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To estimate dementia incidence rates using Australian administrative datasets and compare the characteristics of people identified with dementia across different datasets. This data linkage study used a cohort of 267,153 from the Australian 45 and Up Study. Participants completed a survey in 2006–2009 and subsequent dementia was identified through pharmaceutical claims, hospitalisations, aged care eligibility assessments, care needs at residential aged care entry and death certificates. Age-specific, and age-standardised incidence rates, incidence rate ratios and survival from first dementia diagnosis were estimated. Estimated age-standardised dementia incidence rates using all linked datasets was 16.8 cases per 1000 person years for people aged 65+. Comparing incidence rates to the global published rates suggested 77% of cases were identified but this varied by age with highest coverage among those aged 80–84 years (92%). Incidence rate ratios were inconsistent across datasets for: sex, socio-economic disadvantage, size of support network, marital status, functional limitations and diabetes. Median survival from first dementia diagnosis ranged from 1.80 years in the care needs dataset to 3.74 years in the pharmaceutical claims dataset. Characteristics of people identified with dementia in different administrative datasets reflect the factors that drive interaction with specific services; this may introduce bias in observational studies using a single data-source to identify dementia.

Background The number of people living with chronic health conditions is increasing in Australia. The Chronic Disease Management program was introduced to Medicare Benefits Schedule (MBS) to provide a more structured approach to managing patients with chronic conditions and complex care needs. The program supports General Practitioners (GP)s claiming for up to one general practice management plan (GPMP) and one team care arrangement (TCA) every year and the patient claiming for up to five private allied health visits. We describe the profile of participants who claimed for GPMPs and/or TCAs in Central and Eastern Sydney (CES) and explore if GPMPs and/or TCAs are associated with fewer emergency hospitalisations (EH)s or potentially preventable hospitalisations (PPH)s over the following 5 years. Methods This research used the CES Primary and Community Health Cohort/Linkage Resource (CES-P&CH) based on the 45 and Up Study to identify a community-dwelling population in the CES region. There were 30,645 participants recruited within the CES area at baseline. The CES-P&CH includes 45 and Up Study questionnaire data linked to MBS data for the period 2006–2014. It also includes data from the Admitted Patient Data Collection, Emergency Department Data Collection and Deaths Registry linked by the NSW Centre for Health Record Linkage. Results Within a two-year health service utilisation baseline period 22% (5771) of CES participants had at least one claim for a GPMP and/or TCA. Having at least one claim for a GPMP and/or TCA was closely related to the socio-demographic and health needs of participants with higher EHs and PPHs in the 5 years that followed. However, after controlling for confounding factors such as socio-demographic need, health risk, health status and health care utilization no significant difference was found between having claimed for a GPMP and/or TCA during the two-year health service utilisation baseline period and EHs or PPHs in the subsequent 5 years. Conclusions The use of GPMPs and/or TCAs in the CES area appears well-targeted towards those with chronic and complex care needs. There was no evidence to suggest that the use of GPMPs and /or TCAs has prevented hospitalisations in the CES region.

Introduction: It is anticipated that by 2030 the number of older people and people living with long term conditions will have significantly increased. At the same time, it is expected that there will be a shift to providing more health care in the community. Browning et al [1] using a prospective 16-year longitudinal study of 1000 older Australians described three ageing groups (i) ageing well (30%); initially ageing well then deteriorating (50%); consistently ageing poorly (20%). Understanding the predictors of services use in older people is important in planning and providing quality care. Predictors of general practice service use from a small community-based studies have included: lower age, fewer medical conditions, restful sleep, good nutrition, decreased stress, being a non-smoker and good social support [2]. Using our existing data linkage resource, the Central and Eastern Sydney Primary and Community Health Cohort/Resource (CES-P&CH), which includes questionnaire data, primary care records, prescribing information, hospital records, emergency department records, cancer registry, and vital statistics on over 30,000 participants in CES aged 45 years and over (over 250,000 in NSW for comparison) we identified the predictors of service use (including general practice, pharmaceuticals, emergency departments, hospitalisations) amongst people aged over 75 years. Methods: A record linkage study using 45 and Up Study questionnaire data, MBS claims, PBS claims, Emergency Department visits, hospitalisations and deaths was undertaken. Participant characteristics at baseline (2006-2009) included demographics, health behaviours, social capital, functional status, and health conditions. Service characteristics included type of service, length of stay, location. Predictive models were developed to examine the participant/service characteristics with higher/lower service use over time. Results and Discussion: We identified 6,067 participants who were aged over 75 years in CES at baseline. Of these 59.0% had seen a GP 8 times or more in 2008, 19.6% had seen a specialist 8 times or more, 26.7% had attended an ED at least once, and 44.2% had been hospitalised at least once. In 2014 rates of GP use, specialist use and hospital admissions remained the same however ED visits had increased by 5%. This paper will discuss the different predictive models that were developed to describe service use. This paper will also provide the results from the predictive models and how this information is being/can be used to better plan and provide quality care for older people in CES. Limitations and suggestions for future research: Because the research study used an existing record linkage resource we were limited to the participant and service characteristics that were available. This research study would benefit from the inclusion on non-admitted data such as outpatient, community services and aged care services. References: 1- Browning C, Enticott J, Thomas S and Kendig H. 2017. Trajectories of ageing well among older Australians: a 16-year longitudinal study. Ageing and Society. 2017; 1-22. 2 -Korten AE, Jacomb PA, Jiao Z, Christensen H, Jorm AF, Henderson AS, Rodgers B. Predictors of GP service use: a community survey of an elderly Australian sample. Aust N Z J Public Health. 1998; 22: 609-615.

Introduction: In Australia there has been a sharp increase in the proportion of older people who live alone. Living alone increases the risk of being socially isolated or experiencing loneliness. Older people who are lonely have an increased risk of dying sooner and are more likely to experience a decline in their mobility [1]. Understanding if and how social isolation/loneliness impacts on managing health conditions and use of health services is important in providing quality care and preventing premature mortality. Living alone is not necessarily a predictor of social isolation/loneliness, rather lack of time spent with family or friend may be a better indicator. More supportive social relationships are related to a decreased mortality risk [2]. Research has been undertaken on the determinants of isolation/loneliness (individual, social, community and environment), however less emphasis has occurred on the medical determinants and how these might be mitigated. Using our existing data linkage resource, the Central and Eastern Sydney Primary and Community Health Cohort/Resource (CES-P&CH), which includes questionnaire data, primary care records, prescribing information, hospital records, emergency department records, cancer registry, and vital statistics on over 30,000 participants in CES aged 45 years and over we explored patterns of service use in people who are socially isolated. Methods: A record linkage study using 45 and Up Study questionnaire data, MBS claims, hospitalisations and deaths was undertaken. Social isolation was defined using a combination of baseline questionnaire data on living arrangements, family and friend support, and health issues that impacted on work/daily activities. Participant characteristics and health conditions at baseline (2006-2009) and health service use (including GP presentations, care plan use, and number and frequency of hospitalisations over the next 10 years) were compared for those who were defined as socially isolated versus those who were not using multivariate/time series models. Results and Discussion: At baseline 20% of participant lived alone; 30.8% had no partner; 18.5% had no children; 44.3% were not working; 4.9% regularly need help with daily tasks; 12.0% had severe physical limitations; 8.8% did not have support from family or friends; 9.6% were urinary incontinent, and 11.3% had depression or anxiety. These participants were included in the socially isolated group for the analysis if they had multiple risks. This paper will discuss the different algorithms that were developed to describe social isolation. This paper will also provide the results from the multivariate/time series models and how this information is being/can be used to better understand and provide person-centred quality care in CES. Limitations and suggestions for future research: Because the research study used an existing record linkage resource we were limited to the items that were included in the questionnaire to define social isolations. This research study would benefit from sensitivity testing of the resultant social isolation algorithm. References: 1- Perissinotto CM, Stijacic CI, Covinsky KE. Loneliness in older persons: a predictor of functional decline and death. Arch Intern Med 2012;172(14):1078-83. 2- Holt-Lunstad J, Smith TB, Layton JB. Social Relationships and Mortality Risk: A Meta-analytic Review. PLoS Med 2010;7(7): e1000316. doi:10.1371/journal.pmed.1000316

Effective, scalable dementia prevention interventions are needed to address modifiable risk factors given global burden of dementia and challenges in developing disease-modifying treatments. A single-blind randomized controlled trial assessed an online multidomain lifestyle intervention to prevent cognitive decline over 3 years. Participants were dementia-free community-dwelling Australians aged 55–77 years with modifiable dementia risk factors. Eligible participants ( n  = 6,104, 64% female) were randomized 1:1 to a personalized schedule of online coaching in two to four modules (targeting physical activity, nutrition, cognitive activity and depression or anxiety) or a control group that received module-eligible information only. At 3 years, the mean change in a global cognitive composite, the primary outcome, was met. The mean changes in z scores were 0.28 (95% confidence interval (CI): 0.25–0.32) for intervention, 0.10 (95% CI: 0.07–0.13) for control and 0.18 (95% CI: 0.13–0.23, P  < 0.001) for the between-group difference. Trial-related adverse events occurred in 19 (0.60%) intervention and 1 (0.03%) control participant. Randomization of this internet-delivered lifestyle intervention tailored to individual dementia risk factors resulted in significantly better cognition in older adults over 3 years. This intervention is scalable with the potential for population-level rollout that may delay cognitive decline in the general community. Australian New Zealand ClinicalTrials.gov registration: ACTRN12618000851268. An online tailored coaching intervention, delivered over 3 years, improved global cognition, dementia risk, physical activity, nutrition and depression in older dementia-free community-dwelling individuals.

Background The Maintain Your Brain (MYB) randomised controlled trial (RCT) examined the effect of a multi‐domain internet‐based dementia prevention program against a control group (information only) over three years among Australians aged 55‐77 years. A cost‐effective analysis (CEA) quantified the differences in costs (direct healthcare and program costs) and effectiveness outcomes between the intervention and control groups from a health care sector perspective. Method An economic evaluation was conducted alongside the MYB trial. The intervention comprised a personalised schedule of online coaching in physical activity, nutrition, cognitive activity, and depression or anxiety. MYB trial data were linked to the 45 and Up Study and administrative health data using uniquely assigned identifiers to obtain healthcare utilisation and costs data. The two effectiveness outcomes were global cognition composite (GCC) scores and the Australian‐National University Alzheimer’s Disease Risk Index (ANU‐ADRI) short form questionnaire scores. Costs analysed included MYB program costs and the direct healthcare costs of MYB participants. All costs were reported on actual nominal values in Australian dollars ( $AUD) during the trial period. The time horizon of this analysis was 3 years follow‐up after randomization. Incremental cost effectiveness ratio (ICERs) between the intervention and the control were calculated for GCC and ANU‐ADRI and compared using bootstrapped means and bias corrected and accelerated 95% Confidence Intervals. Result There were 3025 in the intervention group and 3033 in the control with available linked healthcare data. The average program cost per person was $ 1,572 for the intervention group and$538 for the control. Incremental cost‐effectiveness ratios at three years were calculated by comparing the average marginal difference in costs to a mean difference in z score of 0.18 (95%CI: 0.13, 0.23) and in ANU‐ADRI of ‐0.57 (95%CI: ‐0.95, ‐0.24) for the intervention versus control. The base case ICERs calculated were $ 2568 per 1 standard deviation in Z score and $823 per reduction of 1 ADRI point. After 1000 bootstrapped replications, the scatter‐plots of ICER ellipses suggests that the MYB intervention was effective and relatively cost‐neutral. Conclusion The MYB program showed potential cost‐effectiveness for preventing dementia. Longer‐term follow‐up is needed to confirm our initial findings.

Objectives. General practitioner (GP) follow-up after a hospital admission is an important indicator of integrated care. We examined the characteristics of patients who saw a GP within 2 weeks of hospital discharge in the Central and Eastern Sydney (CES) region, Australia, and the relationship between GP follow-up and subsequent hospitalisation. Methods. This data linkage study used a cohort of 10 240 people from the 45 and Up Study who resided in CES and experienced an overnight hospitalisation in the 5 years following recruitment (2007-14). Characteristics of participants who saw a GP within 2 weeks of discharge were compared with those who did not using generalised linear models. Time to subsequent hospitalisation was compared for the two groups using Cox proportional hazards regression models stratified by prior frequency of GP use. Results. Within 2 weeks of discharge, 64.3% participants saw a GP. Seeing a GP within 2 weeks of discharge was associated with lower rates of rehospitalisation for infrequent GP users (i.e. <8 visits in year before the index hospitalisation; hazard ratio (HR) 0.83; 95% confidence interval (CI) 0.70-0.97) but not frequent GP users (i.e. ≥8 plus visits; HR 1.02; 95% CI 0.90-1.17). Conclusion. The effect of seeing a GP on subsequent hospitalisation was protective but differed depending on patient care needs.

To describe the characteristics of people in Central and Eastern Sydney (CES), NSW, who had a General Practice Management Plan (GPMP) and claimed for at least one private allied health service item; and to examine if allied health service use results in less hospitalisations over a five-year period. The number of people living with chronic health conditions is increasing in Australia. The Chronic Disease Management programme was introduced to the Medicare Benefits Schedule (MBS) to provide a more structured approach to managing patients with chronic conditions and complex care needs. The programme supports general practitioners claiming up to one GPMP and one Team Care Arrangement every year, and the patient additionally claiming for up to five private allied health services visits. A prospective longitudinal study was conducted. The sample consisted of 5771 participants in CES who had a GPMP within a two-year health service utilisation baseline period (2007-2009). The analysis used the 45 and Up Study questionnaire data linked to the MBS, hospitalisation, death and emergency department data for the period 2006-2014. Of the eligible participants, 43% (2460) had at least one allied health service item claim in the subsequent 12 months. Allied health services were reported as physiotherapy, podiatry and other allied health services. The highest rates of allied health service use were among participants aged 85 years and over (49%). After controlling for confounding factors, a significant difference was found between having claimed for five or more physiotherapy services and emergency admissions (HR: 0.83; 95% CI: 0.72-0.95) and potentially preventable hospitalisations (HR: 0.79; 95% CI: 0.64-0.96) in the subsequent five years. Use of allied health service items was well targeted towards those with chronic and complex care needs, and use of physiotherapy services was associated with less avoidable hospitalisations.