Registry of Senior Australians (ROSA): integrating cross-sectoral information to evaluate quality and safety of care provided to older people

Prolonged Use of Antidepressants Among Older People Residing in Long-Term Care Facilities

OBJECTIVES

Antidepressants are commonly used by older people and use increases during transition to long-term care facilities (LTCFs); however, little is known regarding duration of use following LTCF entry. This study aimed to examine duration of antidepressant use among new and existing antidepressant users after LTCF entry.

DESIGN

Retrospective cohort study.

SETTING AND PARTICIPANTS

Non-Indigenous individuals aged 65 to 105 years who entered LTCFs in 2 Australian states between 2015 and 2018 and received an antidepressant between LTCF entry and ≤60 days after, were included.

METHODS

Cumulative incidence function and Fine-Gray regression models adjusted for age, sex, and LTCF entry year, accounted for the competing risk of death, and estimated the subdistribution hazard ratio (sHR) and 95% confidence interval (95% CI) for antidepressant discontinuation for all, new, and existing users.

RESULTS

Overall, 28,426 individuals entering 1035 LTCFs were included, of whom 22,365 (78.7%) were existing antidepressant users and 6061 (21.3%) were new users. Selective serotonin reuptake inhibitors and mirtazapine were commonly utilized. Overall, 36.1% (95% CI 35.1-37.1) of residents discontinued antidepressants (median follow-up 614 days, interquartile range 338-1002) following entry and 50.3% (95% CI 49.4-51.2) were dispensed enough to last until death. New antidepressant users had a 36% (adjusted sHR, 1.36; 95% CI, 1.29-1.44) higher risk of discontinuation compared with existing users.

CONCLUSIONS AND IMPLICATIONS

Prolonged antidepressant use is common in LTCFs, and therapy is often continued until the end-of-life. Initiating nonpharmacological alternatives, regular review of antidepressant appropriateness, and seeking discontinuation opportunities where appropriate can minimize potentially inappropriate antidepressant use and risk of harm.

Setting standards in residential aged care: identifying achievable benchmarks of care for long-term aged care services

BACKGROUND

Benchmark is an important aspect of quality measurement and evaluation of long-term care services (LTCS) performance. In this study, we aimed to estimate achievable benchmarks of care (ABC©) for 12 quality indicators used to monitor the quality of care in Australian LTCS and to identify LTCS characteristics associated with attaining the estimated ABC.

METHODS

A cross-sectional study was conducted using integrated population-based datasets from long-term care, health care, and social welfare sectors within the Registry of Senior Australians (ROSA) National Historical Cohort. All LTCS residents in 2019 were included. Twelve risk-adjusted quality indicators were examined. ABC were defined as the performance level of top-ranked LTCS, including those sequentially from rank 1 onward, until the combined number of residents included at least 10% of all residents nationally. Indicator-specific ABC for 2019 were estimated using Bayesian-adjusted performance fraction ranking. Logistic regressions estimated LTCS characteristics associated with ABC attainment.

RESULTS

2746 LTCS and 244 419 residents (≥65 years) between 1 January 2019 and 31 December 2019 were included. The cohort was mostly female (65%), with a median age of 86 years, and 56% had dementia. The ABC provide performance targets based on the observed levels of top-performing LTCS. The ABC for premature mortality (0.007%), weight loss hospitalizations (0.1%), pressure injuries (0.2%), delirium and dementia hospitalizations (0.2%), and medication-related adverse events (0.4%) were lower than 1% and attained by 17-59% of LTCS. The ABC for fractures (1.3%), falls (3.9%), and emergency department presentations (5.1%) were between 1 and 5% and attained by 7-11% of LTCS. The ABC for antipsychotic use (10.5%), chronic opioid use (12.6%), high sedative load exposure (26.8%), and antibiotic use (47.8%) were between 10 and 50% and met by 6-7% of LTCS. Smaller LTCS and government-owned LTCS were more likely to achieve the ABC compared to medium, larger, private, and not-for-profit LTCS.

CONCLUSION

This is the first national estimation of ABC for Australian LTCS, identifying real-world examples of LTCS with relatively better national performance. The ABC are realistic goals for LTCS improvement efforts. They can be leveraged as national standards in quality monitoring reports and incentive programs. Smaller and government LTCS were generally more likely to attain ABC.

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 3000 Australian LTCFs that house more than 240 000 residents annually, which 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. This article is part of a Special Collection on Pharmacoepidemiology.

Glucose-lowering medicines use before and after entry into long-term care facilities

AIM

To examine changes in the use of glucose-lowering medicine (GLM) 12 months before and 12 months after long-term care facility (LTCF) entry among people with diabetes.

MATERIALS AND METHODS

A national retrospective cohort study was conducted using linked health and aged care data from the Registry of Senior Australians National Historical Cohort. Residents of LTCFs with diabetes aged 65 years or older from 2015 to 2019 were included. Prevalence of GLM use and the number of defined daily doses (DDDs) dispensed per 1000 resident-days were estimated quarterly (91-day) using Poisson regression models, or negative binomial regression when overdispersion was present.

RESULTS

Among the 50 993 residents studied (median age 84 years), the prevalence of GLM use was 58.4% (95% confidence interval [CI] 58.0%-58.8%) in the 9-12 months pre-LTCF entry and 56.3% (95% CI 55.9%-56.8%) in the 9-12 months post-entry. The number of DDDs/1000 resident-days increased from 1015.2 (95% CI 1002.3-1028.1) to 1253.8 (95% CI 1168.4-1339.3) during the same period. GLM use in the 3 months pre-entry was 56.8% (95% CI 56.4%-57.2%) compared with 61.7% (95% CI 61.3%-62.1%) in the 3 months post-entry, with the increased use driven mainly by insulin. No marked changes in the number of GLMs dispensed or GLM type were observed at 9-12 months post-entry compared with 3 months pre-entry. Among 22 792 individuals dispensed a GLM in the 3 months prior to LTCF entry, 50.2% continued the same GLM at 9-12 months post-entry.

CONCLUSIONS

GLM use peaked in the first 3 months following LTCF entry, driven mainly by insulin, hence, residents may benefit from close monitoring of diabetes treatment during this period.

Health outcomes following provision of Home Medicines Reviews for older people receiving aged care services at home

BACKGROUND

The impact of Home Medicines Reviews (HMRs) on long-term health outcomes among individuals receiving long-term in-home aged care services is unknown.

OBJECTIVES

To examine associations between HMR provision and hospitalization, long-term care facility (LTCF) entry and mortality among older people receiving long-term in-home aged care services.

METHODS

This retrospective cohort study included individuals aged 65-105 years from three Australian states who accessed in-home aged care services between 2013 and 2017. Using propensity score matching, HMR recipients (n = 1530) were matched to individuals who did not receive an HMR (n = 1530). Associations between HMR provision and outcomes were estimated using multivariable regression models.

RESULTS

Over a median of 414 days (interquartile range 217-650) of follow-up, HMR provision was not associated with hospitalizations for unplanned events (subdistribution hazard ratio (sHR) 1.04, 95%CI 0.96-1.14), falls-related hospitalizations (sHR 0.97, 95%CI 0.83-1.13), LTCF entry (sHR 0.97, 95%CI 0.83-1.13), or all-cause mortality (adjusted HR 0.86, 95%CI 0.72-1.01).

CONCLUSIONS

In a cohort of older people receiving long-term in-home aged care services, no differences in unplanned hospitalizations, falls, LTCF entry or mortality were observed those with HMRs compared to those that did not receive an HMR.

Economic burden of frailty in older adults accessing community-based aged care services in Australia

AIM

To explore the utilization of permanent residential aged care (PRAC), healthcare costs, and mortality for frail compared with non-frail individuals following their first assessment by an aged care assessment team (ACAT) for a government-funded home care package.

METHODS

The study involved people aged 65 years and over who completed their first ACAT assessment in 2013 and were followed for up to 36 months. Frail and non-frail study participants were matched through caliper matching without replacement to adjust for potential unobserved confounders. Poisson regression estimated the impact of frailty on PRAC admission and mortality rates. Healthcare costs, encompassing hospital admissions, emergency department presentations, primary care consultations, and pharmaceutical use, from ACAT assessment to end of follow-up, PRAC entry or death were summarized monthly by frailty status.

RESULTS

13 315 non-frail controls were matched with up to three frail individuals (52 678 total). Frail individuals experienced higher mortality (incidence rate ratio [IRR] = 1.76; 95% confidence interval [CI] 1.70-1.83) and greater likelihood of entering PRAC (IRR = 1.73; 95% CI 1.67-1.79) compared with non-frail individuals. Total healthcare costs over the 3-year post-assessment period for 39 363 frail individuals were $1 277 659 900, compared with expected costs of $885 322 522 had they not been frail. The primary contributor to the mean monthly excess cost per frail individual (mean = $457, SD = 3192) was hospital admissions ($345; 75%).

CONCLUSIONS

Frailty is associated with higher rates of mortality and of entering PRAC, and excess costs of frailty are substantial and sustained over time. These findings emphasize the potential economic value of providing home care for older people before they become frail. Geriatr Gerontol Int 2024; 24: 939-947.

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.

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.

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.

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.

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.

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.

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.

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.

An exploration of healthcare use in older people waiting for and receiving Australian community-based aged care services

AIM

Home care packages (HCPs) facilitate older individuals to remain at home, with longer HCP wait times associated with increased mortality risk. We analyze healthcare cost data pre- and post-HCP access to inform hypotheses around the effects of healthcare use and mortality risk.

METHODS

Regression models were used to assess the impact of delayed HCP access on healthcare costs and to compare costs whilst waiting and in the 6- and 12 month periods post-HCP access for 16 629 older adults.

RESULTS

Average wait time for a HCP was 89.7 days (SD = 125.6) during the study period. Wait-time length had no impact on any healthcare cost category or time period. However, total per day healthcare costs were higher in the 6 and 12 months post-receipt of a HCP (AU$61.5, AU$63, respectively) compared with those in the time waiting for a HCP (AU$48.1). Inpatient care accounted for a higher proportion of total healthcare costs post-HCP (AU$45.1, AU$46.3, respectively) compared with in the wait time (AU$30.6), whilst spending on medical services and pharmaceuticals reduced slightly in the 6 month (AU$7.1, AU$6.3) and 12 month (AU$7.2, AU$6.3) post-HCP periods compared with in the wait time (AU$7.9, AU$7.1).

CONCLUSIONS

Increased spending post-HCP on inpatient care or non-health support afforded by HCPs may offer protective effects for mortality and risk of admission to aged care. Further research should explore the association between delayed access to inpatient care for geriatric syndromes and mortality to inform recommendations on extensions to residential care outreach services into the community to improve the timely identification of the need for inpatient care. Geriatr Gerontol Int 2023; 23: 899-905.

Investigating community-based care service factors delaying residential care home admission of community dwelling older adults and cost consequence

OBJECTIVES

To examine factors contributing to delaying care home admission; and compare the rates of care home admission and cost consequence between two government subsidised programmes, Veterans' Affairs Community Nursing (VCN) and Home Care Package (HCP).

METHODS

Our national, population-based retrospective cohort study and cost analysis used existing, de-identified veterans' claims databases (2010-19) and the Registry of Senior Australians Historical Cohort (2010-17), plus aggregate programme expenditure data. This involved 21,636 VCN clients (20,980 aged 65-100 years), and an age- and sex-matched HCP cohort (N = 20,980).

RESULTS

Service factors associated with lower risk of care home admission in the VCN cohort were periodic (versus continuous) service delivery (HR 0.27 [95%CI, 0.24-0.31] for ≤18 months; HR 0.89 [95%CI, 0.84-0.95] for >18 months), and majority care delivered by registered nurses (versus personal care workers) (HR 0.86 [95%CI, 0.75-0.99] for ≤18 months; HR 0.91 [95%CI, 0.85-0.98] for >18 months). In the matched cohorts, the time to care home admission for VCN clients (median 28 months, IQR 14-42) was higher than for HCP clients (14, IQR 6-27). Within 5 years of service access, 57.6% (95%CI, 56.9-58.4) of HCP clients and 26.6% (95%CI, 26.0-27.2) of VCN clients had care home admission. The estimated cost saving for VCN recipients compared to HCP recipients over 5 years for relevant government providers was over A$1 billion.

CONCLUSIONS

Compared to an HCP model, individuals receiving VCN services remained at home longer, with potentially significant cost savings. This new understanding suggests timely opportunity for many countries' efforts to enhance community-based care services.

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.