Aged care service use by Aboriginal and Torres Strait Islander people after aged care eligibility assessments, 2017-2019: a population-based retrospective cohort study.

OBJECTIVE: To characterise the socio-demographic characteristics, aged and health care needs, and aged care services used by older Aboriginal and Torres Strait Islander people assessed for aged care service eligibility. STUDY DESIGN: Population-based retrospective cohort study; analysis of Registry of Senior Australians (ROSA) National Historical Cohort data. SETTING, PARTICIPANTS: Aboriginal and Torres Strait Islander people aged 50 years or older who were first assessed for aged care service eligibility (permanent residential aged care, home care package, respite care, or transition care) during 1 January 2017 - 31 December 2019. MAJOR OUTCOME MEASURES: Socio-demographic and aged care assessment characteristics; health conditions and functional limitations recorded at the time of the assessment; subsequent aged care service use. RESULTS: The median age of the 6209 people assessed for aged care service eligibility was 67 years (interquartile range [IQR], 60-75 years), 3626 were women (58.4%), and 4043 lived in regional to very remote areas of Australia (65.1%). Aboriginal health workers were involved in 655 eligibility assessments (10.5%). The median number of health conditions was six (IQR, 4-8); 6013 (96.9%) had two or more health conditions, and 2592 (41.8%) had seven or more. Comorbidity was most frequent among people with mental health conditions: 597 of 1136 people with anxiety (52.5%) and 1170 of 2416 people with depression (48.5%) had seven or more other medical conditions. Geriatric syndromes were recorded for 2265 people (36.5%); assistance with at least one functional activity was required by 6190 people (99.7%). A total of 6114 people (98.5%) were approved for at least one aged care service, 3218 of whom (52.6%) subsequently used these services; the first services used were most frequently home care packages (1660 people, 51.6%). CONCLUSION: Despite the high care needs of older Aboriginal and Torres Strait Islander people, only 52% used aged care services for which they were eligible. It is likely that the health and aged care needs of older Aboriginal and Torres Strait Islander people are not being adequately met.

Medication management in long-term care: using evidence generated from real-world data to effect policy change in the Australian setting.

Older individuals residing in long-term care facilities (LTCFs) are often living with multimorbidity and exposed to polypharmacy, and many experience medication-related problems. Because randomized controlled trials seldom include individuals in LTCFs, pharmacoepidemiological studies using real-world data are essential sources of new knowledge on the utilization, safety and effectiveness of pharmacotherapies and related health outcomes in this population. In this commentary, we discuss recent pharmacoepidemiological research undertaken to support the investigations and recommendations of a landmark public inquiry into the quality and safety of care provided in the approximately 3,000 Australian LTCFs which house over 240,000 residents annually and informed subsequent national medication-related policy reforms. Suitable sources of real-world data for pharmacoepidemiological studies in long-term care cohorts and methodological considerations are also discussed.

Estimating potential palliative care needs for residential aged care: A population-based retrospective cohort study.

OBJECTIVE: Population-based data on the required needs for palliative care in residential aged care have been highlighted as a key information gap. This study aimed to provide a comprehensive estimate of palliative care needs among Australia's residential aged care population using a validated algorithm based on causes of death. METHODS: A population-based retrospective cohort study was conducted using data from the Registry of Senior Australians of non-Indigenous residents of residential aged care services in New South Wales, Victoria, and South Australia aged older than 65 years, who died between 2016 and 2017 (n = 71,677). An internationally validated algorithm was used to estimate and characterise potential palliative care needs based on causes of death. This estimate was compared to palliative care needs identified from funding-based care needs assessment data. RESULTS: Ninety two per cent (n = 65,949) were estimated to have had potential palliative care needs prior to their death. Of these, 19% (n = 12,467) were assigned an end-of-life trajectory related to cancer, 61% (n = 40,511) to organ failure and 20% (n = 12,971) to frailty and dementia. By comparison, only 6% (n = 4430) of residents were assessed as needing palliative care by the funding-based care needs assessment. CONCLUSIONS: Over 90% of individuals dying in residential aged care may have benefited from a palliative approach to care. This need is substantially underestimated by the funding-based care needs assessment, which utilises a narrow definition of palliative care when death is imminent. There is a clear imperative to distinguish between palliative and end-of-life care needs within residential aged care to ensure appropriate and equitable access to palliative care.

Quality indicators to monitor the quality and safety of care for older people: a scoping review protocol.

OBJECTIVE: The objective of this review is to identify quality indicators used to monitor the quality and safety of care provided to older people (≥ 65 years old) in 8 care settings: primary care; hospital/acute care; aged care (including residential aged care and home or community care); palliative care; rehabilitation care; care transitions; dementia care; and care in rural areas. INTRODUCTION: There is a need for high-quality, holistic, person-centered aged and health care for older people. Older people receive care across multiple care settings, and population-level monitoring of quality and safety of care across settings represents a significant challenge. INCLUSION CRITERIA: National and international quality indicators used to monitor and evaluate quality and safety of care at the population level for older individuals in the 8 key care settings will be considered for inclusion. English-language quantitative and mixed method studies published from 2012 will be considered. METHODS: Academic (MEDLINE, Embase) and gray (government websites, clinical guidelines, Google) literature searches will be conducted. A standardized data extraction tool will be used to describe the identified quality indicators and associated tools. Quality indicators will be categorized by key domains (ie, pain, function, consumer experience, service delivery), quality indicator type (structure, process, outcome) and the Institute of Medicine's 6 dimensions of care quality (eg, efficiency, effectiveness, appropriateness, accessibility, acceptability/person-centered, safety). The scoping review will be conducted in accordance with the JBI methodology for scoping reviews and the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). REVIEW REGISTRATION: Open Science Framework osf.io/8czun.

Predictors of mortality shortly after entering a long-term care facility.

OBJECTIVE: Moving into a long-term care facility (LTCF) requires substantial personal, societal and financial investment. Identifying those at high risk of short-term mortality after LTCF entry can help with care planning and risk factor management. This study aimed to: (i) examine individual-, facility-, medication-, system- and healthcare-related predictors for 90-day mortality at entry into an LTCF and (ii) create risk profiles for this outcome. DESIGN: Retrospective cohort study using data from the Registry of Senior Australians. SUBJECTS: Individuals aged ≥ 65 years old with first-time permanent entry into an LTCF in three Australian states between 01 January 2013 and 31 December 2016. METHODS: A prediction model for 90-day mortality was developed using Cox regression with the purposeful variable selection approach. Individual-, medication-, system- and healthcare-related factors known at entry into an LTCF were examined as predictors. Harrell's C-index assessed the predictive ability of our risk models. RESULTS: 116,192 individuals who entered 1,967 facilities, of which 9.4% (N = 10,910) died within 90 days, were studied. We identified 51 predictors of mortality, five of which were effect modifiers. The strongest predictors included activities of daily living category (hazard ratio [HR] = 5.41, 95% confidence interval [CI] = 4.99-5.88 for high vs low), high level of complex health conditions (HR = 1.67, 95% CI = 1.58-1.77 for high vs low), several medication classes and male sex (HR = 1.59, 95% CI = 1.53-1.65). The model out-of-sample Harrell's C-index was 0.773. CONCLUSIONS: Our mortality prediction model, which includes several strongly associated factors, can moderately well identify individuals at high risk of mortality upon LTCF entry.

National trends in utilisation of glucose lowering medicines by older people with diabetes in long-term care facilities.

AIMS: To examine national trends in glucose lowering medicine (GLM) use among older people with diabetes in long-term care facilities (LTCFs) during 2009-2019. METHODS: A repeated cross-sectional study of individuals ≥65 years with diabetes in Australian LTCFs (n = 140,322) was conducted. Annual age-sex standardised prevalence of GLM use and number of defined daily doses (DDDs)/1000 resident-days were estimated. Multivariable Poisson or Negative binomial regression models were used to estimate adjusted rate ratios (aRRs) and 95 % confidence intervals (CIs). RESULTS: Prevalence of GLM use remained steady between 2009 (63.9%, 95 %CI 63.3-64.4) and 2019 (64.3%, 95 %CI 63.9-64.8) (aRR 1.00, 95 %CI 1.00-1.00). The percentage of residents receiving metformin increased from 36.0% (95 %CI 35.3-36.7) to 43.5% (95 %CI 42.9-44.1) (aRR 1.01, 95 %CI 1.01-1.01). Insulin use also increased from 21.5% (95 %CI 21.0-22.0) to 27.0% (95 %CI 26.5-27.5) (aRR 1.02, 95 %CI 1.02-1.02). Dipeptidyl peptidase-4 inhibitor use increased from 1.0% (95 %CI 0.9-1.1) to 21.1% (95 %CI 20.7-21.5) (aRR 1.24, 95 %CI 1.24-1.25), while sulfonylurea use decreased from 34.4% (95 %CI 33.8-35.1) to 19.3% (95 %CI 18.9-19.7) (aRR 0.93, 95 %CI 0.93-0.94). Similar trends were observed in DDDs/1000 resident days. CONCLUSIONS: The increasing use of insulin and ongoing use of sulfonylureas suggests a need to implement evidence-based strategies to optimise diabetes care in LTCFs.

National surveillance using a clinical quality indicator for prolonged antipsychotic use among older Australians with dementia who access aged care services.

OBJECTIVES: Dementia guidelines recommend antipsychotics are only used for behavioral and psychological symptoms when non-drug interventions fail, and to regularly review use. Population-level clinical quality indicators (CQIs) for dementia care in permanent residential aged care (PRAC) typically monitor prevalence of antipsychotic use but not prolonged use. This study aimed to develop a CQI for antipsychotic use >90 days and examine trends, associated factors, and variation in CQI incidence; and examine duration of the first episode of use among individuals with dementia accessing home care packages (HCPs) or PRAC. METHODS: Retrospective cohort study, including older individuals with dementia who accessed HCPs (n = 50,257) or PRAC (n = 250,196). Trends in annual CQI incidence (2011-12 to 2015-16) and associated factors were determined using Poisson regression. Funnel plots examined geographical and facility variation. Time to antipsychotic discontinuation was estimated among new antipsychotic users accessing HCP (n = 2367) and PRAC (n = 15,597) using the cumulative incidence function. RESULTS: Between 2011-12 and 2015-16, antipsychotic use for >90 days decreased in HCP recipients from 10.7% (95% CI 10.2-11.1) to 10.1% (95% CI 9.6-10.5, adjusted incidence rate ratio (aIRR) 0.97 (95% CI 0.95-0.98)), and in PRAC residents from 24.5% (95% CI 24.2-24.7) to 21.8% (95% CI 21.5-22.0, aIRR 0.97 (95% CI 0.96-0.98)). Prior antipsychotic use (both cohorts) and being male and greater socioeconomic disadvantage (PRAC cohort) were associated with higher CQI incidence. Little geographical/facility variation was observed. Median treatment duration in HCP and PRAC was 334 (interquartile range [IQR] 108-958) and 555 (IQR 197-1239) days, respectively. CONCLUSIONS: While small decreases in antipsychotic use >90 days were observed between 2011-12 and 2015-16, findings suggest antipsychotic use among aged care recipients with dementia can be further minimized.

Primary, allied health, selected specialists, and mental health service utilisation by home care recipients in Australia before and after accessing the care, 2017-2019.

OBJECTIVES: To examine changes in primary, allied health, selected specialists, and mental health service utilisation by older people in the year before and after accessing home care package (HCP) services. METHODS: A retrospective cohort study using the Registry of Senior Australians Historical National Cohort (≥ 65 years old), including individuals accessing HCP services between 2017 and 2019 (N = 109,558), was conducted. The utilisation of general practice (GP) attendances, health assessments, chronic disease management plans, allied health services, geriatric, pain, palliative, and mental health services, subsidised by the Australian Government Medicare Benefits Schedule, was assessed in the 12 months before and after HCP access, stratified by HCP level (1-2 vs. 3-4, i.e., lower vs. higher care needs). Relative changes in service utilisation 12 months before and after HCP access were estimated using adjusted risk ratios (aRR) from Generalised Estimating Equation Poisson models. RESULTS: Utilisation of health assessments (7-10.2%), chronic disease management plans (19.7-28.2%), and geriatric, pain, palliative, and mental health services (all ≤ 2.5%) remained low, before and after HCP access. Compared to 12 months prior to HCP access, 12 months after, GP after-hours attendances increased (HCP 1-2 from 6.95 to 7.5%, aRR = 1.07, 95% CI 1.03-1.11; HCP 3-4 from 7.76 to 9.32%, aRR = 1.20, 95%CI 1.13-1.28) and allied health services decreased (HCP 1-2 from 34.8 to 30.7%, aRR = 0.88, 95%CI 0.87-0.90; HCP levels 3-4 from 30.5 to 24.3%, aRR = 0.80, 95%CI 0.77-0.82). CONCLUSIONS: Most MBS subsidised preventive, management and specialist services are underutilised by older people, both before and after HCP access and small changes are observed after they access HCP.

National Trends in Antidepressant Use in Australian Residential Aged Care Facilities (2006-2019).

OBJECTIVES: Antipsychotics have been the focus of reforms for improving the appropriateness of psychotropic medicine use in residential aged care facilities (RACFs). Comprehensive evaluation of antidepressant use in RACFs is required to inform policy and practice initiatives targeting psychotropic medicines. This study examined national trends in antidepressant use among older people living in RACFs from 2006 to 2019. DESIGN: National repeated cross-sectional study. SETTING AND PARTICIPANTS: Individuals aged 65 to 105 years who were permanent, long-term (≥100 days) residents of Australian RACFs between January 2006 and December 2019 were included. METHODS: Annual age- and sex-adjusted antidepressant prevalence rates and defined daily doses (DDDs) supplied per 1000 resident-days from 2006 to 2019 were determined. Age- and sex-adjusted prevalence rate ratios (aRRs) and 95% confidence intervals (CIs) were estimated using Poisson and negative binomial regression models. RESULTS: A total of 779,659 residents of 3371 RACFs were included (786,227,380 resident-days). Overall, antidepressant use increased from 46.1% (95% CI, 45.9-46.4) in 2006 to 58.5% (95% CI, 58.3-58.8) of residents in 2019 (aRR, 1.02; 95% CI, 1.02-1.02). Mirtazapine use increased from 8.4% (95% CI, 8.2-8.5) to 20.9% (95% CI, 20.7-21.1) from 2006 to 2019 (aRR, 1.07; 95% CI, 1.07-1.07). Antidepressant use increased from 350.3 (95% CI, 347.6-353.1) to 506.0 (95% CI, 502.8-509.3) DDDs/1000 resident-days (aRR, 1.03; 95% CI, 1.03-1.03), with mirtazapine utilization increasing by 6% annually (aRR, 1.06; 95% CI, 1.06-1.06). CONCLUSIONS AND IMPLICATIONS: This nationwide study identified a substantial increase in antidepressant use among residents of Australian RACFs, largely driven by mirtazapine. With nearly 3 in every 5 residents treated with an antidepressant in 2019, findings highlight potential off-label use and suggest that interventions to optimize care are urgently needed.

Hospitalisations and emergency department presentations by older individuals accessing long-term aged care in Australia.

Objective The study examined emergency department (ED) presentations, unplanned hospitalisations and potentially preventable hospitalisations in older people receiving long-term care by type of care received (i.e. permanent residential aged care or home care packages in the community), in Australia in 2019. Methods A retrospective cohort study was conducted using the Registry of Senior Australians National Historical Cohort. Individuals were included if they resided in South Australia, Queensland, Victoria or New South Wales, received a home care package or permanent residential aged care in 2019 and were aged ≥65 years. The cumulative incidence of ED presentations, unplanned hospitalisations and potentially preventable hospitalisations in each of the long-term care service types were estimated during the year. Days in hospital per 1000 individuals were also calculated. Results The study included 203,278 individuals accessing permanent residential aged care (209,639 episodes) and 118,999 accessing home care packages in the community (127,893 episodes). A higher proportion of people accessing home care packages had an ED presentation (43.1% [95% confidence interval, 42.8-43.3], vs 37.8% [37.6-38.0]), unplanned hospitalisation (39.8% [39.6-40.1] vs 33.4% [33.2-33.6]) and potentially preventable hospitalisation (11.8% [11.6-12.0] vs 8.2% [8.1-8.4]) than people accessing permanent residential aged care. Individuals with home care packages had more days in hospital due to unplanned hospitalisations than those in residential care (7745 vs 3049 days/1000 individuals). Conclusions While a high proportion of older people in long-term care have ED presentations, unplanned hospitalisations and potentially preventable hospitalisations, people in the community with home care packages experience these events at a higher frequency.

Historical Trends and Future Projections of Demand for Permanent Residential Aged Care for Older People in Australia, 2008-2052.

OBJECTIVES: To examine the historical trends and predict the future rates and total volumes of permanent residential aged care (PRAC) service utilization in Australia. DESIGN: A population-based repeated cross-sectional and projection study of non-indigenous older people (≥65 years) accessing PRAC in Australia was conducted. SETTING AND PARTICIPANTS: Publicly available aged care admissions from the Australian Institute of Health and Welfare and population estimates from the Australian Bureau of Statistics were used. METHODS: Historical incidence rates (per 1000 people), incidence rate ratios (IRRs) and 95% CIs of PRAC admission from 2008-2009 to 2020-2021 were estimated using negative binomial regression models. The future incidence and prediction intervals (PIs) of PRAC admission between 2021-2022 and 2051-2052 were projected using a generalized additive model-negative binomial regression. All estimates were adjusted or standardized by sex and age. RESULTS: Between 2008-2009 and 2020-2021, the adjusted admission to PRAC decreased (from 23.6/1000 people to 15.7/1000 people with an IRR = 0.97/year, 95% CI 0.97-0.98). The projected PRAC admission rate will decrease to 12.1/1000 (95%PI 10.8-13.3) by 2037-2038 and 9.0/1000 (95%PI 7.6-10.4) by 2051-2052. The projected volume of PRAC admission will be 73,988 (95%PI 65,960-81,425) at its highest point in 2037-2038 and 64,579 (95%PI 54,258-74,543) in 2051-2052. CONCLUSIONS AND IMPLICATIONS: The utilization of PRAC has decreased in the past decade, and a predicted decrease in PRAC use in future years is estimated. However, the volume of PRAC utilization will still increase for the next 15 years (until 2037-2038) due to our increasingly older population. These findings can inform service planning of PRAC access in Australia.

Excess mortality in residents of aged care facilities during COVID-19 in Australia, 2019-22.

BACKGROUND: To date, the excess mortality experienced by residential aged care facility (RACF) residents related to COVID-19 has not been estimated in Australia. This study examined (i) the historical mortality trends (2008-09 to 2021-22) and (ii) the excess mortality (2019-20 to 2021-22) of Australian RACF residents. METHODS: A retrospective population-based study was conducted using the Australian Institute of Health and Welfare's GEN website data (publicly available aged care services information). Non-Aboriginal, older (≥65 years old) RACF residents between 2008-09 and 2021-22 were evaluated. The observed mortality rate was estimated from RACF exits compared with the RACF cohort yearly. Direct standardization was employed to estimate age-standardized mortality rates and 95% CIs. Excess mortality and 95% prediction intervals (PIs) for 2019-20 to 2021-22 were estimated using four negative binomial (NB) and NB generalized additive models and compared. RESULTS: The age-standardized mortality rate in 2018-19 was 23 061/100 000 residents (95% CI, 22 711-23 412). This rate remained similar in 2019-20 (23 023/100 000; 95% CI, 22 674-23 372), decreased in 2020-21 (22 559/100 000; 95% CI, 22 210-22 909) and increased in 2021-22 (24 885/100 000; 95% CI, 24 543-25 227). The mortality rate increase between 2020-21 and 2021-22 was observed in all age and sex groups. All models yielded excess mortality in 2021-22. Using the best-performing model (NB), the excess mortality for 2019-20 was -160 (95% PI, -418 to 98), -958 (95% PI, -1279 to -637) for 2020-21 and 4896 (95% PI, 4503-5288) for 2021-22. CONCLUSIONS: In 2021-22, RACF residents, who represented <1% of the population, experienced 21% of the Australian national excess mortality (4896/22 886). As Australia adjusts to COVID-19, RACF residents remain a population vulnerable to COVID-19.

The risk of fractures after entering long-term care facilities.

BACKGROUND: Stratifying residents at increased risk for fractures in long-term care facilities (LTCFs) can potentially improve awareness and facilitate the delivery of targeted interventions to reduce risk. Although several fracture risk assessment tools exist, most are not suitable for individuals entering LTCF. Moreover, existing tools do not examine risk profiles of individuals at key periods in their aged care journey, specifically at entry into LTCFs. PURPOSE: Our objectives were to identify fracture predictors, develop a fracture risk prognostic model for new LTCF residents and compare its performance to the Fracture Risk Assessment in Long term care (FRAiL) model using the Registry of Senior Australians (ROSA) Historical National Cohort, which contains integrated health and aged care information for individuals receiving long term care services. METHODS: Individuals aged ≥65 years old who entered 2079 facilities in three Australian states between 01/01/2009 and 31/12/2016 were examined. Fractures (any) within 365 days of LTCF entry were the outcome of interest. Individual, medication, health care, facility and system-related factors were examined as predictors. A fracture prognostic model was developed using elastic nets penalised regression and Fine-Gray models. Model discrimination was examined using area under the receiver operating characteristics curve (AUC) from the 20 % testing dataset. Model performance was compared to an existing risk model (i.e., FRAiL model). RESULTS: Of the 238,782 individuals studied, 62.3 % (N = 148,838) were women, 49.7 % (N = 118,598) had dementia and the median age was 84 (interquartile range 79-89). Within 365 days of LTCF entry, 7.2 % (N = 17,110) of individuals experienced a fracture. The strongest fracture predictors included: complex health care rating (no vs high care needs, sub-distribution hazard ratio (sHR) = 1.52, 95 % confidence interval (CI) 1.39-1.67), nutrition rating (moderate vs worst, sHR = 1.48, 95%CI 1.38-1.59), prior fractures (sHR ranging from 1.24 to 1.41 depending on fracture site/type), one year history of general practitioner attendances (≥16 attendances vs none, sHR = 1.35, 95%CI 1.18-1.54), use of dopa and dopa derivative antiparkinsonian medications (sHR = 1.28, 95%CI 1.19-1.38), history of osteoporosis (sHR = 1.22, 95%CI 1.16-1.27), dementia (sHR = 1.22, 95%CI 1.17-1.28) and falls (sHR = 1.21, 95%CI 1.17-1.25). The model AUC in the testing cohort was 0.62 (95%CI 0.61-0.63) and performed similar to the FRAiL model (AUC = 0.61, 95%CI 0.60-0.62). CONCLUSIONS: Critical information captured during transition into LTCF can be effectively leveraged to inform fracture risk profiling. New fracture predictors including complex health care needs, recent emergency department encounters, general practitioner and consultant physician attendances, were identified.

Primary health care service utilisation before and after entry into long-term care in Australia.

OBJECTIVES: To examine utilisation of primary health care services (subsidised by the Australian Government, Medicare Benefits Schedule, MBS) before and after entry into long-term care (LTC) in Australia. METHODS: A retrospective cohort study of older people (aged ≥65 years) who entered LTC in Australia between 2012 and 2016 using the Historical Cohort of the Registry of Senior Australians. MBS-subsidised general attendances (general practitioner (GP), medical and nurse practitioners), health assessment and management plans, allied health, mental health services and selected specialist attendances accessed in 91-day periods 12 months before and after LTC entry were examined. Adjusted relative changes in utilisation 0-3 months before and after LTC entry were estimated using risk ratios (RR) calculated using Generalised Estimating Equation Poisson models. RESULTS: 235,217 residents were included in the study with a median age of 84 years (interquartile range 79-89) and 61.1% female. In the first 3 months following LTC entry, GP / medical practitioner attendances increased from 86.6% to 95.6% (aRR 1.10 95%CI 1.10-1.11), GP / medical practitioner urgent after hours (from 12.3% to 21.1%; aRR 1.72, 95%CI 1.70-1.74) and after-hours attendances (from 18.5% to 33.8%; aRR 1.83, 95%CI 1.81-1.84) increased almost two-fold. Pain, palliative and geriatric specialist medicine attendances were low in the 3 months prior (<3%) and decreased further following LTC admission. CONCLUSION: There is an opportunity to improve the utilisation of primary health care services following LTC entry to ensure that residents' increasingly complex care needs are adequately met.

Clinical Quality Indicators for Monitoring Hospitalizations Among Older People with Dementia Accessing Aged Care Services.

BACKGROUND: There is a need for clinical quality indicators (CQIs) that can be applied to dementia quality registries to monitor care outcomes for people with Alzheimer's disease and other forms of dementia. OBJECTIVE: To develop tertiary and primary care-based dementia CQIs for application to clinical registries for individuals with dementia accessing aged care services and determine 1) annual trends in CQI incidence between 2011-2012 and 2015-2016, 2) associated factors, and 3) geographic and facility variation in CQI incidence. METHODS: This retrospective repeated cross-sectional study included non-Indigenous individuals aged 65-105 years who lived with dementia between July 2008-June 2016, were assessed for government-funded aged care services, and resided in New South Wales or Victoria (n = 180,675). Poisson or negative binomial regression models estimated trends in annual CQI incidence and associated factors. Funnel plots examined CQI variation. RESULTS: Between 2011-2012 and 2015-2016, CQI incidence increased for falls (11.0% to 13.9%, adjusted incidence rate ratio (aIRR) 1.05 (95% CI 1.01-1.06)) and delirium (4.7% to 6.7%, aIRR 1.09 (95% CI 1.07-1.10)), decreased for unplanned hospitalizations (28.7% to 27.9%, aIRR 0.99 (95% CI 0.98-0.99)) and remained steady for fracture (6.2% to 6.5%, aIRR 1.01 (95% CI 0.99-1.01)) and pressure injuries (0.5% to 0.4%, aIRR 0.99 (95% CI 0.96-1.02)). Being male, older, having more comorbidities and living in a major city were associated with higher CQI incidence. Considerable geographical and facility variation was observed for unplanned hospitalizations and delirium CQIs. CONCLUSIONS: The CQI results highlighted considerable morbidity. The CQIs tested should be considered for application in clinical quality registries to monitor dementia care quality.

Cohort profile: GRACE - a residential aged care cohort examining factors influencing antimicrobial resistance carriage.

BACKGROUND: The emergence of antimicrobial-resistant bacteria represents a considerable threat to human health, particularly for vulnerable populations such as those living in residential aged care. However, antimicrobial resistance carriage and modes of transmission remain incompletely understood. The Generating evidence on antimicrobial Resistance in the Aged Care Environment (GRACE) study was established to determine principal risk factors of antimicrobial resistance carriage and transmission in residential aged care facilities (RACFs). This article describes the cohort characteristics, national representation, and planned analyses for this study. METHODS: Between March 2019 and March 2020, 279 participants were recruited from five South Australian RACFs. The median age was 88.6 years, the median period in residence was 681 days, and 71.7% were female. A dementia diagnosis was recorded in 54.5% and more than two thirds had moderate to severe cognitive impairment (68.8%). 61% had received at least one course of antibiotics in the 12 months prior to enrolment. RESULTS: To investigate the representation of the GRACE cohort to Australians in residential aged care, its characteristics were compared to a subset of the historical cohort of the Registry of Senior Australians (ROSA). This included 142,923 individuals who were permanent residents of RACFs on June 30th, 2017. GRACE and ROSA cohorts were similar in age, sex, and duration of residential care, prevalence of health conditions, and recorded dementia diagnoses. Differences were observed in care requirements and antibiotic exposure (both higher for GRACE participants). GRACE participants had fewer hospital visits compared to the ROSA cohort, and a smaller proportion were prescribed psycholeptic medications. CONCLUSIONS: We have assembled a cohort of aged care residents that is representative of the Australian aged care population, and which provides a basis for future analyses. Metagenomic data isolated from participants and built environments will be used to determine microbiome and resistome characteristics of an individual and the facility. Individual and facility risk exposures will be aligned with metagenomic data to identify principal determinants for antimicrobial resistance carriage. Ultimately, this analysis will inform measures aimed at reducing the emergence and spread of antimicrobial resistant pathogens in this high-risk population.