Department of Statistics and Mathematical Modeling, Expertise Centre for Methodology and Information Services, National Institute for Public Health and the Environment, PO Box 1, 3720 BA, Bilthoven, the Netherlands.
BMC Health Serv Res. 2010 May 6;10:110. doi: 10.1186/1472-6963-10-110.
Long-term care is often associated with high health care expenditures. In the Netherlands, an ageing population will likely increase the demand for long-term care within the near future. The development of risk profiles will not only be useful for projecting future demand, but also for providing clues that may prevent or delay long-term care utilization. Here, we report our identification of predictors of long-term care utilization in a cohort of hospital patients aged 65+ following their discharge from hospital discharge and who, prior to hospital admission, were living at home.
The data were obtained from three national databases in the Netherlands: the national hospital discharge register, the long-term care expenses register and the population register. Multinomial logistic regression was applied to determine which variables were the best predictors of long-term care utilization. The model included demographic characteristics and several medical diagnoses. The outcome variables were discharge to home with no formal care (reference category), discharge to home with home care, admission to a nursing home and admission to a home for the elderly.
The study cohort consisted of 262,439 hospitalized patients. A higher age, longer stay in the hospital and absence of a spouse were found to be associated with a higher risk of all three types of long-term care. Individuals with a child had a lower risk of requiring residential care. Cerebrovascular diseases [relative risk ratio (RRR) = 11.5] were the strongest disease predictor of nursing home admission, and fractures of the ankle or lower leg (RRR = 6.1) were strong determinants of admission to a home for the elderly. Lung cancer (RRR = 4.9) was the strongest determinant of discharge to the home with home care.
These results emphasize the impact of age, absence/presence of a spouse and disease on long-term care utilization. In an era of demographic and epidemiological changes, not only will hospital use change, but also the need for long-term care following hospital discharge. The results of this study can be used by policy-makers for planning health care utilization services and anticipating future health care needs.
长期护理通常与高额医疗保健支出相关。在荷兰,人口老龄化很可能在不久的将来增加对长期护理的需求。制定风险概况不仅有助于预测未来的需求,还可以提供线索,以预防或延迟长期护理的使用。在这里,我们报告了我们在一组年龄在 65 岁以上的出院后居家的住院患者队列中识别长期护理使用的预测因素,这些患者在入院前居住在家中。
数据来自荷兰的三个国家数据库:国家住院患者登记处、长期护理费用登记处和人口登记处。我们应用多项逻辑回归来确定哪些变量是长期护理使用的最佳预测因素。该模型包括人口统计学特征和几种医学诊断。结局变量是出院回家且无需正规护理(参考类别)、出院回家但接受家庭护理、入住养老院和入住老年公寓。
研究队列包括 262439 名住院患者。研究发现,年龄较高、住院时间较长且没有配偶与所有三种类型的长期护理的风险较高相关。有子女的人需要居住护理的风险较低。脑血管疾病(相对风险比 [RRR] = 11.5)是入住养老院的最强疾病预测因素,踝关节或小腿骨折(RRR = 6.1)是入住老年公寓的强烈决定因素。肺癌(RRR = 4.9)是出院回家且接受家庭护理的最强决定因素。
这些结果强调了年龄、有无配偶以及疾病对长期护理使用的影响。在人口和流行病学变化的时代,不仅医院的使用会发生变化,而且出院后对长期护理的需求也会发生变化。本研究的结果可被决策者用于规划医疗保健使用服务并预测未来的医疗保健需求。