期刊
BMC GERIATRICS
卷 21, 期 1, 页码 -出版社
BMC
DOI: 10.1186/s12877-021-02640-w
关键词
Falls; Injury; Aged care; Risk-prediction
资金
- Hospital Research Foundation MidCareer Fellowship [MCF-27-2019]
- National Health and Medical Research Council (NHMRC) Investigator Grant [APP119378]
- NHMRC Early Career Fellowship [APP1156439]
This study examined factors at entry into permanent residential aged care in Australia that predict fall-related hospitalisations. Through the analysis of integrated aged and health care data, it was found that variables such as fracture history, falls history, and dementia were strong predictors for fall-related hospitalisations within 90 and 365 days after entry. The risk prediction models developed had reasonable discrimination for identifying residents at risk of fall-related hospitalisations, suggesting an opportunity for targeted risk mitigation strategies.
Background Entering permanent residential aged care (PRAC) is a vulnerable time for individuals. While falls risk assessment tools exist, these have not leveraged routinely collected and integrated information from the Australian aged and health care sectors. Our study examined individual, system, medication, and health care related factors at PRAC entry that are predictors of fall-related hospitalisations and developed a risk assessment tool using integrated aged and health care data. Methods A retrospective cohort study was conducted on N = 32,316 individuals >= 65 years old who entered a PRAC facility (01/01/2009-31/12/2016). Fall-related hospitalisations within 90 or 365 days were the outcomes of interest. Individual, system, medication, and health care-related factors were examined as predictors. Risk prediction models were developed using elastic nets penalised regression and Fine and Gray models. Area under the receiver operating characteristics curve (AUC) assessed model discrimination. Results 64.2% (N = 20,757) of the cohort were women and the median age was 85 years old (interquartile range 80-89). After PRAC entry, 3.7% (N = 1209) had a fall-related hospitalisation within 90 days and 9.8% (N = 3156) within 365 days. Twenty variables contributed to fall-related hospitalisation prediction within 90 days and the strongest predictors included fracture history (sub-distribution hazard ratio (sHR) = 1.87, 95% confidence interval (CI) 1.63-2.15), falls history (sHR = 1.41, 95%CI 1.21-2.15), and dementia (sHR = 1.39, 95%CI 1.22-1.57). Twenty-seven predictors of fall-related hospitalisation within 365 days were identified, the strongest predictors included dementia (sHR = 1.36, 95%CI 1.24-1.50), history of falls (sHR = 1.30, 95%CI 1.20-1.42) and fractures (sHR = 1.28, 95%CI 1.15-1.41). The risk prediction models had an AUC of 0.71 (95%CI 0.68-0.74) for fall-related hospitalisations within 90 days and 0.64 (95%CI 0.62-0.67) for within 365 days. Conclusion Routinely collected aged and health care data, when integrated at a clear point of action such as entry into PRAC, can identify residents at risk of fall-related hospitalisations, providing an opportunity for better targeting risk mitigation strategies.
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