Objective
Since 2008, the Oxford Diagnostic Horizon Scan Programme has been identifying and summarising evidence on new and emerging diagnostic technologies relevant to primary care. We used these reports to determine the sequence and timing of evidence for new point-of-care diagnostic tests and to identify common evidence gaps in this process.
DesignSystematic overview of diagnostic horizon scan reports.
Primary outcome measuresWe obtained the primary studies referenced in each horizon scan report (n=40) and extracted details of the study size, clinical setting and design characteristics. In particular, we assessed whether each study evaluated test accuracy, test impact or cost-effectiveness. The evidence for each point-of-care test was mapped against the Horvath framework for diagnostic test evaluation.
ResultsWe extracted data from 500 primary studies. Most diagnostic technologies underwent clinical performance (ie, ability to detect a clinical condition) assessment (71.2%), with very few progressing to comparative clinical effectiveness (10.0%) and a cost-effectiveness evaluation (8.6%), even in the more established and frequently reported clinical domains, such as cardiovascular disease. The median time to complete an evaluation cycle was 9 years (IQR 5.5–12.5 years). The sequence of evidence generation was typically haphazard and some diagnostic tests appear to be implemented in routine care without completing essential evaluation stages such as clinical effectiveness.
ConclusionsEvidence generation for new point-of-care diagnostic tests is slow and tends to focus on accuracy, and overlooks other test attributes such as impact, implementation and cost-effectiveness. Evaluation of this dynamic cycle and feeding back data from clinical effectiveness to refine analytical and clinical performance are key to improve the efficiency of point-of-care diagnostic test development and impact on clinically relevant outcomes. While the 'road map' for the steps needed to generate evidence are reasonably well delineated, we provide evidence on the complexity, length and variability of the actual process that many diagnostic technologies undergo.
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