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ObjectivesTo evaluate a multifaceted intervention on diet, physical activity and health literacy of overweight and obese patients attending primary care.DesignA pragmatic two-arm cluster randomised controlled trial.SettingUrban general practices in lower socioeconomic areas in Sydney and Adelaide.ParticipantsWe aimed to recruit 800 patients in each arm. Baseline assessment was completed by 215 patients (120 intervention and 95 control).InterventionA practice nurse-led preventive health check, a mobile application and telephone coaching.Primary and secondary outcome measuresPrimary outcomes were measured at baseline, 6 and 12 months, and included patient health and eHealth literacy, weight, waist circumference and blood pressure. Secondary outcomes included changes in diet and physical activity, preventive advice and referral, blood lipids, quality of life and costs. Univariate and multivariate analyses of difference-in-differences (DiD) estimates for each outcome were conducted.ResultsAt 6 months, the intervention group, compared with the control group, demonstrated a greater increase in Health Literacy Questionnaire domain 8 score (ability to find good health information; mean DiD 0.22; 95% CI 0.01 to 0.44). There were similar differences for domain 9 score (understanding health information well enough to know what to do) among patients below the median at baseline. Differences were reduced and non-statistically significant at 12 months. There was a small improvement in diet scores at 6 months (DiD 0.98 (0.50 to 1.47); p=0.026) but not at 12 months. There were no differences in eHealth literacy, physical activity scores, body mass index, weight, waist circumference or blood pressure.ConclusionsTargeted recruitment and engagement were challenging in this population. While the intervention was associated with some improvements in health literacy and diet, substantial differences in other outcomes were not observed. More intensive interventions and using codesign strategies to engage the practices earlier may produce a different result. Codesign may also be valuable when targeting lower socioeconomic populations.Trial registration numberAustralian New Zealand Clinical Trials Registry (ACTRN 12617001508369) (http://www.ANZCTR.org.au/ACTRN12617001508369.aspx).Trial protocolThe protocol for this trial has been published (open access;https://bmjopen.bmj.com/content/8/6/e023239).

There is anecdotal evidence that the rate of complaints and claims against doctors is rising, yet little is known about (Q1) which types of patients are more likely to make a complaint or claim, nor about (Q2) what interventions are effective in reducing rates of complaints and claims and increasing patient satisfaction. This Evidence Check aimed to answer those two questions. The evidence base for both of the questions was of low quality, with only five studies having a comparison group. Twenty-five studies addressed Question 1. The only patient characteristic to have a consistent effect on rates of complaints and claims was having a mental, behavioural or developmental disorder. Other patient characteristics, including those related to their therapeutic context, had inconsistent or weak relationships with rates of complaints and claims. Twenty studies addressed Question 2 (including one which addressed both questions). There were consistently reduced rates of complaints and claims following implementation of risk management programs and also implementation of communication and resolution programs. Peer feedback programs consistently improved doctors’ response to complaints and subsequent performance. However, the results found here should be interpreted with caution, as the risk of bias inherent in the study designs makes them more likely to erroneously demonstrate an effect.

Cancer incidence and survivorship are increasing worldwide. With more people living through and beyond cancer, there is a subsequent increase in their supportive care needs. This systematic review of qualitative studies aimed to describe the impacts of unmet supportive care needs on cancer survivors in Australia.Databases MEDLINE, EMBASE and Scopus were searched, and after screening and applying eligibility criteria, 27 qualitative studies were included. Findings were synthesised according to the Supportive Care Framework for Cancer Care, including informational, physical, practical, emotional, psychological, social and spiritual need domains.The systematic review identified impacts of unmet informational, physical, practical, emotional and psychological needs. Frequently identified impacts of unmet informational needs were feelings of abandonment and isolation, distress, confusion and regret. Common impacts of unmet physical and practical needs were financial burden and return-to-work difficulties. Over half of all unmet supportive care needs caused emotional and psychological impacts.Findings identify the detrimental emotional and psychological impacts resulting from a range of unmet supportive care needs. The review highlights the interconnections between supportive care need domains thereby enhancing the understanding of the impacts of unmet SCNs. Findings may inform policy and practice change to improve supportive cancer care.

Cancer is a leading cause of global morbidity and mortality, accounting for 250 Disability-Adjusted Life Years and 10 million deaths in 2019. Minimising unwarranted variation and ensuring appropriate cost-effective treatment across primary and tertiary care to improve health outcomes is a key health priority. There are few studies that have used linked data to explore healthcare utilisation prior to diagnosis in addition to post-diagnosis patterns of care. This protocol outlines the aims of the DaLECC project and key methodological features of the linked dataset. The primary aim of this project is to explore predictors of variations in pre- and post-cancer diagnosis care, and to explore the economic and health impact of any variation. The cohort of patients includes all South Australian residents diagnosed with cancer between 2011 and 2020, who were recorded on the South Australian Cancer Registry. These cancer registry records are being linked with state and national healthcare databases to capture health service utilisation and costs for a minimum of one-year prior to diagnosis and to a maximum of 10 years post-diagnosis. Healthcare utilisation includes state databases for inpatient separations and emergency department presentations and national databases for Medicare services and pharmaceuticals. Our results will identify barriers to timely receipt of care, estimate the impact of variations in the use of health care, and provide evidence to support interventions to improve health outcomes to inform national and local decisions to enhance the access and uptake of health care services.

Focus and outcomes for participants Modern technologies offer innovative ways of monitoring health outcomes. Electronic medical records (EMRs) stored in primary care databases provide comprehensive data on infectious and chronic conditions such as diagnosis, medications prescribed, vaccinations, laboratory results, and clinical assessments. Moreover, they allow the possibility of creating a retrospective cohort that can be tracked over time. This rich source of data can be used to generate results that support health policymakers to improve access, reduce health costs, and increase the quality of care. The symposium will discuss the use and future of routinely-collected EMR databases in monitoring health outcomes, using as an example studies based on the MedicineInsight program, a large general practice Australian database including more than 3.5 million patients. This symposium welcomes epidemiologists, researchers and health policymakers who are interested in primary care settings, big data analysis, and artificial intelligence. Rationale for the symposium, including for its inclusion in the Congress EMRs are becoming an important tool for monitoring health outcomes in different high-income countries and settings. However, most countries lack a national primary care database collating EMRs for research purposes. Monitoring of population health conditions is usually performed through surveys, surveillance systems, or census that tend to be expensive or performed over longer time intervals. In contrast, EMR databases are a useful and low-cost method to monitor health outcomes and have shown consistent results compared to other data sources. Although these databases only include individuals attending primary health settings, they tend to resemble the sociodemographic distribution from census data, as in countries such as Australia up to 90% of the population visit these services annually. Results from primary care-based EMRs can be used to inform practices and improve health policies. Analysis from EMRs can be used to identify, for example, those with undiagnosed medical conditions or patients who have not received recommended screenings or immunisations, therefore assessing the impact of government programmes. At a practice-level, healthcare staff can have better access to comprehensive patient histories, improving monitoring of people with certain conditions, such as chronic cardiac, respiratory, metabolic, neurological, or immunological diseases. This information provides feedback to primary care providers about the quality of their care and might help them develop targeted strategies for the most-needed areas or groups. Another benefit of EMRs is the possibility of using statistical modelling and machine learning to improve prediction of health outcomes and medical management, supporting general practitioners with decision making on the best management approach. In Australia, the MedicineInsight program is a large general practice database that since 2011 has been routinely collecting information from over 650 general practices varying in size, billing methods, and type of services offered, and from all Australian states and regions. In the last few years, diverse researchers have used MedicineInsight to investigate infectious and chronic diseases, immunization coverage, prescribed medications, medical management, and temporal trends in primary care. Despite being initially created for monitoring how medicines and medical tests are used, MedicineInsight has overcome some of the legal, ethical, social and resource-related barriers associated with the use of EMRs for research purposes through the involvement of a data governance committee responsible for the ethical, privacy and security aspects of any research using this data, and through applying data quality criteria to their data extraction. This symposium will discuss advances in the use of primary care databases for monitoring health outcomes using as an example the research activities performed based on the Australian MedicineInsight program. These discussions will also cover challenges in the use of this database and possible methodological innovations, such as statistical modelling or machine learning, that could be used to improve monitoring of the epidemiology and management of health conditions. Presentation program The use of large general practice databases for monitoring health outcomes in Australia: infectious and chronic conditions (Professor Nigel Stocks) How routinely collected electronic health records from MedicineInsight can help inform policy, research and health systems to improve health outcomes (Ms Rachel Hayhurst) Influenza-like illness in Australia: how can we improve surveillance systems in Australia using electronic medical records? (Dr Carla Bernardo) Long term use of opioids in Australian general practice (Dr David Gonzalez) Using routinely collected electronic health records to evaluate Quality Use of Medicines for women’s reproductive health (Dr Luke Grzeskowiak) The use of electronic medical records and machine learning to identify hypertensive patients and factors associated with controlled hypertension (Ms Jackie Roseleur) Names of presenters Professor Nigel Stocks, The University of Adelaide Ms Rachel Hayhurst, NPS MedicineWise Dr Carla Bernardo, The University of Adelaide Dr David Gonzalez-Chica, The University of Adelaide Dr Luke Grzeskowiak, The University of Adelaide Ms Jackie Roseleur, The University of Adelaide