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Background: The Pediatric Quality of Life Inventory™ 4.0 Short Form 15 Generic Core Scales (hereafter the PedsQL) and the Child Health Utility-9 Dimensions (CHU9D) are two generic instruments designed to measure health-related quality of life in children and adolescents in the general population and paediatric patient groups living with specific health conditions. Although the PedsQL is widely used among paediatric patient populations, presently it is not possible to directly use the scores from the instrument to calculate quality-adjusted life-years (QALYs) for application in economic evaluation because it produces summary scores which are not preference-based.Objective: This paper examines different econometric mapping techniques for estimating CHU9D utility scores from the PedsQL for the purpose of calculating QALYs for cost-utility analysis.Methods: The PedsQL and the CHU9D were completed by a community sample of 755 Australian adolescents aged 15-17 years. Seven regression models were estimated: ordinary least squares estimator, generalised linear model, robust MM estimator, multivariate factorial polynomial estimator, beta-binomial estimator, finite mixture model and multinomial logistic model. The mean absolute error (MAE) and the mean squared error (MSE) were used to assess predictive ability of the models.Results: The MM estimator with stepwise-selected PedsQL dimension scores as explanatory variables had the best predictive accuracy using MAE and the equivalent beta-binomial model had the best predictive accuracy using MSE.Conclusions: Our mapping algorithm facilitates the estimation of health-state utilities for use within economic evaluations where only PedsQL data is available and is suitable for use in community-based adolescents aged 15-17 years. Applicability of the algorithm in younger populations should be assessed in further research. [ABSTRACT FROM AUTHOR]

Objectives: In Australia, no therapeutic agents were subsidised for the treatment of idiopathic pulmonary artery hypertension (iPAH), a rare progressive and severe disease with short life expectancy, until 1 March 2004, when bosentan (a dual endothelin receptor antagonist of high cost) was listed on the Pharmaceutical Benefits Scheme (PBS). Bosentan, in addition to conventional therapy, has been shown to slow iPAH progression and improve clinical and haemodynamic status and symptomatology, compared with placebo and conventional therapy. The objective of this paper is to describe the process of the Australian Pharmaceutical Benefits Scheme listing for bosentan (Tracleer), which included a health economic model assessing the cost effectiveness of bosentan from a healthcare payer perspective, and a risk-sharing arrangement based on the establishment of a patient registry.Methods: The health economic model predicted the cost, hospitalisation and mortality rates of a population of iPAH patients treated with either the conventional therapy regimen used in Australia or bosentan plus the conventional therapy regimen. The model was implemented as a first-order Monte Carlo simulation with mortality modelled directly as the main clinical outcome. The impacts of proposed continuation criteria, restricting the ongoing use of the drug, were evaluated. Costs and outcomes were discounted at 5% and a sensitivity analysis examined the robustness of the key assumptions.Results: The model predicted that after 5, 10 and 15 years, the difference in average cumulative costs between bosentan plus conventional therapy and conventional therapy alone would be 116,929 Australian dollars (A dollars), A181,808 dollars and A216,331 dollars for each patient, respectively. There would be an associated increase in average life expectancy of 1.39, 2.93 and 3.87 years at 5, 10 and 15 years, respectively, with an incremental cost-effectiveness ratio at 15 years of A55,927 dollars for each life-year gained. Removing the continuation criteria from the model increased the incremental cost-effectiveness ratio to A62,267 dollars (1996-2002 values).Conclusions: Economic modelling based on improved survival suggests bosentan to be a potentially cost-effective treatment for iPAH. However, the structure of the model and its inputs should be reviewed and updated as more data become available. [ABSTRACT FROM AUTHOR]

Background and Objective: Unplanned pregnancies can lead to poorer maternal and child health outcomes. The Australian Therapeutic Goods Administration committee rejected reclassifying a range of oral contraceptive pills (OCPs) from prescription to pharmacist-only medicines in 2015, mainly based on safety concerns. Improving access to OCPs may encourage some women to use contraceptives or switch from other contraceptive methods. However, some adverse events may increase and some women may stop using condoms, increasing their risk of sexually transmitted infections. This study aimed to estimate the cost effectiveness of reclassifying OCPs from prescription to pharmacist-only.Perspective: Healthcare system.Setting: Australian primary care.Methods: A Markov model was used to synthesise data from a variety of sources. The model included all Australian women aged 15-49 years (N = 5,644,701). The time horizon was 35 years. Contraceptive use before reclassification was estimated using data from the Household, Income and Labour Dynamics in Australia (HILDA) survey, while survey data informed use after reclassification. Health outcomes included pregnancies, pregnancy outcomes (live birth, miscarriage, stillbirth, ectopic pregnancy and abortion), sexually transmitted infections, adverse events (venous thromboembolism, depression, myocardial infarction and stroke), ovarian cancer cases and quality-adjusted life-years. Costs included those related to general practitioner and specialist consultations, contraceptives and other medicines, pharmacist time, hospitalisations and adverse events. All costs were reported in 2016 Australian Dollars. A 5% discount rate was applied to health outcomes and costs.Results: Reclassifying OCPs resulted in 85.70 million quality-adjusted life-years experienced and costs of $46,910.14 million over 35 years, vs. 85.68 million quality-adjusted life-years experienced and costs of $50,274.95 million with OCPs remaining prescription-only. Thus, reclassifying OCPs was more effective and cost saving. However, a sensitivity analysis found that more research on the probability of pregnancy in women not using contraception and not trying to conceive is needed.Conclusion: Reclassifying OCPs is likely to be considered cost effective by Australian decision makers. [ABSTRACT FROM AUTHOR]

Background: The inclusion of future medical costs in cost-effectiveness analyses remains a controversial issue. The impact of capturing future medical costs is likely to be particularly important in patients with cancer where costly lifelong medical care is necessary. The lack of clear, definitive pharmacoeconomic guidelines can limit comparability and has implications for decision making.Objective: The aim of this study was to demonstrate the impact of incorporating future medical costs through an applied example using original data from a clinical study evaluating the cost effectiveness of a sepsis intervention in cancer patients.Methods: A decision analytic model was used to capture quality-adjusted life-years (QALYs) and lifetime costs of cancer patients from an Australian healthcare system perspective over a lifetime horizon. The evaluation considered three scenarios: (1) intervention-related costs (no future medical cost), (2) lifetime cancer costs and (3) all future healthcare costs. Inputs to the model included patient-level data from the clinical study, relative risk of death due to sepsis, cancer mortality and future medical costs sourced from published literature. All costs are expressed in 2017 Australian dollars and discounted at 5%. To further assess the impact of future costs on cancer heterogeneity, variation in survival and lifetime costs between cancer types and the implications for cost-effectiveness analysis were explored.Results: The inclusion of future medical costs increased incremental cost-effectiveness ratios (ICERs) resulting in a shift from the intervention being a dominant strategy (cheaper and more effective) to an ICER of $7526/QALY. Across different cancer types, longer life expectancies did not necessarily result in greater lifetime healthcare costs. Incremental costs differed across cancers depending on the respective costs of managing cancer and survivorship, thus resulting in variations in ICERs.Conclusions: There is scope for including costs beyond intervention costs in economic evaluations. The inclusion of future medical costs can result in markedly different cost-effectiveness results, leading to higher ICERs in a cancer population, with possible implications for funding decisions. [ABSTRACT FROM AUTHOR]

Background: Disease management programmes may improve quality of care, improve health outcomes and potentially reduce total healthcare costs. To date, only one very large population-based study has been undertaken and indicated reductions in hospital admissions > 10%.Objective: We sought to confirm the effectiveness of population-based disease management programmes. The objective of this study was to evaluate the relative impact on healthcare utilisation and cost of participants the Costs to Australian Private Insurance - Coaching Health (CAPICHe) trial.Design: Parallel-group randomised controlled trial, intention-to-treat analysis SETTING: Australian population PARTICIPANTS: Forty-four thousand four hundred eighteen individuals (18-90 years of age) with private health insurance and diagnosis of heart failure, chronic obstructive pulmonary disease (COPD), coronary artery disease (CAD), diabetes, or low back pain, with predicted high cost claims for the following 12 months.Intervention: Health coaching for disease management from Bupa Health Dialog, vs Usual Care.Main Outcome Measures: Total cost of claims per member to the private health insurer 1 year post-randomisation for hospital admissions, including same-day, medical and prostheses hospital claims, excluding any maternity costs. Analysis was based on the intent-to-treat population.Results: Estimated total cost 1 year post-randomisation was not significantly different (means: intervention group A$4934; 95% CI A$4823-A$5045 vs control group A$4868; 95% CI A$4680-A$5058; p = 0.524). However, the intervention group had significantly lower same-day admission costs (A$468; 95% CI A$454-A$482 vs A$508; 95% CI A$484-A$533; p = 0.002) and fewer same-day admissions per 1000 person-years (intervention group, 530; 95% CI 508-552 vs control group, 614; 95% CI 571-657; p = 0.002). Subgroup analyses indicated that the intervention group had significantly fewer admissions for patients with COPD and fewer same-day admissions for patients with diabetes.Conclusions: Chronic disease health coaching was not effective to reduce the total cost after 12 months of follow-up for higher risk individuals with a chronic condition. Statistically significant changes were found with fewer same-day admissions; however, these did not translate into cost savings from a private health insurance perspective. [ABSTRACT FROM AUTHOR]

Background: Spending on new healthcare technologies increases net population health when the benefits of a new technology are greater than their opportunity costs-the benefits of the best alternative use of the additional resources required to fund a new technology.Objective: The objective of this study was to estimate the expected incremental cost per quality-adjusted life-year (QALY) gained of increased government health expenditure as an empirical estimate of the average opportunity costs of decisions to fund new health technologies. The estimated incremental cost-effectiveness ratio (ICER) is proposed as a reference ICER to inform value-based decision making in Australia.Methods: Empirical top-down approaches were used to estimate the QALY effects of government health expenditure with respect to reduced mortality and morbidity. Instrumental variable two-stage least-squares regression was used to estimate the elasticity of mortality-related QALY losses to a marginal change in government health expenditure. Regression analysis of longitudinal survey data representative of the general population was used to isolate the effects of increased government health expenditure on morbidity-related, QALY gains. Clinical judgement informed the duration of health-related quality-of-life improvement from the annual increase in government health expenditure.Results: The base-case reference ICER was estimated at AUD28,033 per QALY gained. Parametric uncertainty associated with the estimation of mortality- and morbidity-related QALYs generated a 95% confidence interval AUD20,758-37,667.Conclusion: Recent public summary documents suggest new technologies with ICERs above AUD40,000 per QALY gained are recommended for public funding. The empirical reference ICER reported in this article suggests more QALYs could be gained if resources were allocated to other forms of health spending. [ABSTRACT FROM AUTHOR]

Background: The EORTC QLU-C10D is a new multi-attribute utility instrument derived from the widely used cancer-specific quality-of-life (QOL) questionnaire, EORTC QLQ-C30. The QLU-C10D contains ten dimensions (Physical, Role, Social and Emotional Functioning; Pain, Fatigue, Sleep, Appetite, Nausea, Bowel Problems), each with four levels. To be used in cost-utility analysis, country-specific valuation sets are required.Objective: The aim of this study was to provide Australian utility weights for the QLU-C10D.Methods: An Australian online panel was quota-sampled to ensure population representativeness by sex and age (≥ 18 years). Participants completed a discrete choice experiment (DCE) consisting of 16 choice-pairs. Each pair comprised two QLU-C10D health states plus life expectancy. Data were analysed using conditional logistic regression, parameterised to fit the quality-adjusted life-year framework. Utility weights were calculated as the ratio of each QOL dimension-level coefficient to the coefficient on life expectancy.Results: A total of 1979 panel members opted in, 1904 (96%) completed at least one choice-pair, and 1846 (93%) completed all 16 choice-pairs. Dimension weights were generally monotonic: poorer levels within each dimension were generally associated with greater utility decrements. The dimensions that impacted most on choice were, in order, Physical Functioning, Pain, Role Functioning and Emotional Functioning. Oncology-relevant dimensions with moderate impact were Nausea and Bowel Problems. Fatigue, Trouble Sleeping and Appetite had relatively small impact. The value of the worst health state was -0.096, somewhat worse than death.Conclusions: This study provides the first country-specific value set for the QLU-C10D, which can facilitate cost-utility analyses when applied to data collected with the EORTC QLQ-C30, prospectively and retrospectively. [ABSTRACT FROM AUTHOR]

Objective: Deciding on public funding for pharmaceuticals on the basis of value for money is now widespread. We suggest that evidence-based assessment of value has restricted the availability of medicines in Australia in a way that reflects the relative bargaining power of government and the pharmaceutical industry. We propose a simple informal game-theoretic model of bargaining between the funding agency and industry and test its predictions using a logistic multiple regression model of past funding decisions made by the Pharmaceutical Benefits Advisory Committee in Australia.Method: The model estimates the probability of a drug being recommended for subsidy as a function of incremental cost per quality-adjusted life-year (QALY), as well as other drug and market characteristics. Data are major submissions or resubmissions from 1993 to 2009 where there was a claim of superiority and evidence of a difference in quality of life. Independent variables measure the incremental cost per QALY, the cost to the public budget, the strength and quality of the clinical and economic evidence, need as measured by severity of illness and the availability of alternative treatments, whether or not a resubmission, and newspaper reports as a measure of public pressure. We report the odds ratio for each variable and calculate the ratio of the marginal effect of each variable to the marginal effect of the cost per QALY as a measure of the revealed willingness to pay for each of the variables that influence the decision.Results: The results are consistent with a bargaining model where a 10,000 Australian dollar ($A) fall in value (increase in cost per QALY) reduces the average probability of public funding from 37 to 33% (95% CI 34-32). If the condition is life threatening or the drug has no active comparator, then the odds of a positive recommendation are 3.18 (95% CI 1.00-10.11) and 2.14 (95% CI 0.95-4.83) greater, equivalent to a $A33,000 and a $A21,000 increase in value (fall in cost per QALY). If both conditions are met, the odds are increased by 4.41 (95% CI 1.28-15.24) times, equivalent to an increase in value of $A46,000. Funding is more likely as time elapses and price falls, but we did not find clear evidence that public or corporate pressure influences decisions.Conclusion: Evidence from Australia suggests that the determinants of public funding and pricing decisions for medicines reflect the relative bargaining power of government and drug companies. Value for money depends on the quality of evidence, timing, patient need, perceived benefit and opportunity cost; these factors reflect the potential gains from striking a bargain and the risk of loss from not doing so. [ABSTRACT FROM AUTHOR]