丹麦语
心理干预
医学
医疗保健
老年学
梅德林
护理部
家庭医学
疗养院
老年人
护理干预分类
就地老化
同行评审
定性研究
老年护理学
风险评估
医疗保健系统
作者
Connie Berthelsen,Mia Ingerslev Loft
摘要
BACKGROUND: Denmark's increasing elderly population with multiple chronic diseases calls for special attention regarding the risk of hospitalisation. This review aims to address the characteristics of this population and their antecedents with hospitalisation, contributing to the development of tailored interventions that could improve health outcomes and reduce preventable hospitalisations in this vulnerable population. AIM: To synthesise the data on characteristics of Danish older adults at risk for initial hospital admission and readmission while receiving home care or residing in nursing homes. DESIGN: Integrative review. The protocol was registered in Open Science Framework and published in Nordic Nursing Research. METHODS: Empirical studies were identified through electronic databases, including MEDLINE/PubMed, CINAHL Complete via EBSCO, ProQuest and SCOPUS. Theoretical sources were searched using Google, Google Scholar, organisational and university websites and library catalogues. All included records were assessed using the Critical Appraisal Skills Programme (CASP) Cohort Study Checklist. The PRISMA flowchart was utilised to report the search process across databases, registers and other sources. RESULTS: Age and sex were found to be unreliable predictors of hospital admission and readmission, whereas the number of comorbidities and medications were strong predictors of hospitalisation among Danish older adults receiving home care or residing in nursing homes. The risk of initial hospital admission and readmission was found to increase with the severity of illness and the level of care required. CONCLUSION: This review contributes to understanding how home care and nursing home residency influence older adults' likelihood of hospitalisation and readmission. The insights from this integrative review will be used to develop targeted interventions and serve as a step toward improving healthcare strategies for this population.
科研通智能强力驱动
Strongly Powered by AbleSci AI