TIMING AND PREDICTORS OF NURSING HOME TRANSFERS

对于那些护理需求发生变化或最初安置情况不佳的居民来说，转移到另一家养老院的好处可能很大。转移率的知识对于确定长期护理的事件也是必要的。文献中几乎没有对转移流行率的估计，而且缺乏跟踪各设施居民的大型数据集，因此无法分析转移的时间或预测因素。这项研究的目标是开发衡量疗养院转移的流行率和时间的指标，并确定与转移相关的居民和设施特征。这些分析将以前无法获得的居民水平数据(使用最小数据集)与设施信息和县一级特征相结合，以检查1994年至1996年六个州的转移率及其预测因素。初步估计表明，在研究期间的前六个月，纽约的转移率为3.35%，缅因州为7.28%。这一估计既包括流行的患者，也包括事件患者，而在疗养院住宿的前六个月观察到的患者的转院流行率将更高。居民被观察的时间越长，转移率就会下降，在研究的24个月到30个月期间，1.6%的纽约居民和3.5%的缅因州居民进行了转移。潜在的行为模型假设，转移的可能性随着转移的预期收益和转移的显性和隐性成本降低的因素而增加。影响转移的收益和成本的因素包括居民的社会人口结构、支付来源、功能地位的水平和变化、参与社会活动、家庭参与、设施所有权和规模、提供的服务和护理质量，以及县市场层面的特点，包括乡村和与其他提供者的距离。该项目将有助于提供适当的护理，因为它设计的干预措施能使个人和提供者更好地匹配，并确保随着居民需求的发展而获得适当的护理，并有助于关于向弱势群体提供适当服务的政策讨论以及选择提供者的障碍的重要性。

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.