Wilfrid Laurier University, Waterloo, Ontario, Canada.
Fraser Health, Surrey, British Columbia, Canada.
J Appl Gerontol. 2021 Jul;40(7):731-741. doi: 10.1177/0733464820920102. Epub 2020 May 26.
The main objective was to develop a decision-support tool to assess the risk of caregiver burden, the Caregiver Risk Evaluation (CaRE) algorithm. Home care clients were assessed using the Resident Assessment Instrument for Home Care (RAI-HC). Their caregiver completed the 12-item Zarit Burden Interview (ZBI), the main dependent measure, which was linked to the RAI-HC. In the sample ( = 344), 48% were aged 85+ years and 61.6% were female. The algorithm can be collapsed into four categories (low, moderate, high, and very high risk). Relative to the low-risk group, clients in the very high-risk group had an odds ratio of 5.16 (95% confidence interval: [2.05, 12.9]) for long-term care admission, after adjusting for client age, sex, and regional health authority. The CaRE algorithm represents a new tool to be used by home care clinicians as they proactively plan for the needs of clients and their caregivers.
主要目标是开发一种决策支持工具来评估照顾者负担的风险，即照顾者风险评估（CaRE）算法。使用家庭护理居民评估工具（RAI-HC）对家庭护理客户进行评估。他们的照顾者完成了 12 项 Zarit 负担访谈（ZBI），这是主要的因变量，与 RAI-HC 相关联。在样本（n=344）中，48%的人年龄在 85 岁以上，61.6%为女性。该算法可以分为四个类别（低、中、高和极高风险）。与低风险组相比，极高风险组的客户在调整了客户年龄、性别和地区卫生局后，长期护理入院的优势比为 5.16（95%置信区间：[2.05，12.9]）。CaRE 算法代表了家庭护理临床医生在积极规划客户及其照顾者需求时使用的一种新工具。
