Modelling the long term cost-effectiveness of the SPCCT-based strategy for diagnosing, treating and monitoring atherosclerotic patients will ensure good quality and relevant analyses.
Economic evaluations aim to inform decision makers regarding the costs and the consequences of a novel medical technology compared to the current situation regarding the way in which patients are diagnosed and/or treated. However, most clinical trials and prospective cohort studies collecting data on the costs and health outcomes from individual patients have one important limitation: their follow-up period is too short to observe the lifetime consequences of the treatments that patients receive.
For this reason mathematical modelling is used to estimate the long term costs and consequences of different courses of action comprehensively. Suitable cost-effectiveness models can synthesize the evidence from different sources, including pre-clinical studies (e.g. evidence on risks), diagnostic test accuracy studies, and therapeutic intervention studies (e.g. evidence on outcomes). Subsequently, the lifetimes of hypothetical individuals can be simulated while tracking risk factors, clinical events like MIs and strokes, complications from procedures like CABG or thrombectomy, quality of life, and costs to assess the incremental cost-effectiveness of a new diagnostic strategy versus an alternative strategy.
SPCCT is expected to support treatment decision-making in stroke and MI in emergency settings. However, the degree and extent to which the SPCCT based strategies could improve diagnosis and treatment decisions are currently unknown. Since the added value of SPCCT can only be determined by comparing it with alternative imaging modalities, it is essential to ascertain their use in current care and routine clinical practice.
The PICO framework is well suited to support this research project. In this framework, the events and outcomes experienced by a patient population are investigated. The outcomes generated by the use of the new technology (SPCCT) are compared to those generated in current care. Outcomes are valued in terms of costs and effects (health benefits).
In order to compare interventions, a single measure of benefits is needed. One solution to this is the QALY (Quality Adjusted Life Years) which captures both the length of life and the quality of life. This common unit of benefits can be used in economic evaluations within and between clinical areas.
Modelling the cost-effectiveness (in terms of life expectancy and QALYs) of the SPCCT-based strategy requires a good understanding of the natural process of the disease and of the way clinical care is organised.
First, the structure of any model should accurately reflect the sequences of diagnostic options and treatment decisions that occur in clinical care. This includes intended outcome of clinical activities as well as other issues such as inaccuracy of diagnostics, the incidence of adverse events, compliance, non-response to treatment and so on.
Second, once the structure of a cost-effectiveness model has been defined and validated, data on probabilities of events and occurrences, costs, patient outcomes, and health state values need to be determined in order to populate the model. Only in this manner, the mathematical calculations needed to derive cost-effectiveness estimates can be executed.