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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

Introduction: The Healthy Homes and Neighbourhoods (HHAN) integrated care program seeks to enhance vulnerable family access to, and engagement with, health and social services. This is achieved through a care-coordination model and other integrated care activities targeted towards capacity building at the professional and organisational level. The initiative is supported by a multiagency steering committee comprised of representatives from local government and non-government agencies who are responsible for the provision of a range of health, social and education services to the community. This study, conducted early in the HHAN implementation phase, sought to build consensus from service partners and staff on what was working, not working, areas of improvement and training needs of the program to ensure effective service delivery and ultimately better outcomes for families. Methods: A three stage process was undertaken, according to a Delphi method: Stage 1: A representative from 15 HHAN-partnered organisations were interviewed and asked to comment on what was working, not working, areas for improvement and training needs. Staff involved in this project were also interviewed. Interviews were transcribed and thematically analysed. Stage 2: Participants were then asked to rank these themes in order of importance. These responses were analysed, collated and fed back to participants. Stage 3: Participants were then asked to re-rank the most commonly identifies themes in order of importance. Results: What is working: Findings suggest that service delivery is flexible and innovative and consequently allows access to a wider range of services, joint multidisciplinary assessments, ‘soft’ entry points and assertive follow-up. What is not working: Findings suggest that the shift in delivery of services has resulted in tension as organisations adapt to a new professional culture that involves novel information-sharing methods, common language and protocol development, role clarity and change sustainment. Areas for improvement: Findings reflected two major themes: 1. Strengthening adaptive processes by improving access to protocols, promoting a shared vernacular and process and recognising that change causes professional and organisation discomfort; and 2. Improving models of care by encouraging utilisation of a breadth of integrated strategies such as step-down or exit pathways for clients. Training: Findings reflected adaptive processes including additional support, training and supervision, experience in joint planning and case conferencing, and contact with other services. These processes facilitate knowledge of available resources in the health sector. Discussion: This study suggests tension and debate should be expected between and within organisations involved in attempting to integrate care. Novel processes are adopted and organisations are required to adjust to shifting workplace culture. Limitations and suggestions for further research: It is unknown if participants ranked issues based on personal rather than organisational priorities, introducing a source of reporting bias. Involvement of researchers in organisational change may assist in developing a theoretical basis of how individuals and services can be supported to integrate care.

Can Get Health in Canterbury (CGHiC) is a locality-based project that aims to improve health and reduce inequities for marginalised culturally and linguistically diverse groups by increasing access to comprehensive primary health care services and addressing the underlying social determinants of health in a socio-economically disadvantaged Local Government Area in Sydney, Australia. CGHiC project has undertaken to increase the power of marginalised population groups to participate in and influence decisions affecting their health. There is evidence that marginalised communities require space in which to develop and agree on items that they wish to place on the public agenda of the health sector; representation (by right, rather than by invitation) in decision-making spaces; and capacity to influence policy decisions. CGHIC is working with Rohingya refugees and asylum seekers to evaluate a collective control initiative modelled on the Big Local in the United Kingdom. An initiative that aims to support communities to have more collective control over which defining issues to address and how to address them. Community engagement underpinned the preparatory work and included a Zoo trip to build trust and develop relationships and a community consultation that used story boards to understand the communities’ health priorities. To offer a longitudinal perspective semi-structured interviews will be conducted with a purposeful sample of stakeholders to evaluate the impact on social relationship and cohesion, skill development and improvements in community assets. Interviews will be conducted in two time points (Month 6 and Month 12). This paper will describe the work currently being done by CGHiC with the Rohingya’s and early evaluation findings.