Comprehensive observational study evaluating the enduring effectiveness of 4CMenB, the meningococcal B vaccine against gonococcal infections in the Northern Territory and South Australia, Australia: study protocol.

INTRODUCTION: The effectiveness of antibiotics for treating gonococcal infections is compromised due to escalating antibiotic resistance; and the development of an effective gonococcal vaccine has been challenging. Emerging evidence suggests that the licensed meningococcal B (MenB) vaccine, 4CMenB is effective against gonococcal infections due to cross-reacting antibodies and 95% genetic homology between the two bacteria, Neisseria meningitidis and Neisseria gonorrhoeae, that cause the diseases. This project aims to undertake epidemiological and genomic surveillance to evaluate the long-term protection of the 4CMenB vaccine against gonococcal infections in the Northern Territory (NT) and South Australia (SA), and to determine the potential benefit of a booster vaccine doses to provide longer-term protection against gonococcal infections. METHODS AND ANALYSES: This observational study will provide long-term evaluation results of the effectiveness of the 4CMenB vaccine against gonococcal infections at 4-7 years post 4CMenB programme implementation. Routine notifiable disease notifications will be the basis for assessing the impact of the vaccine on gonococcal infections. Pathology laboratories will provide data on the number and percentage of N. gonorrhoeae positive tests relative to all tests administered and will coordinate molecular sequencing for isolates. Genome sequencing results will be provided by SA Pathology and Territory Pathology/New South Wales Health Pathology, and linked with notification data by SA Health and NT Health. There are limitations in observational studies including the potential for confounding. Confounders will be analysed separately for each outcome/comparison. ETHICS AND DISSEMINATION: The protocol and all study documents have been reviewed and approved by the SA Department for Health and Well-being Human Research Ethics Committee (HREC/2022/HRE00308), and the evaluation will commence in the NT on receipt of approval from the NT Health and Menzies School of Health Research Human Research Ethics Committee. Results will be published in peer-reviewed journals and presented at scientific meetings and public forums.

A Prototype Software Framework for Transferable Computational Health Economic Models and Its Early Application in Youth Mental Health.

We are developing an economic model to explore multiple topics in Australian youth mental health policy. To help make that model more readily transferable to other jurisdictions, we developed a software framework for authoring modular computational health economic models (CHEMs) (the software files that implement health economic models). We specified framework user requirements for: a simple programming syntax; a template CHEM module; tools for authoring new CHEM modules; search tools for finding existing CHEM modules; tools for supplying CHEM modules with data; reproducible analysis and reporting tools; and tools to help maintain a CHEM project website. We implemented the framework as six development version code libraries in the programming language R that integrate with online services for software development and research data archiving. We used the framework to author five development version R libraries of CHEM modules focussed on utility mapping in youth mental health. These modules provide tools for variable validation, dataset description, multi-attribute instrument scoring, construction of mapping models, reporting of mapping studies and making out of sample predictions. We assessed these CHEM module libraries as mostly meeting transparency, reusability and updatability criteria that we have previously developed, but requiring more detailed documentation and unit testing of individual modules. Our software framework has potential value as a prototype for future tools to support the development of transferable CHEMs.Code: Visit https://www.ready4-dev.com for more information about how to find, install and apply the prototype software framework.

Process mining and customer journey mapping in healthcare: Enhancing patient-centred care in stroke rehabilitation.

Background: Patient-centred care and enhancing patient experience is a priority across Australia. Stroke rehabilitation has multiple consumer touchpoints that would benefit from a better understanding of customer journeys, subsequently impacting better patient-centred care, and contributing to process improvements and better patient outcomes. Customer journey mapping through process mining extracts process data from event logs in existing information systems discovering patient journeys, which can be utilized to monitor guideline compliance and uncover nonconformance. Methodology: Utilizing process mining and variant analysis, customer journey maps were developed for 130 stroke rehabilitation patients from referral to discharge. In total, 168 cases from the Australasian Rehabilitation Outcomes Centre dataset were matched with 6291 cases from inpatient stroke data. Variants were explored for age, gender, outcome measures, length of stay and functional independence measure (FIM) change. Results: The study illustrated the process, process variants and patient journey map in stroke rehabilitation. Process characteristics of stroke rehabilitation patients were extracted and represented utilizing process mining and results highlighted process variation, attributes, touchpoints and timestamps across stroke rehabilitation patient journeys categorized by patient demographics and outcome variables. Patients demonstrated a mean and median duration of 49.5 days and 44 days, respectively, across the patient journeys. Nine variants were discovered, with 78.46% (n = 102) of patients following the expected sequence of activities in their stroke rehabilitation patient journey. Relationships involving age, gender, length of stay and FIM change along the patient journeys were evident, with four cases experiencing stroke rehabilitation journeys of more than 100 days, warranting further investigation. Conclusion: Process mining can be utilized to visualize and analyse patient journeys and identify gaps in service quality, thus contributing to better patient-centred care and improved patient outcomes and experiences in stroke rehabilitation.

Models for delivery and co-ordination of primary or secondary health care (or both) to older adults living in aged care facilities.

BACKGROUND: The number of older people is increasing worldwide and public expenditure on residential aged care facilities (ACFs) is expected to at least double, and possibly triple, by 2050. Co-ordinated and timely care in residential ACFs that reduces unnecessary hospital transfers may improve residents' health outcomes and increase satisfaction with care among ACF residents, their families and staff. These benefits may outweigh the resources needed to sustain the changes in care delivery and potentially lead to cost savings. Our systematic review comprehensively and systematically presents the available evidence of the effectiveness, safety and cost-effectiveness of alternative models of providing health care to ACF residents. OBJECTIVES: Main objective To assess the effectiveness and safety of alternative models of delivering primary or secondary health care (or both) to older adults living in ACFs. Secondary objective To assess the cost-effectiveness of the alternative models. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, five other databases and two trials registers (WHO ICTRP, ClinicalTrials.gov) on 26 October 2022, together with reference checking, citation searching and contact with study authors to identify additional studies. SELECTION CRITERIA: We included individual and cluster-randomised trials, and cost/cost-effectiveness data collected alongside eligible effectiveness studies. Eligible study participants included older people who reside in an ACF as their place of permanent abode and healthcare professionals delivering or co-ordinating the delivery of healthcare at ACFs. Eligible interventions focused on either ways of delivering primary or secondary health care (or both) or ways of co-ordinating the delivery of this care. Eligible comparators included usual care or another model of care. Primary outcomes were emergency department visits, unplanned hospital admissions and adverse effects (defined as infections, falls and pressure ulcers). Secondary outcomes included adherence to clinical guideline-recommended care, health-related quality of life of residents, mortality, resource use, access to primary or specialist healthcare services, any hospital admissions, length of hospital stay, satisfaction with the health care by residents and their families, work-related satisfaction and work-related stress of ACF staff. DATA COLLECTION AND ANALYSIS: Two review authors independently selected studies for inclusion, extracted data, and assessed risk of bias and certainty of evidence using GRADE. The primary comparison was any alternative model of care versus usual care. MAIN RESULTS: We included 40 randomised trials (21,787 participants; three studies only reported number of beds) in this review. Included trials evaluated alternative models of care aimed at either all residents of the ACF (i.e. no specific health condition; 11 studies), ACF residents with mental health conditions or behavioural problems (12 studies), ACF residents with a specific condition (e.g. residents with pressure ulcers, 13 studies) or residents requiring a specific type of care (e.g. residents after hospital discharge, four studies). Most alternative models of care focused on 'co-ordination of care' (n = 31). Three alternative models of care focused on 'who provides care' and two focused on 'where care is provided' (i.e. care provided within ACF versus outside of ACF). Four models focused on the use of information and communication technology. Usual care, the comparator in all studies, was highly heterogeneous across studies and, in most cases, was poorly reported. Most of the included trials were susceptible to some form of bias; in particular, performance (89%), reporting (66%) and detection (42%) bias. Compared to usual care, alternative models of care may make little or no difference to the proportion of residents with at least one emergency department visit (risk ratio (RR) 1.01, 95% confidence interval (CI) 0.84 to 1.20; 7 trials, 1276 participants; low-certainty evidence), but may reduce the proportion of residents with at least one unplanned hospital admission (RR 0.74, 95% CI 0.56 to 0.99, I2 = 53%; 8 trials, 1263 participants; low-certainty evidence). We are uncertain of the effect of alternative models of care on adverse events (proportion of residents with a fall: RR 1.15, 95% CI 0.83 to 1.60, I² = 74%; 3 trials, 1061 participants; very low-certainty evidence) and adherence to guideline-recommended care (proportion of residents receiving adequate antidepressant medication: RR 5.29, 95% CI 1.08 to 26.00; 1 study, 65 participants) as the certainty of the evidence is very low. Compared to usual care, alternative models of care may have little or no effect on the health-related quality of life of ACF residents (MD -0.016, 95% CI -0.036 to 0.004; I² = 23%; 12 studies, 4016 participants; low-certainty evidence) and probably make little or no difference to the number of deaths in residents of ACFs (RR 1.03, 95% CI 0.92 to 1.16, 24 trials, 3881 participants, moderate-certainty evidence). We did not pool the cost-effectiveness or cost data as the specific costs associated with the various alternative models of care were incomparable, both across models of care as well as across settings. Based on the findings of five economic evaluations (all interventions focused on co-ordination of care), we are uncertain of the cost-effectiveness of alternative models of care compared to usual care as the certainty of the evidence is very low. AUTHORS' CONCLUSIONS: Compared to usual care, alternative models of care may make little or no difference to the number of emergency department visits but may reduce unplanned hospital admissions. We are uncertain of the effect of alternative care models on adverse events (i.e. falls, pressure ulcers, infections) and adherence to guidelines compared to usual care, as the certainty of the evidence is very low. Alternative models of care may have little or no effect on health-related quality of life and probably have no effect on mortality of ACF residents compared to usual care. Importantly, we are uncertain of the cost-effectiveness of alternative models of care due to the limited, disparate data available.

Nudging towards COVID-19 and influenza vaccination uptake in medically at-risk children: EPIC study protocol of randomised controlled trials in Australian paediatric outpatient clinics.

INTRODUCTION: Children with chronic medical diseases are at an unacceptable risk of hospitalisation and death from influenza and SARS-CoV-2 infections. Over the past two decades, behavioural scientists have learnt how to design non-coercive 'nudge' interventions to encourage positive health behaviours. Our study aims to evaluate the impact of multicomponent nudge interventions on the uptake of COVID-19 and influenza vaccines in medically at-risk children. METHODS AND ANALYSES: Two separate randomised controlled trials (RCTs), each with 1038 children, will enrol a total of approximately 2076 children with chronic medical conditions who are attending tertiary hospitals in South Australia, Western Australia and Victoria. Participants will be randomly assigned (1:1) to the standard care or intervention group. The nudge intervention in each RCT will consist of three text message reminders with four behavioural nudges including (1) social norm messages, (2) different messengers through links to short educational videos from a paediatrician, medically at-risk child and parent and nurse, (3) a pledge to have their child or themselves vaccinated and (4) information salience through links to the current guidelines and vaccine safety information. The primary outcome is the proportion of medically at-risk children who receive at least one dose of vaccine within 3 months of randomisation. Logistic regression analysis will be performed to determine the effect of the intervention on the probability of vaccination uptake. ETHICS AND DISSEMINATION: The protocol and study documents have been reviewed and approved by the Women's and Children's Health Network Human Research Ethics Committee (HREC/22/WCHN/2022/00082). The results will be published via peer-reviewed journals and presented at scientific meetings and public forums. TRIAL REGISTRATION NUMBER: NCT05613751.

Using Expert Elicitation to Adjust Published Intervention Effects to Reflect the Local Context.

Background. Local health services make limited use of economic evaluation to inform decisions to fund new health service interventions. One barrier is the relevance of published intervention effects to the local setting, given these effects can strongly reflect the original evaluation context. Expert elicitation methods provide a structured approach to explicitly and transparently adjust published effect estimates, which can then be used in local-level economic evaluations to increase their local relevance. Expert elicitation was used to adjust published effect estimates for 2 interventions targeting the prevention of inpatient hypoglycemia. Methods. Elicitation was undertaken with 6 clinical experts. They were systematically presented with information regarding potential differences in patient characteristics and quality of care between the published study and local contexts, and regarding the design and application of the published study. The experts then assessed the intervention effects and provided estimates of the most realistic, most pessimistic, and most optimistic intervention effect sizes in the local context. Results. The experts estimated both interventions would be less effective in the local setting compared with the published effect estimates. For one intervention, the experts expected the lower complexity of admitted patients in the local setting would reduce the intervention's effectiveness. For the other intervention, the reduced effect was largely driven by differences in the scope of implementation (hospital-wide in the local setting compared with targeted implementation in the evaluation). Conclusions. The pragmatic elicitation methods reported in this article provide a feasible and acceptable approach to assess and adjust published intervention effects to better reflect expected effects in the local context. Further development and application of these methods is proposed to facilitate the use of local-level economic evaluation. Highlights: Local health services make limited use of economic evaluation to inform their decisions on the funding of new health service interventions. One barrier to use is the relevance of published intervention evaluations to the local setting.Expert elicitation methods provide a structured way to consider differences between the evaluation and local settings and to explicitly and transparently adjust published effect estimates for use in local economic evaluations.The pragmatic elicitation methods reported in this article offer a feasible and acceptable approach to adjusting published intervention effects to better reflect the effects expected in the local context. This increases the relevance of economic evaluations for local decision makers.

Local Level Economic Evaluation: What is it? What is its Value? Is it Sustainable?

In Australia, local health services with allocated budgets manage public hospital services for defined geographical areas. The authors were embedded in a local health service for around 2 years and undertook a range of local level economic evaluations for which three decision contexts were defined: intervention development, post-implementation and prioritisation. Despite difficulties in estimating opportunity costs and in the relevance of portfolio-based prioritisation approaches, economic evaluation added value to local decision-making. Development-focused (ex ante) economic evaluations used expert elicitation and calibration methods to synthesise published evidence with local health systems data to evaluate interventions to prevent hospital acquired complications. The use of economic evaluation facilitated the implementation of interventions with additional resource requirements. Decision analytic models were used alongside the implementation of larger scale, more complex service interventions to estimate counterfactual patient pathways, costs and outcomes, providing a transparent alternative to the statistical analyses of intervention effects, which were subject to high risk of bias. Economic evaluations of more established services had less impact due to data limitations and lesser executive interest. Prioritisation-focused economic evaluations compared costs, outcomes and processes of care for defined patient populations across alternative local health services to identify, understand and quantify the effects of unwarranted variation to inform priority areas for improvement within individual local health services. The sustained use of local level economic evaluation could be supported by embedding health economists in local continuous improvement units, perhaps with an initial focus on supporting the development and evaluation of prioritised new service interventions. Shared resources and critical mass are important, which could be facilitated through groups of embedded economists with joint appointments between different local health services and the same academic institution.

A framework for local-level economic evaluation to inform implementation decisions: health service interventions to prevent hospital-acquired hypoglycemia.

OBJECTIVES: Published evidence on health service interventions should inform decision-making in local health services, but primary effectiveness studies and cost-effectiveness analyses are unlikely to reflect contexts other than those in which the evaluations were undertaken. A ten-step framework was developed and applied to use published evidence as the basis for local-level economic evaluations that estimate the expected costs and effects of new service intervention options in specific local contexts. METHODS: Working with a multidisciplinary group of local clinicians, the framework was applied to evaluate intervention options for preventing hospital-acquired hypoglycemia. The framework included: clinical audit and analyses of local health systems data to understand the local context and estimate baseline event rates; pragmatic literature review to identify evidence on relevant intervention options; expert elicitation to adjust published intervention effect estimates to reflect the local context; and modeling to synthesize and calibrate data derived from the disparate data sources. RESULTS: From forty-seven studies identified in the literature review, the working group selected three interventions for evaluation. The local-level economic evaluation generated estimates of intervention costs and a range of cost, capacity and patient outcome-related consequences, which informed working group recommendations to implement two of the interventions. CONCLUSIONS: The applied framework for modeled local-level economic evaluation was valued by local stakeholders, in particular the structured, formal approach to identifying and interpreting published evidence alongside local data. Key methodological issues included the handling of alternative reported outcomes and the elicitation of the expected intervention effects in the local context.

Prevalence of unmet supportive care needs reported by individuals ever diagnosed with cancer in Australia: a systematic review to support service prioritisation.

PURPOSE: Improved health outcomes for individuals ever diagnosed with cancer require comprehensive, coordinated care that addresses their supportive care needs. Implementing interventions to address these is confounded by a lack of evidence on population needs and a large pool of potential interventions. This systematic review estimates the point prevalence of different supportive care needs stratified by the tool used to measure needs and cancer type in Australia. METHODS: We searched MEDLINE, Embase, and Scopus from 2010 to April 2023 to identify relevant studies published on the prevalence of supportive care needs in Australia. RESULTS: We identified 35 studies that met the inclusion criteria. The highest prevalent unmet need across all cancers was 'fear of cancer spreading' (20.7%) from the Supportive Care Needs Survey Short-Form 34 (SCNS-SF34), ranging from 9.4% for individuals ever diagnosed with haematological cancer to 36.3% for individuals ever diagnosed with gynaecological cancer, and 'concerns about cancer coming back' (17.9%) from the Cancer Survivors' Unmet Needs (CaSUN), ranging from 9.7% for individuals ever diagnosed with prostate cancer to 37.8% for individuals ever diagnosed with breast cancer. Two studies assessed needs in Aboriginal and Torres Strait Islander populations, reporting the highest needs for financial worries (21.1%). CONCLUSIONS: Point prevalence estimates presented here, combined with estimates of the costs and effects of potential interventions, can be used within economic evaluations to inform evidence-based local service provision to address the supportive care needs of individuals ever diagnosed with cancer. IMPLICATIONS FOR CANCER SURVIVORS: Local health services can use local evidence to prioritise the implementation of interventions targeted at unmet needs.

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.

The fraction of life years lost after diagnosis (FLYLAD): a person-centred measure of cancer burden.

BACKGROUND: Cancer control initiatives are informed by quantifying the capacity to reduce cancer burden through effective interventions. Burden measures using health administrative data are a sustainable way to support monitoring and evaluating of outcomes among patients and populations. The Fraction of Life Years Lost After Diagnosis (FLYLAD) is one such burden measure. We use data on Aboriginal and non-Aboriginal South Australians from 1990 to 2010 to show how FLYLAD quantifies disparities in cancer burden: between populations; between sub-population cohorts where stage at diagnosis is available; and when follow-up is constrained to 24-months after diagnosis. METHOD: FLYLADcancer is the fraction of years of life expectancy lost due to cancer (YLLcancer) to life expectancy years at risk at time of cancer diagnosis (LYAR) for each person. The Global Burden of Disease standard life table provides referent life expectancies. FLYLADcancer was estimated for the population of cancer cases diagnosed in South Australia from 1990 to 2010. Cancer stage at diagnosis was also available for cancers diagnosed in Aboriginal people and a cohort of non-Aboriginal people matched by sex, year of birth, primary cancer site and year of diagnosis. RESULTS: Cancers diagnoses (N = 144,891) included 777 among Aboriginal people. Cancer burden described by FLYLADcancer was higher among Aboriginal than non-Aboriginal (0.55, 95% CIs 0.52-0.59 versus 0.39, 95% CIs 0.39-0.40). Diagnoses at younger ages among Aboriginal people, 7 year higher LYAR (31.0, 95% CIs 30.0-32.0 versus 24.1, 95% CIs 24.1-24.2) and higher premature cancer mortality (YLLcancer = 16.3, 95% CIs 15.1-17.5 versus YLLcancer = 8.2, 95% CIs 8.2-8.3) influenced this. Disparities in cancer burden between the matched Aboriginal and non-Aboriginal cohorts manifested 24-months after diagnosis with FLYLADcancer 0.44, 95% CIs 0.40-0.47 and 0.28, 95% CIs 0.25-0.31 respectively. CONCLUSION: FLYLAD described disproportionately higher cancer burden among Aboriginal people in comparisons involving: all people diagnosed with cancer; the matched cohorts; and, within groups diagnosed with same staged disease. The extent of disparities were evident 24-months after diagnosis. This is evidence of Aboriginal peoples' substantial capacity to benefit from cancer control initiatives, particularly those leading to earlier detection and treatment of cancers. FLYLAD's use of readily available, person-level administrative records can help evaluate health care initiatives addressing this need.

Outcomes of completed quality activities in an Australian tertiary hospital, 2015-2019.

Quality activities including quality assurance and quality improvement are an integral part of safety and quality governance for hospitals. Previous studies identified that (i) majority are for quality assurance and knowledge-acquiring purposes and (ii) adherence to the quality cycle as well as impact on patient-related outcomes at the hospital level are unclear, neither associated with costs. This study aims to (i) assess adherence to the quality cycle for quality activities in a large Australian tertiary hospital; (ii) report outcomes of quality activities at the hospital level, including impact on patient-related outcomes measured by the occurrence of hospital-acquired complications; and (iii) estimate time and costs for data collection. This quantitative study utilized three data sources. First is the hospital's electronic quality management system, Governance, Evidence, Knowledge and Outcome that identifies completed quality activities over a 5-year period; second is Tableau dashboards for hospital-acquired complication performance; third is Microsoft Teams Forms used to capture time of data collection for bedside observations and retrospective notes reviews. Median sample size and median hourly rates in 2018 were used for calculations. A total of 1768 quality activities were completed over a 5-year period representing an average of 353 quality activities per year, of which 87.8% were initiated by clinicians and 12.2% planned and coordinated by safety and quality or equivalent. The activity reports indicated that less than a fifth (17.1%) brought about improvement in process measures and only 7.1% improved outcome measures. Two-thirds of the quality activities (66.3%) provided recommendations based on their findings, but evidence of action plan was available in 14.1% of the reports only. No association was found between the number of activities completed and overall hospital-acquired complication performance. Retrospective data collection (64.7%) was common. The estimated time and cost for data collection averaged at 3490 h/year, equivalent to 1.8 full-time employees, for a cost of $171 000 at the nursing rate (A$49.0), $280 000 at the medical rate (A$79.5), and $200 000 at the Health Service Union rate (A$58.9). Most quality activities were clinician-initiated. Implementing change and achieving and sustaining improvement were the two challenging stages in the quality cycle. No clear association was observed between activities completed and improvement in patient-related outcomes although some improvement in processes. A paradigm shift may be needed to engineer quality activities in hospitals to be more outcome-oriented. Opportunities exist for hospitals to consider how quality activities can be organized to maximize returns from investment.

Development and validation of an individual-based state-transition model for the prediction of frailty and frailty-related events.

Frailty is a biological syndrome that is associated with increased risks of morbidity and mortality. To assess the value of interventions to prevent or manage frailty, all important impacts on costs and outcomes should be estimated. The aim of this study is to describe the development and validation of an individual-based state transition model that predicts the incidence and progression of frailty and frailty-related events over the remaining lifetime of older Australians. An individual-based state transition simulation model comprising integrated sub models that represent the occurrence of seven events (mortality, hip fracture, falls, admission to hospital, delirium, physical disability, and transitioning to residential care) was developed. The initial parameterisation used data from the Survey of Health, Ageing, and Retirement in Europe (SHARE). The model was then calibrated for an Australian population using data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey. The simulation model established internal validity with respect to predicting outcomes at 24 months for the SHARE population. Calibration was required to predict longer terms outcomes at 48 months in the SHARE and HILDA data. Using probabilistic calibration methods, over 1,000 sampled sets of input parameter met the convergence criteria across six external calibration targets. The developed model provides a tool for predicting frailty and frailty-related events in a representative community dwelling Australian population aged over 65 years and provides the basis for economic evaluation of frailty-focussed interventions. Calibration to outcomes observed over an extended time horizon would improve model validity.

Randomised controlled trials of behavioural nudges delivered through text messages to increase influenza and COVID-19 vaccines among pregnant women (the EPIC study): study protocol.

BACKGROUND: Influenza and COVID-19 infections during pregnancy may have serious adverse consequences for women as well as their infants. However, uptake of influenza and COVID-19 vaccines during pregnancy remains suboptimal. This study aims to assess the effectiveness of a multi-component nudge intervention to improve influenza and COVID-19 vaccine uptake among pregnant women. METHODS: Pregnant women who receive antenatal care at five tertiary hospitals in South Australia, Western Australia and Victoria will be recruited to two separate randomised controlled trials (RCTs). Women will be eligible for the COVID-19 RCT is they have received two or less doses of a COVID-19 vaccine. Women will be eligible for the influenza RCT if they have not received the 2023 seasonal influenza vaccine. Vaccination status at all stages of the trial will be confirmed by the Australian Immunisation Register (AIR). Participants will be randomised (1:1) to standard care or intervention group (n = 1038 for each RCT). The nudge intervention in each RCT will comprise three SMS text message reminders with links to short educational videos from obstetricians, pregnant women and midwives and vaccine safety information. The primary outcome is at least one dose of a COVID-19 or influenza vaccine during pregnancy, as applicable. Logistic regression will compare the proportion vaccinated between groups. The effect of treatment will be described using odds ratio with a 95% CI. DISCUSSION: Behavioural nudges that facilitate individual choices within a complex context have been successfully used in other disciplines to stir preferred behaviour towards better health choices. If our text-based nudges prove to be successful in improving influenza and COVID-19 vaccine uptake among pregnant women, they can easily be implemented at a national level. TRIAL REGISTRATION: ClinicalTrials.gov Identifier NCT05613751. Registered on November 14, 2022.

DAta Linkage to Enhance Cancer Care (DaLECC): Protocol of a Large Australian Data Linkage Study.

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.

Strict Lockdown versus Flexible Social Distance Strategy for COVID-19 Disease: a Cost-Effectiveness Analysis.

Objectives: To balance the costs and effects comparing a strict lockdown versus a flexible social distancing strategy for societies affected by Coronavirus-19 Disease (COVID-19). Design: Cost-effectiveness analysis. Participants: We used societal data and COVID-19 mortality rates from the public domain. Interventions: The intervention was a strict lockdown strategy that has been followed by Denmark. Reference strategy was flexible social distancing policy as was applied by Sweden. We derived mortality rates from COVID-19 national statistics, assumed the expected life years lost from each COVID-19 death to be 11 years and calculated lost life years until 31st August 2020. Expected economic costs were derived from gross domestic productivity (GDP) statistics from each country's official statistics bureau and forecasted GDP. The incremental financial costs of the strict lockdown were calculated by comparing Sweden with Denmark using externally available market information. Calculations were projected per one million inhabitants. In sensitivity analyses we varied the total cost of the lockdown (range -50% to +100%). Main Outcome Measure: Financial costs per life years saved. Results: In Sweden, the number of people who died with COVID-19 was 577 per million inhabitants, resulting in an estimated 6,350 life years lost per million inhabitants. In Denmark, where a strict lockdown strategy was installed for months, the number of people dying with COVID-19 was on average 111 per million, resulting in an estimated 1,216 life years per million inhabitants lost. The incremental costs of strict lockdown to save one life year was US$ 137,285, and higher in most of the sensitivity analyses. Conclusions: Comparisons of public health interventions for COVID-19 should take into account life years saved and not only lost lives. Strict lockdown costs more than US$ 130,000 per life year saved. As our all our assumptions were in favour of strict lockdown, a flexible social distancing policy in response to COVID19 is defendable.

The Cost of Uncontrolled Blood Pressure in Australian General Practice: A Modelling Study Using Electronic Health Records (MedicineInsight).

BACKGROUND: Hypertension is the most common condition seen in Australian general practice. Despite hypertension being amenable to lifestyle modifications and pharmacological treatment, only around half of these patients have controlled blood pressure levels (< 140/90 mmHg), placing them at an increased risk of cardiovascular disease. OBJECTIVE: We aimed to estimate the health and acute hospitalisation costs of uncontrolled hypertension among patients attending general practice. METHODS: We used population data and electronic health records from 634,000 patients aged 45-74 years who regularly attended an Australian general practice between 2016 and 2018 (MedicineInsight database). An existing worksheet-based costing model was adapted to calculate the potential cost savings for acute hospitalisation of primary cardiovascular disease events by reducing the risk of a cardiovascular event over the next 5 years through improved systolic blood pressure control. The model estimated the number of expected cardiovascular disease events and associated acute hospital costs under current levels of systolic blood pressure and compared this estimate with the expected number of cardiovascular disease events and costs under different levels of systolic blood pressure control. RESULTS: The model estimated that across all Australians aged 45-74 years who visit their general practitioner (n = 8.67 million), 261,858 cardiovascular disease events can be expected over the next 5 years at current systolic blood pressure levels (mean 137.8 mmHg, standard deviation = 12.3 mmHg), with a cost of AUD$1813 million (in 2019-20). By reducing the systolic blood pressure of all patients with a systolic blood pressure greater than 139 mmHg to 139 mmHg, 25,845 cardiovascular disease events could be avoided with an associated reduction in acute hospital costs of AUD$179 million. If systolic blood pressure is lowered further to 129 mmHg for all those with systolic blood pressure greater than 129 mmHg, 56,169 cardiovascular disease events could be avoided with potential cost savings of AUD$389 million. Sensitivity analyses indicate that potential cost savings range from AUD$46 million to AUD$1406 million and AUD$117 million to AUD$2009 million for the two scenarios, respectively. Cost savings by practice range from AUD$16,479 for small practices to AUD$82,493 for large practices. CONCLUSIONS: The aggregate cost effects of poor blood pressure control in primary care are high, but cost implications at the individual practice level are modest. The potential cost savings improve the potential to design cost-effective interventions, but such interventions may be best targeted at a population level rather than at individual practices.