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NURSING HOME POLICY VIA HIERARCHICAL DURATION MODELS

通过分层持续时间模型制定疗养院政策

基本信息

批准号：
2236011
负责人：
CARL N MORRIS
金额：
$ 13.22万
依托单位：
HARVARD MEDICAL SCHOOL
依托单位国家：
美国
项目类别：
财政年份：
1992
资助国家：
美国
起止时间：
1992-07-01 至 1995-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/2236011
关键词：
health care cost /financing health care service utilization mathematical model mental health model design /development nursing homes statistics /biometry

项目摘要

The project objective is to develop statistical methods to estimate duration (survival) models, and to apply these methods to nursing home and mental health duration data. In spite of increasing interest in nursing home utilization among the elderly, there have not been corresponding improvements in our knowledge of how long people stay in nursing homes. In particular, elderly people who enter nursing homes as private patients face the risk of spending-down their assets until they become eligible for Medicaid, and it is not known how great this risk is. The first aim is to develop and validate on several data sets hierarchical models incorporating linear multiple regression terms that will provide estimates of important policy variables, while accounting for commonly encountered sampling problems. These sampling problems include censoring and length-biased sampling. The hierarchical modeling framework is important because it enables fitting individual-level models, permits heterogeneity across individuals, and results in more general (mixture) duration distributions. The other two aims are to apply the models developed to improve estimates of nursing home length of stay and the probability of spend-down. The nursing home data set includes all residents in thirty-six San Diego nursing homes during a year and a half period during the early 1980s. As second major focus will be an estimating length of stay of inpatients in mental health facilities, using data from Massachusetts during 1985-1992. The methods developed will be applicable to other health data sets.

该项目的目标是开发统计方法来估计持续时间(生存)模型，并将这些方法应用于养老院和心理健康持续时间数据。尽管对护理的兴趣与日俱增在老年人的居所使用中，还没有出现相应的我们对人们在养老院停留多长时间的了解有所改善。在……里面特别是，作为私人病人进入疗养院的老年人面临花费他们的资产直到他们有资格获得医疗补助，目前还不知道这种风险有多大。第一个目标是在几个分层的数据集上进行开发和验证包含线性多元回归项的模型将提供对重要政策变量的估计，同时说明通常遇到了抽样问题。这些抽样问题包括审查和长度偏差抽样。分层建模框架是重要的是因为它能够匹配个人级别的模型、许可个体之间的异质性，并导致更普遍的(混合) 持续时间分布。另外两个目标是应用为改进估计而开发的模型疗养院的住院时间和花费的概率。这个疗养院数据集包括圣地亚哥36个州的所有居民 20世纪80年代初一年半期间的养老院。AS 第二个主要关注点是估计住院患者的住院时间。精神卫生机构，使用1985-1992年间马萨诸塞州的数据。所开发的方法将适用于其他健康数据集。