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Model-based economic evaluations of diagnostic point of care tests were rarely fit for purpose
Katie Breheny1, Andrew J Sutton1, Jonathan J Deeks2
1Health Economics Unit, Institute of Applied Health Research, University of Birmingham, Birmingham B15 2TT, UK.
Objectives:
Linked evidence models are recommended to predict health benefits and cost-effectiveness of diagnostic tests. We considered how published models accounted for changes in patient pathways that occur with point of care tests (POCTs) and their impact on patient health and costs.
Study Design And Setting:
Model-based evaluations of diagnostic POCTs published from 2004 to 2017 were identified from searching six databases. For each model, we assessed the outcomes considered, and whether reduced time to diagnosis and increased access to testing affected patient health and costs.
Results:
Seventy-four model-based evaluations were included: 95% incorporated evidence on test accuracy, but 34% only assessed intermediate outcomes such as rates of correct diagnosis. Of 54 models where POCTs reduced testing time, 39% addressed the economic and 37% addressed the health benefits of faster diagnosis. No model considered differences in access to tests.
Conclusion:
Many models fail to capture the effects of POCTs in increasing access, advancing speed of diagnosis and treatment, and reducing anxiety and the associated costs. Many only consider the impact of testing from changes in accuracy. Ensuring models incorporate changes in patient pathways from faster and more accessible testing will lead to economic evaluations that better reflect the impact of POCTs.
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