TIMING AND PREDICTORS OF NURSING HOME TRANSFERS

转移到另一个养老院的好处是潜在的巨大的居民的护理需求已经改变或其初始安置是次优的。对转移率的了解对于确定长期护理的发作也是必要的。文献中对转移流行率的估计很少，而且缺乏大型数据集来跟踪各个设施的居民，这就排除了对转移时间或预测因素的分析。本研究的目标是发展衡量疗养院转移的普遍性和时间，以及识别与转移相关的居民和设施特征。分析将以前无法获得的居民水平数据（使用最小数据集）与设施信息和县级特征相结合，以检查1994年至1996年六个州的转移率及其预测因子。初步估计表明，在研究期间的前六个月，纽约州的转移率为3.35%，缅因州为7.28%。这一估计既包括常见病患者，也包括偶发患者，而在养老院入住的前六个月观察到的患者，转院的发生率将更高。居民被观察的时间越长，转院率就越低，比如在研究的第24到30个月之间，1.6%的纽约居民和3.5%的缅因州居民转院了。潜在的行为模型假设，转移的可能性随着有助于提高预期收益和降低显性和隐性转移成本的因素而增加。影响转移效益和成本的因素包括居民的社会人口特征、支付来源、功能状态的水平和变化、社会活动的参与、家庭参与、设施的所有权和规模、提供的服务和护理质量，以及县市场层面的特征，包括乡村性和与其他提供者的距离。该项目将有助于设计干预措施，更好地匹配个人和提供者，并确保随着居民需求的变化获得适当的护理，并有助于就向弱势群体提供适当服务以及选择提供者的障碍的重要性进行政策讨论。

The benefits of transferring to another nursing home are potentially large for residents whose care needs have changed or whose initial placement was Suboptimal. Knowledge of transfer rates is also necessary to defining episodes of long-term care. The literature contains few estimates of transfer prevalence and the lack of large data sets tracking residents across facilities has precluded analyses of the timing or predictors of transfers. This study's goals are the development of measures of both the prevalence and timing of nursing home transfers and the identification of resident and facility characteristics associated with transferring. The analyses combine previously unavailable resident level data (using the Minimum Data Set) with facility information and county level characteristics to examine transfer rates and their predictors for six states from 1994 through 1996. Preliminary estimates indicate that transfer rates during the first six months of the study period were 3.35 percent in New York and 7.28 percent in Maine. That estimate includes both prevalent and incident patients, and the prevalence of transfers will be higher for patients who are observed in the first six months of their nursing home stay. The transfer rate declined the longer a resident was under observation, such that between months 24 and 30 of the study, 1.6 percent of New York and 3.5 percent of Maine residents transferred. The underlying behavior model posits that the likelihood of a transfer increases with factors that contribute to higher expected benefits and lower explicit and implicit costs of transferring. Factors contributing to the benefits and costs of transferring include resident's sociodemographics, payment source, levels and changes in functional status, involvement in social activities, family involvement, facility ownership and size, services provided, and quality of care, and county market-level characteristics, including rurality and distance to other providers. This project will contribute to appropriate care as designing interventions that better match individuals and providers and ensure access to appropriate care as resident's needs evolve and to policy discussions about the availability of appropriate services to vulnerable populations and the significance of barriers to choice of provider.