Point-of-care Scanning technologies hold immense promise for transforming healthcare, particularly in primary care settings. Since 2008, the Oxford Diagnostic Horizon Scan Programme has diligently tracked the emergence of these innovative diagnostic tools. Their work provides a valuable insight into the evidence supporting new point-of-care diagnostic tests and, crucially, reveals significant gaps in the evaluation process. A systematic review of these horizon scan reports highlights a critical issue: the journey of evidence generation for point-of-care scanning is often slow, unsystematic, and heavily skewed towards test accuracy, overshadowing other vital aspects like clinical impact and cost-effectiveness.
Analysis of numerous primary studies associated with point-of-care diagnostic technologies reveals a concerning trend. While a substantial portion of research focuses on assessing the clinical performance—the basic ability of a test to detect a condition—far fewer studies delve into comparative clinical effectiveness or cost-effectiveness. This imbalance persists even in well-established clinical areas such as cardiovascular disease. The data indicates that a significant number of diagnostic technologies undergo clinical performance evaluations (approximately 71.2%), but only a small fraction progress to evaluating comparative clinical effectiveness (10.0%) and cost-effectiveness (8.6%). This bottleneck in the evaluation pipeline has serious implications for the efficient and responsible adoption of point-of-care scanning in routine clinical practice.
The timeline for completing a full evaluation cycle for point-of-care scanning is also remarkably lengthy. The median time observed is around 9 years, with some evaluations stretching beyond a decade. This protracted process contributes to a haphazard approach to evidence generation. Alarmingly, some point-of-care diagnostic tests appear to be implemented in routine healthcare settings without robust evidence of their clinical effectiveness. This premature adoption risks compromising patient care and misallocating healthcare resources.
The current evidence generation model for point-of-care scanning disproportionately emphasizes test accuracy, neglecting crucial factors such as the real-world impact on patient outcomes, the practicalities of implementation, and economic considerations. To optimize the development and deployment of point-of-care diagnostic tests and maximize their positive impact on clinically relevant outcomes, a shift in focus is essential. It is imperative to streamline the evaluation cycle, ensuring that data from clinical effectiveness studies are fed back to refine both the analytical and clinical performance assessments. While the roadmap outlining the necessary steps for evidence generation may be reasonably clear, the reality is a complex, lengthy, and inconsistent process for many promising diagnostic technologies. Addressing these challenges is critical to realize the full potential of point-of-care scanning in modern healthcare.
