To address the challenges posed by large number of the point of care testing (POCT) equipment for blood glucose in large-scale hospitals, homogeneous quality management and concealed risks, this paper verified the practical value of 'isk-oriented sampling combined with technical evaluation' strategy for detecting systematic risks and guiding management decisions.

Four-party collaboration mechanism was established, risk-oriented sampling was conducted and public health "risk early warning" theory was introduced. From over 850 POCT glucose meters throughout the hospital, 115 devices (around 13.5%) exhibiting characteristic of "saturation operation" or "minor performance degradation" were selected as risk-oriented devices. Using the fully automatic biochemical analyzer as the reference method, fresh venous blood samples at five different concentration gradients were tested for on-site comparison. Bias was assessed using Bland-Altman analysis, followed by risk tracing and intervention.

The results showed that correlation coefficients (r) of the three brands of glucose meters and the biochemical analyzer were all above 0.99. However, at a biochemical analyzer measurement value of 13.1 mmol/L, Bland-Altman analysis results showed systematic negative bias in Brand Q and H (bias of -0.403 mmol/L and -0.688 mmol/L respectively) and the relative bias ranges were -16.79% to -7.63% for Brand Q and -17.56% to -9.16% for Brand H, with a few points exceeding the conventional ±15% error limit. Although an overall pass rate of 100% was achieved for all the three brands based on conventional standard, this strategy successfully identified the concealed concentration-dependent bias. The data analysis revealed that under the same experimental conditions, detection systems of different brands showed significant response inconsistency at high concentration ranges.

The strategy validated that with limited healthcare resource, risk-oriented sampling was able to effectively identify the systematic negative bias at high concentration ranges for devices with specific brands, which is concealed by conventional pass rate evaluation. These findings provide an evidence-based foundation for management strategy on implementing dynamic calibration of blood glucose POCT devices (to correct systematic drift), establishing of scientific retirement criteria, and implementing of targeted clinical supervision (to mitigate potential error accumulation).