TY - JOUR
T1 - The risk of fall-related hospitalisations at entry into permanent residential aged care
AU - Inacio, Maria C.
AU - Moldovan, Max
AU - Whitehead, Craig
AU - Sluggett, Janet K.
AU - Crotty, Maria
AU - Corlis, Megan
AU - Visvanathan, Renuka
AU - Wesselingh, Steve
AU - Caughey, Gillian E.
N1 - Funding Information:
A/Prof Maria Inacio is supported by The Hospital Research Foundation Mid-Career Fellowship (MCF-27-2019) and National Health and Medical Research Council (NHMRC) Investigator Grant (APP119378). JKS is supported by a NHMRC Early Career Fellowship (APP1156439).
Funding Information:
We would like to acknowledge the Healthy Ageing Research Consortium Investigator Team and the Registry of Senior Australians? (ROSA) South Australian Health and Medical Research Institute Research Team for ensuring the success of the ROSA and support with this study. We also acknowledge the South Australian Government who provide us with support (2017-2021) through the Department for Innovation and Skills, and the Australian Institute of Health and Welfare (AIHW), SA Health, and the NSW Ministry of Health, for the provision of the raw data used in the ROSA, and the Centre for Health Record Linkage, SA NT DataLink and AIHW for the data linkage. This study is a restrospective cohort study of existing data obtained from the Australian Government Department of Health and South Australia and New South Waltes state health authorities and integrated by the Australian Institute of Health and Welfare, Centre for Health Record Linkage, and SA NT DataLink. A waiver of informed consent was granted by the ethics committees who reviewed and approved the study due to the de-identified, existing nature of these data.
PY - 2021/12
Y1 - 2021/12
N2 - 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.
AB - 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.
KW - Aged care
KW - Falls
KW - Injury
KW - Risk-prediction
UR - https://www.scopus.com/pages/publications/85120872700
U2 - 10.1186/s12877-021-02640-w
DO - 10.1186/s12877-021-02640-w
M3 - Article
C2 - 34876037
AN - SCOPUS:85120872700
SN - 1471-2318
VL - 21
JO - BMC Geriatrics
JF - BMC Geriatrics
IS - 1
M1 - 686
ER -