Cost-effectiveness of a community-based integrated care model compared with usual care for older adults with complex needs: a stepped-wedge cluster-randomised trial.

Objective: To assess the cost of implementation, delivery and cost-effectiveness (CE) of a flagship community-based integrated care model (OPEN ARCH) against the usual primary care. Design: A 9-month stepped-wedge cluster-randomised trial. Setting and participants: Community-dwelling older adults with chronic conditions and complex care needs were recruited from primary care (14 general practices) in Far North Queensland, Australia. Methods: Costs and outcomes were measured at 3-month windows from the healthcare system and patient's out-of-pocket perspectives for the analysis. Outcomes included functional status (Functional Independence Measure (FIM)) and health-related quality of life (EQ-5D-3L and AQoL-8D). Bayesian CE analysis with 10 000 Monte Carlo simulations was performed using the BCEA package in R (V.3.6.1). Results: The OPEN ARCH model of care had an average cost of $A1354 per participant. The average age of participants was 81, and 55% of the cohort were men. Within-trial multilevel regression models adjusted for time, general practitioner cluster and baseline confounders showed no significant differences in costs, resource use or effect measures regardless of the analytical perspective. Probabilistic sensitivity analysis with 10 000 simulations showed that OPEN ARCH could be recommended over usual care for improving functional independence at a willing to pay above $A600 (US$440) per improvement of one point on the FIM Scale and for avoiding or reducing inpatient stay for any willingness-to-pay threshold up to $A50 000 (US$36 500). Conclusions and implications: OPEN ARCH was associated with a favourable Bayesian CE profile in improving functional status and dependency levels, avoiding or reducing inpatient stay compared with usual primary care in the Australian context. Trial registration number: ACTRN12617000198325.

Public Preferences for Allocating Ventilators in an Intensive Care Unit: A Discrete Choice Experiment.

BACKGROUND AND OBJECTIVE: During the COVID-19 pandemic, resources in intensive care units (ICUs) have the potential to be inadequate to treat all those who might benefit. Therefore, it is paramount to identify the views of the community regarding how to allocate such resources. This study aims to quantify Australian community preferences for ventilation allocation. METHODS: A discrete choice experiment was designed and administrated to an adult Australian online panel. Each survey respondent answered 12 choice sets from a total design of 120. Each choice set placed the respondent in the role of hypothetical decision maker, prioritising care between two patients. Conditional logit, mixed logit regression and latent class analysis were used to analyse the data. Additionally, we asked a series of attitudinal questions about different methods of making such decisions in practice, focusing on who should be responsible. RESULTS: A total of 1050 community members completed the survey and responded to each choice. Dimensions considered most important were age, likely effectiveness, smoking status, whether the person has dependents, whether they are a healthcare worker, and whether they have a disability or not. Estimating marginal rates of substitution between patient characteristics and chance of survival if ventilated yielded values of up to 30 percentage points if the patient was 70 years old relative to being 30. However, respondents typically said they would prefer such decisions to be made by medical professionals. CONCLUSION: This study demonstrated the preferences of the community to allocation of ventilators during the COVID-19 pandemic. The use of such information should be treated with some caution as the underlying reason for such preferences are unclear, and respondents themselves preferred the decision to be made by others.

Finding Out What Matters in Decision-Making Related to Genomics and Personalized Medicine in Pediatric Oncology: Developing Attributes to Include in a Discrete Choice Experiment.

BACKGROUND: Treatment decision-making in pediatric oncology can be complex. Recent advances in genome sequencing and novel or 'personalized' therapies potentially increases the complexity of decision-making and treatment options. OBJECTIVES: This study explored the views and experiences of healthcare providers (HCPs) and parents with respect to decision-making in difficult-to-treat cancers, including genomic decision-making. METHODS: A two-phase qualitative study was undertaken in which oncologists and nurses and parents of children with relapsed and refractory cancers were interviewed using a semi-structured interview guide. Data were analyzed thematically, with a focus on measurable themes relevant to the development of candidate attributes for a discrete choice experiment (DCE). Secondly, a review of studies that utilized stated preference experiments in the fields of genomics, medical decision-making, and pediatrics was undertaken and compared with the candidate attributes identified from interviews. RESULTS: Six candidate attributes were developed from the interview themes: clinical benefit, quality of life (QoL) including both treatment effects and functionality, likelihood of a target, cost (who pays), recommendation of HCP or extent family supported the decision, and whether a biopsy was needed. Two further candidate attributes were identified from the literature review: severity of illness and cost (dollar amount). CONCLUSIONS: This study identified eight candidate attributes that will be further validated prior to developing a DCE aimed at better understanding factors influencing decision-making related to genomic sequencing and personalized medicine. This study and the proposed DCE will contribute to improving ethical and clinical practices in the application of novel genomic technology in pediatric oncology.

Real-World Cost Effectiveness of Mandatory Folic Acid Fortification of Bread-Making Flour in Australia.

BACKGROUND: In 2009, mandatory folic acid fortification of bread-making flour was introduced in Australia to reduce the birth prevalence of preventable neural tube defects (NTDs) such as spina bifida. Before the introduction of the policy, modelling predicted a reduction of 14-49 NTDs each year. OBJECTIVE: Using real-world data, this study provides the first ex-post evaluation of the cost effectiveness of mandatory folic acid fortification of bread-making flour in Australia. METHODS: We developed a decision tree model to compare different fortification strategies and used registry data to quantify the change in NTD rates due to the policy. We adopted a societal perspective that included costs to industry and government as well as healthcare and broader societal costs. RESULTS: We found 32 fewer NTDs per year in the post-mandatory folic acid fortification period. Mandatory folic acid fortification improved health outcomes and was highly cost effective because of the low intervention cost. The policy demonstrated improved equity in outcomes, particularly in birth prevalence of NTDs in births from teenage and indigenous mothers. CONCLUSIONS: This study calculated the value of mandatory folic acid fortification using real-world registry data and demonstrated that the attained benefit was comparable to the modelled expected benefits. Mandatory folic acid fortification (in addition to policies including advice on supplementation and education) improved equity in certain populations and was effective and highly cost effective for the Australian population.