Utilization and cost of non-insulin glucose-lowering drugs in Australia from 2013 to 2023.

OBJECTIVES: To investigate the utilization and costs of non-insulin glucose-lowering drugs (GLDs) in Australia from 2013 to 2023. MATERIALS AND METHODS: We conducted a retrospective analysis of the Australian Pharmaceutical Benefits Scheme (PBS) administrative dataset of 118 727 494 GLD prescriptions. The main outcome measures were the annual number of GLD prescriptions dispensed, accounting for type 2 diabetes mellitus (T2DM) prevalence and healthcare system costs, adjusted for inflation. RESULTS: Utilization of GLDs doubled from 6.4 million prescriptions in 2013 to 15.6 million in 2023. The average annual percent increase in utilization was 8.1%, compared to the average annual increase in prevalence of T2DM of 1.8%. The biggest change was in sodium-glucose cotransporter-2 (SGLT2) inhibitors, for which there was an average annual increase in utilization of 59.4% (95% confidence interval [CI] 51.7%, 68.2%; p < 0.05) from 2014 (first full year of PBS listing), followed by glucagon-like peptide-1 receptor agonists (GLP-1RAs), which showed an increase of 31.4% (95% CI 28.5%, 33.8%; p < 0.05) annually (2013 to 2023). Dipeptidyl peptidase-4 inhibitor utilization tripled, with an average annual increase of 10.9% (95% CI 8.1%, 13.8%; p < 0.05), but this plateaued from 2020. Metformin utilization increased by 4.7% (95% CI 2.0%, 6.9%; p < 0.05) annually. In contrast, sulphonylurea, glitazone and acarbose utilization declined. Total GLD costs increased threefold over the same period. Despite only accounting for 11.7% of utilization, GLP-1RAs contributed to 35% of the costs. CONCLUSION: Utilization of GLDs doubled, and associated costs tripled over the past 11 years, with no sign of either utilization or costs plateauing, predominantly due to increased GLP-1RA and SGLT2 inhibitor prescribing.

Variational Bayes machine learning for risk adjustment of general outcome indicators with examples in urology.

Risk adjustment is often necessary for outcome quality indicators (QIs) to provide fair and accurate feedback to healthcare professionals. However, traditional risk adjustment models are generally oversimplified and not equipped to disentangle complex factors influencing outcomes that are out of a healthcare professional's control. We present VIRGO, a novel variational Bayes model trained on routinely collected, large administrative datasets to risk-adjust outcome QIs. VIRGO uses detailed demographics, diagnosis, and procedure codes to provide individualized risk adjustment and explanations on patient factors affecting outcomes. VIRGO achieves state-of-the-art on external datasets and features capabilities of uncertainty expression, explainable features, and counterfactual analysis capabilities. VIRGO facilitates risk adjustment by explaining how patient factors led to adverse outcomes and expresses the uncertainty of each prediction, allowing healthcare professionals to not only explore patient factors with unexplained variance that are associated with worse outcomes but also reflect on the quality of their clinical practice.

The Reduction of the Productivity Burden of Cardiovascular Disease by Improving the Risk Factor Control Among Australians with Type 2 Diabetes: A 10-Year Dynamic Analysis.

AIMS: To quantify the productivity burden of cardiovascular disease (CVD) in type 2 diabetes and the potential benefits of improved CVD risk factor control. METHODS: We designed models to quantify the productivity burden (using the productivity-adjusted life-year; PALY) of CVD in Australians with type 2 diabetes aged 40-69 years from 2023-2032. PALYs were ascribed a financial value equivalent to gross domestic product (GDP) per full-time worker (AU$204,167 (€124,542)). The base-case model was designed to quantify the productivity burden of CVD in the target population. Then, other hypothetical scenarios were simulated to estimate the potential productivity gains resulting from improved control of risk factors. These scenarios included reductions in systolic blood pressure (SBP), number of smokers, total cholesterol, and incidence of type 2 diabetes. All future costs and outcomes were discounted at an annual rate of 5%. RESULTS: In the base-case (i.e. current projections), the estimated total PALYs lost due to CVD in type 2 diabetes were 1.21 million (95%CI (1.10-1.29 million), contributing to an AU$258.93 (€157.94) billion (95%CI (AU$258.73-261.69 (€157.83-159.63) billion) lost in the country's GDP. If there were reductions in SBP, number of smokers, total cholesterol, and incidence of type 2 diabetes, there would be gains of 7,889, 28,971, 7,117, and 320,124 PALYs, respectively. These improvements would also lead to economic gains of AU$1.72 (€1.05) billion, AU$6.21 (€3.79) billion, AU$1.55 billion (€947.33 million), and AU$68.34 (€41.69) billion, respectively. CONCLUSIONS: Targeted "early lifestyle" strategies that can prevent CVD in Australians with type 2 diabetes are likely positively impact Australian health and work productivity.

This study aimed to assess the productivity burden of cardiovascular disease (CVD) in individuals with type 2 diabetes and the potential benefits of improving the control of CVD risk factors. We developed models to estimate the productivity burden using a measure called productivity-adjusted life-years (PALY). We assigned a financial value to PALYs based on the country's gross domestic product (GDP) per full-time worker. The base-case model showed that the estimated total PALYs lost due to CVD in type 2 diabetes were 1.21 million (95%CI (1.10-1.29 million), contributing AU$258.93 (€157.94) billion (95%CI (AU$258.73-261.69 (€157.83-159.63) billion) lost in the country's GDP.We also simulated hypothetical scenarios to explore the potential gains from reducing risk factors. We found that reductions in systolic blood pressure (SBP), smoking rates, total cholesterol, and the incidence of type 2 diabetes could lead to gains of 7,889, 28,971, 7,117, and 320,124 PALYs, respectively. These improvements would also result in economic gains of AU$1.72 (€1.05) billion, AU$6.21 (€3.79) billion, AU$1.55 billion (€947.33 million), and AU$68.34 (€41.69) billion, respectively.Targeted strategies focusing on early lifestyle interventions to prevent CVD in individuals with type 2 diabetes can have a positive impact on both health outcomes and work productivity in Australia.

Lost Therapeutic Benefit of Delayed Low-Density Lipoprotein Cholesterol Control in Statin-Treated Patients and Cost-Effectiveness Analysis of Lipid-Lowering Intensification.

OBJECTIVES: Attainment of low-density lipoprotein cholesterol (LDL-C) therapeutic goals in statin-treated patients remains suboptimal. We quantified the health economic impact of delayed lipid-lowering intensification from an Australian healthcare and societal perspective. METHODS: A lifetime Markov cohort model (n = 1000) estimating the impact on coronary heart disease (CHD) of intensifying lipid-lowering treatment in statin-treated patients with uncontrolled LDL-C, at moderate to high risk of CHD with no delay or after a 5-year delay, compared with standard of care (no intensification), starting at age 40 years. Intensification was tested with high-intensity statins or statins + ezetimibe. LDL-C levels were extracted from a primary care cohort. CHD risk was estimated using the pooled cohort equation. The effect of cumulative exposure to LDL-C on CHD risk was derived from Mendelian randomization data. Outcomes included CHD events, quality-adjusted life-years (QALYs), healthcare and productivity costs, and incremental cost-effectiveness ratios (ICERs). All outcomes were discounted annually by 5%. RESULTS: Over the lifetime horizon, compared with standard of care, achieving LDL-C control with no delay with high-intensity statins prevented 29 CHD events and yielded 30 extra QALYs (ICERs AU$13 205/QALY) versus 22 CHD events and 16 QALYs (ICER AU$20 270/QALY) with a 5-year delay. For statins + ezetimibe, no delay prevented 53 CHD events and gave 45 extra QALYs (ICER AU$37 271/QALY) versus 40 CHD events and 29 QALYs (ICER of AU$44 218/QALY) after a 5-year delay. CONCLUSIONS: Delaying attainment of LDL-C goals translates into lost therapeutic benefit and a waste of resources. Urgent policies are needed to improve LDL-C goal attainment in statin-treated patients.

The Hospitalizations for Cardiovascular and Respiratory Conditions, Emergency Department Presentations and Economic Burden of Bushfires in Australia Between 2021 and 2030: A Modelling Study.

The health and environmental impacts of bushfires results in substantial economic costs to society. The present analysis sought to estimate the burden of bushfires in Australia over 10 years from 2021 to 2030 inclusive. A dynamic model with yearly cycles was constructed to simulate follow-up of the entire Australian population from 2021 to 2030, capturing deaths and years of life lived. Estimated numbers of bushfire-related-deaths, costs of related-hospitalizations, and broader economic costs were derived from published sources. A 5% annual discount rate was applied to all costs incurred and life years lived from 2022 onwards. Over the 10 years from 2021 to 2030, the modelled analysis predicted that 2418 [95% confidence interval (CI) 2412 - 2422] lives would be lost to bushfires, as well as 8590 [95% CI 8573 - 8606] years of life lost (discounted). Healthcare costs arising from deaths for smoke-related conditions, hospitalizations amounted to AUD $110 million [95% CI 91-129 million] (discounted). The impact on gross domestic product (GDP) totaled AUD $17.2 billion. A hypothetical intervention that reduces the impact of bushfires by 10% would save $11 million in healthcare costs and $1.9 billion in GDP. The health and economic burden of bushfires in Australia looms large during 2021 and 2030. This underscores the importance of actions to mitigate bushfire risk. The findings are useful for the future design and delivery and help policy makers to make informed decisions about investment in strategies to reduce the incidence and severity of future bushfires.

Quality Indicators in the Clinical Specialty of Urology: A Systematic Review.

CONTEXT: In health care, monitoring of quality indicators (QIs) in general urology remains underdeveloped in comparison to other clinical specialties. OBJECTIVE: To identify, synthesise, and appraise QIs that monitor in-hospital care for urology patients. EVIDENCE ACQUISITION: This systematic review included peer-reviewed articles identified via Embase, MEDLINE, Web of Science, CINAHL, Global Health, Google Scholar, and grey literature from 2000 to February 19, 2021. The review was carried out under the Preferred Reporting Items of Systematic Reviews and Meta-Analyses (PRISMA) guidelines and used the Appraisal of Indicators through Research and Evaluation (AIRE) tool for quality assessment. EVIDENCE SYNTHESIS: A total of 5111 articles and 62 government agencies were screened for QI sets. There were a total of 57 QI sets included for analysis. Most QIs focused on uro-oncology, with prostate, bladder, and testicular cancers the most represented. The most common QIs were surgical QIs in uro-oncology (positive surgical margin, surgical volume), whereas in non-oncology the QIs most frequently reported were for treatment and diagnosis. Out of 61 articles, only four scored a total of ≥50% on the AIRE tool across four domains. Aside from QIs developed in uro-oncology, general urological QIs are underdeveloped and of poor methodological quality and most lack testing for both content validity and reliability. CONCLUSIONS: There is an urgent need for the development of methodologically robust QIs in the clinical specialty of general urology for patients to enable standardised quality of care monitoring and to improve patient outcomes. PATIENT SUMMARY: We investigated a range of quality indicators (QIs) that provide health care professionals with feedback on the quality of their care for patients with general urological diseases. We found that aside from urological cancers, there is a lack of QIs for general urology. Hence, there is an urgent need for the development of robust and disease-specific QIs in general urology.

Transmission of SARS-CoV-2 in a primary school setting with and without public health measures using real-world contact data: A modelling study.

Background: Stringent public health measures have been shown to influence the transmission of SARS-CoV-2 within school environments. We investigated the potential transmission of SARS-CoV-2 in a primary school setting with and without public health measures, using fine-grained physical positioning traces captured before the COVID-19 pandemic. Methods: Approximately 172.63 million position data from 98 students and six teachers from an open-plan primary school were used to predict a potential transmission of SARS-CoV-2 in primary school settings. We first estimated the daily average number of contacts of students and teachers with an infected individual during the incubation period. We then used the Reed-Frost model to estimate the probability of transmission per contact for the SARS-CoV-2 Alpha (B.1.1.7), Delta (B.1.617.2), and Omicron variant (B.1.1.529). Finally, we built a binomial distribution model to estimate the probability of onward transmission in schools with and without public health measures, including face masks and physical distancing. Results: An infectious student would have 49.1 (95% confidence interval (CI) = 46.1-52.1) contacts with their peers and 2.00 (95% CI = 1.82-2.18) contacts with teachers per day. An infectious teacher would have 47.6 (95% CI = 45.1-50.0) contacts with students and 1.70 (95% CI = 1.48-1.92) contacts with their colleague teachers per day. While the probability of onward SARS-CoV-2 transmission was relatively low for the Alpha and Delta variants, the risk increased for the Omicron variant, especially in the absence of public health measures. Onward teacher-to-student transmission (88.9%, 95% CI = 88.6%-89.1%) and teacher-to-teacher SARS-CoV-2 transmission (98.4%, 95% CI = 98.5%-98.6%) were significantly higher for the Omicron variant without public health measures in place. Conclusions: Our findings illustrate that, despite a lower frequency of close contacts, teacher-to-teacher close contacts demonstrated a higher risk of transmission per contact of SARS-CoV-2 compared to student-to-student close contacts. This was especially significant with the Omicron variant, with onward transmission more likely occurring from teacher index cases than student index cases. Public health measures (eg, face masks and physical distance) seem essential in reducing the risk of onward transmission within school environments.

An exploration into physician and surgeon data sensemaking: a qualitative systematic review using thematic synthesis.

Providing electronic health data to medical practitioners to reflect on their performance can lead to improved clinical performance and quality of care. Understanding the sensemaking process that is enacted when practitioners are presented with such data is vital to ensure an improvement in performance. Thus, the primary objective of this research was to explore physician and surgeon sensemaking when presented with electronic health data associated with their clinical performance. A systematic literature review was conducted to analyse qualitative research that explored physicians and surgeons experiences with electronic health data associated with their clinical performance published between January 2010 and March 2022. Included articles were assessed for quality, thematically synthesised, and discussed from the perspective of sensemaking. The initial search strategy for this review returned 8,829 articles that were screened at title and abstract level. Subsequent screening found 11 articles that met the eligibility criteria and were retained for analyses. Two articles met all of the standards within the chosen quality assessment (Standards for Reporting Qualitative Research, SRQR). Thematic synthesis generated five overarching themes: data communication, performance reflection, infrastructure, data quality, and risks. The confidence of such findings is reported using CERQual (Confidence in the Evidence from Reviews of Qualitative research). The way the data is communicated can impact sensemaking which has implications on what is learned and has impact on future performance. Many factors including data accuracy, validity, infrastructure, culture can also impact sensemaking and have ramifications on future practice. Providing data in order to support performance reflection is not without risks, both behavioural and affective. The latter of which can impact the practitioner's ability to effectively make sense of the data. An important consideration when data is presented with the intent to improve performance.Registration This systematic review was registered with Prospero, registration number: CRD42020197392.

Attainment of low-density lipoprotein cholesterol goals in patients treated with combination therapy: A retrospective cohort study in primary care.

BACKGROUND: The attainment of low-density lipoprotein cholesterol (LDL-C) therapeutic goals in real-world settings among patients receiving combination lipid-lowering therapy (LLT, statins plus non-statins) is not well characterised. OBJECTIVE: To evaluate LDL-C levels and LDL-C goal attainment in patients treated with combination LLT in real-world primary care settings. METHODS: A retrospective cohort study of patients treated with combination LLT. Data were drawn from general practitioner electronic medical records across Australia from 2013 to 2019. The on-treatment goal for LDL-C was < 2 mmol/L (77 mg/dL), as per Australian guidelines. RESULTS: The cohort analysed included 9,173 individuals treated with combination LLT. The mean age was 65.8 years (standard deviation [SD] 11.5), 60.1% were males, and 56.7% had at least one cardiovascular risk factor. The median on-treatment LDL-C was 2.1 mmol/L (IQR 1.6-2.8), and overall 45.4% of the cohort met LDL-C goals, with individuals on fixed-dose combination of statins plus ezetimibe having the highest rates of achievement (49.8%). In multivariable logistic regression analyses, factors associated with LDL-C goal achievement were male sex (odds ratio [OR] 1.4, 95% confidence interval [CI] 1.3-1.6, p < 0.001), aged >80 years (OR 4.2, 95% CI 1.5 - 6.6, p = 0.006), and a history of T2DM (OR 1.7; 95% CI 1.5-1.9, p < 0.001) or coronary heart disease (OR 1.4, 95% CI 1.2 - 1.6, p < 0.001). CONCLUSIONS: More than half of Australians on combination LLT did not achieve LDL-C goals. Urgent measures are needed to address this gap in clinical practice to minimise negative health outcomes.

Projected New-Onset Cardiovascular Disease by Socioeconomic Group in Australia.

BACKGROUND: Socioeconomic status has an important effect on cardiovascular disease (CVD). Data on the economic implications of CVD by socioeconomic status are needed to inform healthcare planning. OBJECTIVES: The aim of this study was to project new-onset CVD and related health economic outcomes in Australia by socioeconomic status from 2021 to 2030. METHODS: A dynamic population model was built to project annual new-onset CVD by socioeconomic quintile in Australians aged 40-79 years from 2021 to 2030. Cardiovascular risk was estimated using the Pooled Cohort Equation (PCE) from Australian-specific data, stratified for each socioeconomic quintile. The model projected years of life lived, quality- adjusted life-years (QALYs), acute healthcare medical costs, and productivity losses due to new-onset CVD. All outcomes were discounted by 5% annually. RESULTS: PCE estimates showed that 8.4% of people in the most disadvantaged quintile were at high risk of CVD, compared with 3.7% in the least disadvantaged quintile (p < 0.001). From 2021 to 2030, the model projected 32% more cardiovascular events in the most disadvantaged quintile compared with the least disadvantaged (127,070 in SE 1 vs. 96,222 in SE 5). Acute healthcare costs in the most disadvantaged quintile were Australian dollars (AU$) 183 million higher than the least disadvantaged, and the difference in productivity costs was AU$959 million. Removing the equity gap (by applying the cardiovascular risk from the least disadvantaged quintile to the whole population) would prevent 114,822 cardiovascular events and save AU$704 million of healthcare costs and AU$3844 million of lost earnings over the next 10 years. CONCLUSION: Our results highlight the pressing need to implement primary prevention interventions to reduce cardiovascular health inequity. This model provides a platform to incorporate socioeconomic status into health economic models by estimating which interventions are likely to yield more benefits in each socioeconomic quintile.

Switching, Persistence and Adherence to Statin Therapy: a Retrospective Cohort Study Using the Australian National Pharmacy Data.

BACKGROUND: Statins are widely prescribed for the primary and secondary prevention of cardiovascular disease (CVD), but their effectiveness is dependent on the level of adherence and persistence. OBJECTIVES: This study aimed to explore the patterns of switching, adherence and persistence among the Australian general population with newly dispensed statins. METHODS: A retrospective cohort study was conducted using a random sample of data from the Australian national prescription claims data. Switching, adherence to and persistence with statins were assessed for people starting statins from 1 January 2015 to 31 December 2019. Switching was defined as either switching to another intensity of statin, to another statin or to a non-statin agent. Non-persistence to treatment was defined as discontinuation (i.e. ≥90 days with no statin) of coverage. Adherence was measured using proportion of days covered (PDC), and patients with PDC < 0.80 were considered non-adherent. Cox proportional hazard models were used to compare discontinuation, switching and reinitiation between different statins. RESULTS: A cohort of 141,062 people dispensed statins and followed over a median duration of 2.5 years were included. Of the cohort, 29.3% switched statin intensity, 28.4% switched statin type, 3.7% switched to ezetimibe and in 2.7%, ezetimibe was added as combination therapy during the study period. Overall, 58.8% discontinued statins based on the 90-day gap criteria, of whom 55.2% restarted. The proportion of people non-adherent was 24.0% at 6 months to 49.0% at 5 years. People on low and moderate intensity statins were more likely to discontinue compared to those on high-intensity statins (hazard ratio [HR] 1.20, 95% confidence interval [CI] 1.09-1.31), (HR 1.28, 95%CI 1.14-1.42), respectively. Compared to maintaining same statin type and intensity, switching statins, which includes up-titration (HR 0.77, 95%CI 0.70 to 0.86) was associated with less likelihood of discontinuation after reinitiation. CONCLUSIONS: Long-term persistence and adherence to statins remains generally poor among Australians, which limits the effectiveness of these medicines and the consequent health impact they may provide for individuals (and by extension, the population impact when poor persistence and adherence is considered in the statin-taking population). Switching between statins is prevalent in one third of statin users, although any clinical benefit of the observed switching trend is unknown. This, combined with the high volume of statin prescriptions, highlights the need for better strategies to address poor persistence and adherence.

Electronic Health Records That Support Health Professional Reflective Practice: a Missed Opportunity in Digital Health.

A foundational component of digital health involves collecting and leveraging electronic health data to improve health and wellbeing. One of the central technologies for collecting these data are electronic health records (EHRs). In this commentary, the authors explore intersection between digital health and data-driven reflective practice that is described, including an overview of the role of EHRs underpinning technology innovation in healthcare. Subsequently, they argue that EHRs are a rich but under-utilised source of information on the performance of health professionals and healthcare teams that could be harnessed to support reflective practice and behaviour change. EHRs currently act as systems of data collection, not systems of data engagement and reflection by end users such as health professionals and healthcare organisations. Further consideration should be given to supporting reflective practice by health professionals in the design of EHRs and other clinical information systems.

Attainment of low-density lipoprotein cholesterol goals in statin treated patients: Real-world evidence from Australia.

Little is known about the attainment of low-density lipoprotein cholesterol (LDL-C) targets in patients treated with statins in Australian primary healthcare setting that are at increased risk of cardiovascular disease. A retrospective cohort study was conducted using data from electronic medical records of patients treated by general practitioners across Australia. LDL-C target attainment was defined as LDL-C levels ≤ 2 mmol/L for all risk groups, in line with Australian guidelines. Multivariable logistic regression was used to identify the factors associated with LDL-C target attainment. Overall, 61,407 patients were included in the analysis. The mean age was 65 years (± standard deviation [SD] 12.1); 52.0% were males.. Overall, the median LDL-C level was 2.3 mmol/L (IQR = 1.8 - 2.8) and 36.0% of the study population met therapeutic targets. Increased likelihood to achieve LDL-C targets was observed in patients diagnosed with type 2 diabetes (OR 2.07, 95% CI 1.92 - 2.24), stroke (OR = 1.58, 95% CI 1.39 - 1.79, P < 0.001) or chronic heart disease (OR = 1.67, 95% CI 1.55 - 1.81, P < 0.001). Patients diagnosed with dyslipidemia (OR = 0.59, 95% CI 0.55 - 0.64, P < 0.001), hypertension (OR = 0.91, 95% CI 0.83 - 1.00, P < 0.05) and current smokers (OR = 0.71, 95% CI 0.71 - 1.00, P < 0.05), were less likely to attain LDL-C targets, regardless of the type, intensity and length of use of the prescribed statin. Longer duration and higher intensity statin were associated with more patients achieving targeted LDL-C goal, however nearly two thirds of Australians still failed to achieve targeted outcome even after 24 months of statin therapy.

Trends in the Utilization of Lipid-Lowering Medications in Australia: An Analysis of National Pharmacy Claims Data.

Lipid-lowering medications comprise standard of care in the prevention of cardiovascular disease. This study examined the trends in the utilization of statin and non-statin medications in the Australian general population between 2013 and 2019. Pharmacoepidemiological analyses were performed using pharmacy dispensing data from Australian Pharmaceutical Benefits Scheme. One-year prevalence and incidence of statin and non-statin prescribing patterns were reported, and relative variations in prescribing examined via Poisson regression modelling. The one-year prevalence of statins' prescriptions decreased between 2013-2019 by 5.5% (from 25.0%-19.5%). Females were less likely than males to be prescribed statins (rate ratio [RR]=0.90, 95% confidence interval [CI] 0.89-0.91). The one-year prevalence of ezetimibe alone, and in combination with statins, increased consistently from 2013-2019 from 1.5%-3.6% (P<0.01) and 0.1%-1.1% (P<0.01), respectively. The prevalence was higher among those aged 61-80 years (RR=1.20, 95%CI 1.10-1.21) and those aged older than 80 years (RR=1.34, 95%CI 1.22-1.47), when compared to people aged <60 years. The incidence of ezetimibe prescriptions was highest in people aged 61-80 years (RR=1.36, 95%CI 1.31-1.41) compared to those aged <60 years. The one-year prevalence of proprotein convertase subtilisin/kexin type 9 inhibitor prescriptions was highest among those aged 46-60 years (RR=1.24, 95%CI 0.97-4.97) compared to people aged <46 and >60 years. Females were less likely than males to be prescribed a proprotein convertase subtilisin/kexin type 9 inhibitor (RR=0.87, 95%CI 0.75-0.98). Statins remain the most prevalent lipid-lowering medication prescribed in Australia. The prescribing of non-statin medications remains low, but is increasing.

Future burden of cardiovascular disease in Australia: impact on health and economic outcomes between 2020 and 2029.

AIMS: To estimate the health and economic burden of new and established cardiovascular disease from 2020 to 2029 in Australia. METHODS AND RESULTS: A two-stage multistate dynamic model was developed to predict the burden of the incident and prevalent cardiovascular disease, for Australians 40-90 years old from 2020 to 2029. The model captured morbidity, mortality, years of life lived, quality-adjusted life years, healthcare costs, and productivity losses. Cardiovascular risk for the primary prevention population was derived using Australian demographic data and the Pooled Cohort Equation. Risk for the secondary prevention population was derived from the REACH registry. Input data for costs and utilities were extracted from published sources. All outcomes were annually discounted by 5%. A number of sensitivity analyses were undertaken to test the robustness of the study. Between 2020 and 2029, the model estimates 377 754 fatal and 991 375 non-fatal cardiovascular events. By 2029, 1 061 756 Australians will have prevalent cardiovascular disease (CVD). The population accrued 8 815 271 [95% uncertainty interval (UI) 8 805 083-8 841 432] years of life lived with CVD and 5 876 975 (5 551 484-6 226 045) QALYs. The total healthcare costs of CVD were projected to exceed Australian dollars (AUD) 61.89 (61.79-88.66) billion, and productivity losses will account for AUD 78.75 (49.40-295.25) billion, driving the total cost to surpass AUD 140.65 (123.13-370.23) billion. CONCLUSION: Cardiovascular disease in Australia has substantial impacts in terms of morbidity, mortality, and lost revenue to the healthcare system and the society. Our modelling provides important information for decision making in relation to the future burden of cardiovascular disease.

Exploring the Intersection Between Health Professionals' Learning and eHealth Data: Protocol for a Comprehensive Research Program in Practice Analytics in Health Care.

BACKGROUND: There is an increasing amount of electronic data sitting within the health system. These data have untapped potential to improve clinical practice if extracted efficiently and harnessed to change the behavior of health professionals. Furthermore, there is an increasing expectation from the government and peak bodies that both individual health professionals and health care organizations will use electronic data for a range of applications, including improving health service delivery and informing clinical practice and professional accreditation. OBJECTIVE: The aim of this research program is to make eHealth data captured within tertiary health care organizations more actionable to health professionals for use in practice reflection, professional development, and other quality improvement activities. METHODS: A multidisciplinary approach was used to connect academic experts from core disciplines of health and medicine, education and learning sciences, and engineering and information communication technology with government and health service partners to identify key problems preventing the health care industry from using electronic data to support health professional learning. This multidisciplinary approach was used to design a large-scale research program to solve the problem of making eHealth data more accessible to health professionals for practice reflection. The program will be delivered over 5 years by doctoral candidates undertaking research projects with discrete aims that run in parallel to achieving this program's objectives. RESULTS: The process used to develop the research program identified 7 doctoral research projects to answer the program objectives, split across 3 streams. CONCLUSIONS: This research program has the potential to successfully unpack electronic data siloed within clinical sites and enable health professionals to use them to reflect on their practice and deliver informed and improved care. The program will contribute to current practices by fostering stronger connections between industry and academia, interlinking doctoral research projects to solve complex problems, and creating new knowledge for clinical sites on how data can be used to understand and improve performance. Furthermore, the program aims to affect policy by developing insights on how professional development programs may be strengthened to enhance their alignment with clinical practice. The key contributions of this paper include the introduction of a new conceptualized research program, Practice Analytics in Health care, by describing the foundational academic disciplines that the program is formed of and presenting scientific methods for its design and development. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/27984.

Effectiveness of public health measures in reducing the incidence of covid-19, SARS-CoV-2 transmission, and covid-19 mortality: systematic review and meta-analysis.

OBJECTIVE: To review the evidence on the effectiveness of public health measures in reducing the incidence of covid-19, SARS-CoV-2 transmission, and covid-19 mortality. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Medline, Embase, CINAHL, Biosis, Joanna Briggs, Global Health, and World Health Organization COVID-19 database (preprints). ELIGIBILITY CRITERIA FOR STUDY SELECTION: Observational and interventional studies that assessed the effectiveness of public health measures in reducing the incidence of covid-19, SARS-CoV-2 transmission, and covid-19 mortality. MAIN OUTCOME MEASURES: The main outcome measure was incidence of covid-19. Secondary outcomes included SARS-CoV-2 transmission and covid-19 mortality. DATA SYNTHESIS: DerSimonian Laird random effects meta-analysis was performed to investigate the effect of mask wearing, handwashing, and physical distancing measures on incidence of covid-19. Pooled effect estimates with corresponding 95% confidence intervals were computed, and heterogeneity among studies was assessed using Cochran's Q test and the I2 metrics, with two tailed P values. RESULTS: 72 studies met the inclusion criteria, of which 35 evaluated individual public health measures and 37 assessed multiple public health measures as a "package of interventions." Eight of 35 studies were included in the meta-analysis, which indicated a reduction in incidence of covid-19 associated with handwashing (relative risk 0.47, 95% confidence interval 0.19 to 1.12, I2=12%), mask wearing (0.47, 0.29 to 0.75, I2=84%), and physical distancing (0.75, 0.59 to 0.95, I2=87%). Owing to heterogeneity of the studies, meta-analysis was not possible for the outcomes of quarantine and isolation, universal lockdowns, and closures of borders, schools, and workplaces. The effects of these interventions were synthesised descriptively. CONCLUSIONS: This systematic review and meta-analysis suggests that several personal protective and social measures, including handwashing, mask wearing, and physical distancing are associated with reductions in the incidence covid-19. Public health efforts to implement public health measures should consider community health and sociocultural needs, and future research is needed to better understand the effectiveness of public health measures in the context of covid-19 vaccination. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020178692.