specific expenditure estimates (e.g., three National Nursing Home Surveys (1977-1996), two National Health Expenditure Panels (1987, 1996), and Medicare administrative data.

在1982年至1994年，美国老年人口的功能状况和死亡率已记录下来，国家长期护理调查（NLTC）。这些可能是由于人口社会经济的混合，以及随着时间的推移和不同的出生人群的生物技术变化。其中重要的是，人们对老年人群的衰老和慢性疾病的运作越来越多，并且随着时间的流逝以及随着时间的流逝以及生物医学技术的进步以及在后期阶段治疗慢性病的能力。基础研究表明，与衰老相关的物理变化比以前想象的更“塑性”。在拟议的研究中，我们将对美国老年人口的死亡率和健康状况的变化对健康趋势的函数进行建模，以及生物医学技术和研究的进步，这是通过Medicare介导的，这支付了美国老年受益人使用的大多数卫生服务。这将需要在基于人群的多元模型中进行方法论创新，以描述疾病依赖性的影响，并评估当前和未来的美国老年人群中疾病的成本后果。最大似然程序将用于将人口，社会，经济，精算和健康调查数据结合起来，以估计随机人口过程的参数。所使用的数据包括65岁以上的美国人口的纵向NLTC，与Medicare死亡率和服务使用记录有关。还将使用有关年龄特定人群疾病发病率和患病率的辅助数据来源，以及有关新疗法对美国老年人群的可能影响的数据。其他几项调查将用于改善特定的支出估计（例如，三项国家疗养院调查（1977-1996），两个国家卫生支出小组（1987，1996）和Medicare行政数据。