Could Computed Tomography Coronary Angiography Replace Invasive Coronary Angiography as a First-Line Diagnostic Investigation in Suspected Acute Coronary Syndromes? A Decision-Analytic Model.

BACKGROUND: The implementation of high-sensitivity cardiac troponin (hs-cTn) assays into clinical practice has resulted in the identification of a novel cohort of patients with modestly increased troponin concentrations. Subsequent increases in rates of coronary angiography have been observed, without significant increases in rates of coronary revascularisation. Computed tomography coronary angiography (CTCA) is a non-invasive investigation that offers the opportunity to decouple investigation from the impetus to revascularise, and may provide an alternative, more risk-appropriate initial investigative strategy for the cohort with low to moderate hs-cTn increases. This analysis seeks to define the threshold of pre-test probability of coronary revascularisation in patients with suspected acute coronary syndrome at which a strategy of initial CTCA is safe and a more cost-effective approach than standard invasive coronary angiography (ICA). METHODS: A cost-benefit evaluation was conducted using a decision-analytic model. The primary outcome measure was the incremental cost-effectiveness ratio (ICER) of CTCA in comparison with ICA as an initial diagnostic investigation for patients with hs-cTnT levels between 5 and 100 ng/L. Secondary outcome measures of costs, patient outcomes, and quality-adjusted life years were analysed. RESULTS: Median base case ICER over 1,000 trials was $17,163 AUD but demonstrated large variability. Sensitivity analysis demonstrated that CTCA was cost-effective until the probability of requiring revascularisation was ∼60%, beyond which point CTCA was associated with higher costs and poorer outcomes than ICA. CONCLUSIONS: Computed tomography coronary angiography may be a cost-effective first-line investigation for patients with moderate hs-cTnT rises until/up to a 60% pre-test probability for receiving coronary revascularisation. To objectively assess the optimal circumstances of cost-effectiveness, prospective evaluation incorporating the estimated probability of revascularisation will be required.

Evaluation of collaborative models of care in the management of patients with depression: protocol and progress.

Introduction Depression is highly prevalent and has a considerable impact on the quality of life of affected individuals, and on healthcare resources. Evidence indicates that collaborative care models can improve patient outcomes within a primary care setting. The Primary Care Services Improvement Project (PCSIP) aims to investigate the costs and outcomes of different models of care for the management of patients with depression. These models have been defined based on the level of involvement of practice nurses in management processes within the primary care setting in Australia. This paper describes our study protocol and its progress. Methods PCSIP is an observational study that will link retrospective data from a range of sources to estimate costs and intermediate outcomes (such as relapse rate) over a 3-year time horizon. The main sources of primary data include the medical records of patients held at participating practices and Medicare Australia. Initial report We recruited 15 practices from a metropolitan area and allocated them to three models of care. Two hundred and sixty-one patients agreed to participate. Appropriate regression-based analyses will be used to evaluate the association between different models of care and patient-level outcomes while controlling for several covariates such as age and gender. Discussion/conclusions This project will generate the knowledge required to promote investment in the most cost-effective initiatives, and to ensure that waste of resources due to the implementation of comparatively inefficient interventions is minimised. Given the scarcity of resources, the increasing costs of providing healthcare and the increasing prevalence of chronic diseases, such research is essential.