Expanding access to fracture liaison services in Australia for people with minimal trauma fractures: a system dynamics modelling study.

OBJECTIVES: To project how many minimal trauma fractures could be averted in Australia by expanding the number and changing the operational characteristics of fracture liaison services (FLS). STUDY DESIGN: System dynamics modelling. SETTING, PARTICIPANTS: People aged 50 years or more who present to hospitals with minimal trauma fractures, Australia, 2020-31. MAIN OUTCOME MEASURES: Numbers of all minimal trauma fractures and of hip fractures averted by increasing the FLS number (from 29 to 58 or 100), patient screening rate (from 30% to 60%), and capacity for accepting new patients (from 40 to 80 per service per month), and reducing the proportion of eligible patients who do not attend FLS (from 30% to 15%); cost per fracture averted. RESULTS: Our model projected a total of 2 441 320 minimal trauma fractures (258 680 hip fractures; 2 182 640 non-hip fractures) in people aged 50 years or older during 2020-31, including 1 211 646 second or later fractures. Increasing the FLS number to 100 averted a projected 5405 fractures (0.22%; $39 510 per fracture averted); doubling FLS capacity averted a projected 3674 fractures (0.15%; $35 835 per fracture averted). Our model projected that neither doubling the screening rate nor reducing by half the proportion of eligible patients who did not attend FLS alone would reduce the number of fractures. Increasing the FLS number to 100, the screening rate to 60%, and capacity to 80 new patients per service per month would together avert a projected 13 672 fractures (0.56%) at a cost of $42 828 per fracture averted. CONCLUSION: Our modelling indicates that increasing the number of hospital-based FLS and changing key operational characteristics would achieve only moderate reductions in the number of minimal trauma fractures among people aged 50 years or more, and the cost would be relatively high. Alternatives to specialist-led, hospital-based FLS should be explored.

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.

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.

Sharing administrative health data with private industry: A report on two citizens' juries.

BACKGROUND: There is good evidence of both community support for sharing public sector administrative health data in the public interest and concern about data security, misuse and loss of control over health information, particularly if private sector organizations are the data recipients. To date, there is little research describing the perspectives of informed community members on private sector use of public health data and, particularly, on the conditions under which that use might be justified. METHODS: Two citizens' juries were held in February 2020 in two locations close to Sydney, Australia. Jurors considered the charge: 'Under what circumstances is it permissible for governments to share health data with private industry for research and development?' RESULTS: All jurors, bar one, in principle supported sharing government administrative health data with private industry for research and development. The support was conditional and the juries' recommendations specifying these conditions related closely to the concerns they identified in deliberation. CONCLUSION: The outcomes of the deliberative processes suggest that informed Australian citizens are willing to accept sharing their administrative health data, including with private industry, providing the intended purpose is clearly of public benefit, sharing occurs responsibly in a framework of accountability, and the data are securely held. PATIENT AND PUBLIC CONTRIBUTION: The design of the jury was guided by an Advisory Group including representatives from a health consumer organization. The jurors themselves were selected to be descriptively representative of their communities and with independent facilitation wrote the recommendations.

Alignment of preferences in the treatment of multiple myeloma - a discrete choice experiment of patient, carer, physician, and nurse preferences.

BACKGROUND: Multiple Myeloma (MM) is a cancer characterised by the proliferation of malignant plasma cells in the bone marrow. This study examined the treatment preferences of people living with MM compared to the treatment preferences of other groups involved in treatment decision making, including carers, as well as physicians and nurses who treat people living with MM in Australia. METHODS: Data were collected using discrete choice experiments (DCEs) through an online survey. The DCEs presented participants with a traditional treatment generic choice experiment (e.g., treatment A vs treatment B), focusing on the clinical benefits of treatments and the associated risks. The attributes and levels of the attributes were selected based on previous research, literature review, qualitative research and expert opinion. The DCE data were modelled using a Latent Class Model (LCM). RESULTS: The model revealed significant heterogeneity in preferences for treatment attributes. In particular, overall survival, remission period and annual out of pocket cost were the attributes with the most variation. In comparison to people living with MM, carers were less cost-sensitive and more concerned with quality of life (remission period). Physicians and nurses were generally more concerned with overall survival and more cost sensitive than people living with MM. CONCLUSIONS: This study demonstrated that not all people living with MM valued the same treatment attributes equally. Further, not all groups involved in MM treatment decision making had preference alignment on all treatment attributes. This has important implications for healthcare policy decisions and shared decision making. Results from this study could be used to guide decisions around the value of new MM medicines or the medical plan surrounding the needs of those living with MM, as well as those caring for them.

Analysis of PBAC submissions and outcomes for medicines (2010-2018).

OBJECTIVES: The Pharmaceutical Benefits Scheme (PBS) provides timely, reliable, and affordable access to necessary medicines for Australians. We reviewed the Pharmaceutical Benefits Advisory Committee (PBAC) submissions and their related outcomes and timelines since 2010. METHODS: We examined the PBS Website to identify submissions and their related PBAC outcomes for new medicines, new indications, and new combination products that had been considered by the PBAC since 2010. RESULTS: Thirty-five PBAC meetings were held during the study period, at which the Committee considered 781 submissions (1,074 medicine/patient population pairings). We saw an increase in the annual number of submissions (medicine/patient population parings). The recommendation rate for the study period was higher than the rejection rate. The annual mean value for the period from the date of initial PBAC recommendation to the date of PBS listing ranged from 357 to 644 days; the annual mean value for the period of the date of PBAC recommendation to the date of PBS listing ranged from 187 to 245 days. It took, on average, 1.70 submissions that included an economic evaluation to obtain a PBAC recommendation. It took more submissions to obtain a PBAC recommendation for a cost-effectiveness analysis submission than it did for a CMA submission. The PBAC was willing to recommend medicines for most acceptable base-case incremental cost-effectiveness ratio (ICER) bands, and the majority of the PBAC did not recommended any medicine in the study period that had a base-case ICER >AUD75,000. CONCLUSIONS: The results of our analyses reveal a minor reduction in the period from the date of PBAC recommendation to the date of PBS listing. Several analyses were hampered by a high proportion of missing data.

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.

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.

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.

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.

Gazing through time and beyond the health sector: Insights from a system dynamics model of cardiovascular disease in Australia.

OBJECTIVE: To construct a whole-of-system model to inform strategies that reduce the burden of cardiovascular disease (CVD) in Australia. METHODS: A system dynamics model was developed with a multidisciplinary modelling consortium. The model population comprised Australians aged 40 years and over, and the scope encompassed acute and chronic CVD as well as primary and secondary prevention. Health outcomes were CVD-related deaths and hospitalisations, and economic outcomes were the net benefit from both the healthcare system and societal perspectives. The eight strategies broadly included creating social and physical environments supportive of a healthy lifestyle, increasing the use of preventive treatments, and improving systems response to acute CVD events. The effects of strategies were estimated as relative differences to the business-as-usual between 2019-2039. Probabilistic sensitivity analysis produced uncertainty intervals of interquartile ranges (IQR). FINDINGS: The greatest reduction in CVD-related deaths was seen in strategies that improve systems response to acute CVD events (8.9%, IQR: 7.7-10.2%), yet they resulted in an increase in CVD-related hospitalisations due to future recurrent admissions (1.6%, IQR: 0.1-2.3%). This flow-on effect highlighted the importance of addressing underlying CVD risks. On the other hand, strategies targeting the broad environment that supports a healthy lifestyle were effective in reducing both hospitalisations (7.1%; IQR: 5.0-9.5%) and deaths (8.1% reduction; IQR: 7.1-8.9%). They also produced an economic net benefit of AU$43.3 billion (IQR: 37.7-48.7) using a societal perspective, largely driven by productivity gains. Overall, strategic planning to reduce the burden of CVD should consider the varying effects of strategies over time and beyond the health sector.

Analysis of sponsor hearings on health technology assessment decision making.

Objective The aim of this study was to get a better understanding of the frequency of Pharmaceutical Benefits Advisory Committee (PBAC) hearings, the factors that influence a sponsor's decision to proceed with a hearing and to assess the impact hearings may have had on PBAC decision making. Methods All public summary documents (PSDs) from March 2014 to November 2016 PBAC meetings, obtained from the Pharmaceutical Benefits Scheme (PBS) website, were examined to identify major submissions for which sponsor hearings were conducted. Each PSD was analysed to determine the topics discussed at the sponsor hearing and the 'usefulness' of a sponsor hearing from the PBAC's perspective. Results During the study period there were 472 PSDs. 74 sponsor hearings (28% of major submissions) were conducted during the study period. A clinician external to the sponsor presented at the majority of the hearings (78%) and accordingly, the main topics presented related to clinical positioning/use and clinical benefit/use. Conclusion The PBAC considered approximately 45% of sponsor hearings to be informative or moderately informative whereas 18% were classed as uninformative. What is known about the topic? Although the sponsors of medicines being considered by the Pharmaceutical Benefits Advisory Committee (PBAC) for public subsidy have been able to give a 10 min presentation to the Committee at the time of decision making for several years, it is unknown whether these hearings are beneficial. What does this paper add? We present what is believed to be the results of the first analysis of PBAC sponsor hearings. What are the implications for practitioners? All stakeholders should consider the findings of our research and associated recommendations to ensure that future sponsor hearings enhance PBAC decision making and promote good public health policy.