Early Health Technology Assessment of Point-of-Care and Laboratory Diagnostics: Methods and applications in acute and primary care

The demand for healthcare has strongly increased in the last decades, due to the aging population, the increase in the number of people with chronic diseases, the rise of personalized medicine, and technological advances. Although this was accompanied by a strong increase in the number of available diagnostic tests, only a limited number of these tests are actually implemented and used in clinical practice. However, this rising number of diagnostic tests available raises concerns about potential overuse of tests that are already implemented in clinical practice, the accompanying (potential) negative health impact of diagnostic testing, for example caused by (unnecessary) distress about test results, as well as rising healthcare costs. Therefore, evaluating the expected health economic impact of new diagnostic tests or diagnostic strategies is highly important to enhance efficient test implementation and use, and to ensure the provision of affordable and good quality healthcare.

The aim of this thesis was therefore to investigate the health economic impact of (new) diagnostic tests or diagnostic testing strategies within three disease areas (i.e. acute coronary syndrome, sepsis and anaemia). In addition, this thesis investigated which aspects affect the implementation and use of (new) diagnostic tests (with a focus on laboratory biomarkers), and to provide recommendations and guidance on investigating the health economic impact of such diagnostic tests.

The results of this thesis have indicated that it is highly important to evaluate the expected impact of a diagnostic test (or combination of tests) on health outcomes and costs, prior to their implementation in clinical practice. In this regard, HTA, and especially early HTA, represent a highly valuable set of techniques to evaluate this impact. Besides health economic models, other techniques that are part of early HTA, for example multi-criteria decision analysis, are valuable to obtain insight in factors that hamper or facilitate the implementation and use of new diagnostic tests. In order to fully quantify the value of diagnostic testing, wider elements of value besides the impact on costs and patients’ health should be considered. Such wider elements of value for example include being reassured of not having a serious illness, or the knowledge of having a genetic disorder, which may affect family planning. Besides a test’s cost-effectiveness, these broader elements of value will likely also affect its implementation and use.