Suppr超能文献

康复服务提供者对 SNF 到家庭过渡的成功可能性的预测因学科而异。

Rehabilitation Providers' Prediction of the Likely Success of the SNF-to-Home Transition Differs by Discipline.

机构信息

Department of Psychiatry, University of Rochester Medical Center (URMC), Rochester, NY.

Division of Geriatrics, Department of Medicine, URMC, Rochester, NY.

出版信息

J Am Med Dir Assoc. 2019 Apr;20(4):492-496. doi: 10.1016/j.jamda.2018.11.015. Epub 2019 Jan 7.

Abstract

OBJECTIVES

Our article's primary objective is to examine whether rehabilitation providers can predict which patients discharged from skilled nursing facility (SNF) rehabilitation will be successful in their transition to home, controlling for sociodemographic factors and physical, mental, and social health characteristics.

DESIGN

Longitudinal cohort study.

SETTING AND PARTICIPANTS

One hundred-twelve English-speaking adults aged 65 years and older admitted to 2 SNF rehabilitation units.

MEASURES

Our outcome is time to "failed transition to home," which identified SNF rehabilitation patients who did not successfully transition from the SNF to home during the study. Our primary independent variable consisted of the prediction of medical providers, occupational therapists, physical therapists, and social workers about the likely success of their patients' SNF-to-home transition. We also examined the association of sociodemographic factors and physical, mental, and social health with a failed transition to home.

RESULTS

The predictions of occupational and physical therapists were associated with whether patients successfully transitioned from the SNF to their homes in bivariate [hazard ratio (HR) = 4.96, P = .014; HR = 10.91, P = .002, respectively] and multivariate (HR = 5.07, P = .036; HR = 53.33, P = .004) analyses. The predictions of medical providers and social workers, however, were not associated with our outcome in either bivariate (HR = 1.44, P = .512; HR = 0.84, P = .794, respectively) or multivariate (HR = 0.57, P = .487; HR = 0.54, P = .665) analyses. Living alone, more medical conditions, lower physical functioning scores, and greater depression scores were also associated with time to failed transition to home.

CONCLUSIONS/IMPLICATIONS: These findings suggest that occupational and physical therapists may be better able to predict post-SNF discharge outcomes than are other rehabilitation providers. Why occupational and physical therapists' predictions are associated with the SNF-to-home outcome whereas the predictions of medical providers and social workers are not is uncertain. A better understanding of the factors informing the postdischarge predictions of occupational and physical therapists may help identify ways to improve the SNF-to-home discharge planning process.

摘要

目的

我们这篇文章的主要目的是,通过控制社会人口因素以及身体、心理和社会健康特征,来检验康复服务提供者是否可以预测从熟练护理机构(SNF)康复出院的患者在过渡到家庭时是否成功。

设计

纵向队列研究。

地点和参与者

112 名年龄在 65 岁及以上、讲英语的成年人,他们被收入 2 个 SNF 康复病房。

措施

我们的结局是“向家庭过渡失败”的时间,这确定了 SNF 康复患者在研究期间未能从 SNF 成功过渡到家庭。我们的主要自变量包括医疗服务提供者、职业治疗师、物理治疗师和社会工作者对其患者 SNF 到家庭过渡成功可能性的预测。我们还检查了社会人口因素以及身体、心理和社会健康与向家庭过渡失败的关联。

结果

职业治疗师和物理治疗师的预测与患者是否能从 SNF 成功过渡到家庭有关(单变量分析的风险比[HR]分别为 4.96,P=0.014;HR 为 10.91,P=0.002),在多变量分析(HR 分别为 5.07,P=0.036;HR 为 53.33,P=0.004)中也存在关联。然而,医疗服务提供者和社会工作者的预测在单变量(HR 分别为 1.44,P=0.512;HR 为 0.84,P=0.794)和多变量(HR 分别为 0.57,P=0.487;HR 为 0.54,P=0.665)分析中均与我们的结局无关。独居、更多的医疗状况、较低的身体功能评分和更高的抑郁评分也与向家庭过渡失败的时间有关。

结论/意义:这些发现表明,职业治疗师和物理治疗师可能比其他康复服务提供者更能预测 SNF 出院后的结局。为什么职业治疗师和物理治疗师的预测与 SNF 到家庭的结果有关,而医疗服务提供者和社会工作者的预测却没有,这是不确定的。更好地了解影响职业治疗师和物理治疗师出院后预测的因素,可能有助于确定改善 SNF 向家庭出院计划流程的方法。

相似文献

本文引用的文献

6
Relationship Status and Long-Term Care Facility Use in Later Life.晚年的恋爱状况与长期护理机构的使用情况
J Gerontol B Psychol Sci Soc Sci. 2016 Jul;71(4):711-23. doi: 10.1093/geronb/gbv106. Epub 2015 Nov 17.
7
Factors Associated with Nursing Home Admission after Stroke in Older Women.老年女性中风后入住养老院的相关因素。
J Stroke Cerebrovasc Dis. 2015 Oct;24(10):2329-37. doi: 10.1016/j.jstrokecerebrovasdis.2015.06.013. Epub 2015 Jul 10.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验