Size rules life, but does it in the assessment of medical vigilance best practice? Towards a testable hypothesis

The goal of this paper is to infer the applicability of scaling concepts to haemovigilance based on the study of the relationship between severe adverse reactions and events (SARE) and blood transfusions (BT). We hypothesize that in a haemovigilance operating optimally, SARE should be a power-law function of BT as SARE=αBTβ. We investigated the relationship between yearly BT and the related SARE reported in 12 French hospitals of the Picardie State from 2004 to 2015. First we found that when integrated over the whole period 2004-2015, SARE were significantly described by a power-law function SARE ∝ BT1.51 for 10 of the 12 hospitals considered. The numbers of SARE in these two hospitals is drastically over-estimated by this power-law, that is 1.9- to 4.3-fold lower than those predicted by the power-law. When considered on a yearly basis, we consistently found that SARE was also significantly described by a power-law function of the form SARE ∝ BT1.44 for 10 of the 12 hospitals considered. In turn, the occurrence of SARE in the two other hospitals was strongly over-estimated by this power-law, though it is also significantly described by another power-law, SARE ∝ BT1.11. We specified these results through separate yearly analyses and found the relationship between SARE and BT was best described by a power-law with β=0.90 in 2004, a linear relationship from 2005 to 2007 and a power-law with β ranging from 1.49 and 1.92 from 2008 to 2014. Finally, in 2015, the relationship between SARE and BT was significantly described by a power-law SARE ∝ BT1.17 for the 12 hospitals considered. Overall, our results suggest that hospitals performing more blood transfusions are more efficient as the observed negative effects of blood transfusions increase relatively slower than in hospitals performing less transfusions.