End of life hospitalisations differ for older Australian women according to death trajectory: a longitudinal data linkage study

BACKGROUND: Hospitalisations are the prime contributor to healthcare expenditure, with older adults often identified as high hospital users. Despite the apparent high use of hospitals at the end of life, limited evidence currently exists regarding reasons for hospitalisation. Understanding complex end of life care needs is required for future health care planning as the global population ages. This study aimed to investigate patterns of hospitalisation in the last year of life by cause of death (COD) as well as reasons for admission and short-term predictors of hospital use. METHODS: Survey data from 1,205 decedents from the 1921-1926 cohort of the Australian Longitudinal Study on Women's Health were matched with the state-based hospital records and the National Death Index. Hospital patterns based on COD were graphically summarised and multivariate logistic regression models examined the impact of short-term predictors of length of stay (LOS). RESULTS: 85 % of women had at least one admission in the last year of life; and 8 % had their first observed admission during this time. Reasons for hospitalisation, timing of admissions and LOS differed by COD. Women who died of cancer, diabetes and 'other' causes were admitted earlier than women who died of organ failure, dementia and influenza. Women who died of organ failure overall spent the longest time in hospital, and women with cancer had the highest median LOS. Longer LOS was associated with previous short- and medium-term- hospitalisations and type of hospital separation. CONCLUSIONS: Reducing acute care admissions and LOS at the end of life is complex and requires a shift in perceptions and treatment regarding end of life care and chronic disease management

Accuracy of self-reported medicines use compared to pharmaceutical claims data amongst a national sample of older Australian women

This study assessed agreement between two measures of medicine use, self-report by mail and pharmaceutical claims data, for a national sample (N = 4687) of older women aged 79 to84 in2005, from the Australian Longitudinal Study on Women’s Health. Medicines used for common chronic diseases in older people were selected, with pharmaceutical claims data retrieval periods of three and six months. For six month retrieval, Kappa’s ranged between 0.44 (nervous system medicines) and 0.94 (glucose lowering medicines). For three month retrieval, aspirin (Kappa: 0.35) and folic acid (Kappa = 0.48) had lowest agreement. Women were least able to accurately report use of nervous system medicines (sensitivity < 50%), and most accurately report glucose lowering medicines use (sensitivity > 80%). Specificity was consistently high across all classes, suggesting women could accurately report using a medicine. Pharmaceutical claims data can assist evaluation of judicious medicines use, changes to availability and uptake of medicines, and track medicine expenditure for chronic conditions. Over-the-counter medicines, medicines not covered by pharmaceutical subsidies and those used on an as needed basis may be best measured by self-report, as use may be underestimated using pharmaceutical claims data

Use, access to, and impact of Medicare services for Australian women: findings from the Australian Longitudinal Study on Women’s Health

This major report from the Australian Longitudinal Study on Women’s Health (also known as Women’s Health Australia) adopts a life course approach to investigate changes in women’s health and health service use change across life stages. Women’s survey data were linked to Medicare Benefits Scheme (MBS) data, enabling analysis of women’s health, health behaviours and social circumstances over time, and how these relate to health care use at different life stages. Using these data, the report provides detailed information on how and when women use health services, and their costs, throughout the women’s life course

Validation of Frail Scale and comparison with hospital frailty risk score to predict hospital use in a cohort of older Australian women

Introduction: With no standard frailty tool for clinical care, research and policymaking, identifying frail older people is a challenge. Aims: This study aimed to compare two validated scales, which are the Frail Scale and Hospital Frailty Risk Score (HFRS) for their ability in identifying frailty in older Australian women and predicting hospital use. Methods: This study included older Australian women aged 75–95 years, who had unplanned overnight hospital admission as an index admission between 2001 and 2016. Data from the Australian Longitudinal Study on Women\u27s Health (ALSWH) were linked with administrative hospital data to calculate HFRS (using the International Statistical Classification of Diseases, Australia Modification (ICD-10-AM) diagnostic codes) and the Frail Scale (using the ALSWH self-reported survey). Results: The Frail Scale identified a higher proportion of older frail women (30.54%) compared to the HFRS (23.0%). Frail older women, classified by Frail Scale, were at higher risk of long hospital stay (adjusted odds ratio = 1.28, 95% CI = 1.02–1.60), repeated admission (adjusted hazard ratio [AHR] = 1.30, 95% CI = 1.03–1.41) and death (AHR = 1.70, 95% CI = 1.45–2.01). HFRS was associated with longer hospital stay and mortality. Conclusions: The proportion of older women classified as frail by the Frail Scale tool was higher than women classified as frail by HFRS. The Frail Scale and HFRS were not significantly associated with each other. While both tools were associated with the risk of long hospital stay and mortality, only the Frail Scale predicted the risk of repeated admission

Unplanned Readmission within 28 Days of Hospital Discharge in a Longitudinal Population-Based Cohort of Older Australian Women

This study aimed to estimate the incidence of 28-day unplanned readmission among older women, and associated factors. Data were used from the 1921&ndash;1926 birth cohort of the Australian Longitudinal Study on Women&rsquo;s Health. Linkage of self-reported survey data with the Admitted Patient Data Collection allowed the identification of hospital admissions for each woman and the corresponding baseline characteristics. The Cox proportional-hazards model was used to identify factors associated with time to unplanned readmission, using SAS software V 9.4. (SAS Institute, Cary, NC, USA). Of 2056 women with index unplanned admission, 363 (17.5%) were readmitted within 28 days of discharge, and of these 229 (11.14%) had unplanned readmission. Among women with unplanned readmission, 24% were for the same condition as for the index hospitalisation. Cardiovascular diseases were the main diagnoses for the index admission and readmission. Unplanned readmission risk was higher if not partnered (hazard ratio (HR) = 1.43, 95% confidence interval (CI): 1.05&ndash;1.95), of non-English speaking background (HR = 1.62%, 95% CI: 1.07&ndash;2.47), more than three days length of stay on index admission (HR = 1.41%, 95% CI: 1.04&ndash;1.90) and one or two of the assessed chronic diseases (HR = 1.68, 95% CI: 1.19&ndash;2.36). At least one in ten women had unplanned readmission at some time between ages 75&ndash;95 years. Women who are not partnered, not of English-speaking background, with longer hospital stay and those with multi-morbidity, may need further efforts during their stay and on discharge to mitigate unplanned readmission