Influence of physician networks on prescribing a new ingredient combination in heart failure: a longitudinal claim data-based study

Table 3 Network characteristics in 2017 from prescriber versus non-prescriber in 2018

	Total	Non-prescriber	Prescriber	p-value
	N = 7831 (100%) (median, IQR)	n = 4873 (62.2%) (median, IQR)	n = 2958 (37.8%) (median, IQR)	p-value
Link to ARNI, n (%)				< 0.001^a
Few (0–5 links)	3212 (41.0)	2342 (48.1)	870 (29.4)
Medium (6–10 links)	2521 (32.2)	1431 (29.4)	1090 (36.9)
Many (> 10 links)	2098 (26.8)	1100 (22.6)	998 (33.7)
Degree centrality	27 (25)	23 (24)	31 (25)	< 0.001^b
Constraint	0.07 (0.05)	0.08 (0.06)	0.06 (0.03)	< 0.001^b
Betweenness centrality	0.02 (0.10)	0.01 (0.08)	0.03 (0.14)	< 0.001^b

^aChi-squared test,^bWilcoxon’s test
ARNI angiotensin receptor and neprilysin inhibitor
Degree measures the number of connections an actor has in the network (values 0 to 7.830)
Constraint measures the extent to which time and energy is concentrated within a single cluster of connections (values 0 to 1)
Betweenness centrality measures the proportion of pathways in the whole network for which the physician of interest is on the shortest path (values 0 to 1)