Health care public reporting utilization – user clusters, web trails, and usage barriers on Germany’s public reporting portal Weisse-Liste.de

Table 4 User cluster and their usage characteristics

User cluster	Share [%]	Average number clicks²	Average visit length [sec]²	Time betw. clicks [sec]³	Return visitors [%]	Viewed results [%]	Search steps/results¹	Visit dur. Workday [%]	Working hours [%]	Desktop usage [%]	Access via [%]
Intensive Work Timers	19	15.2	693	45	29	100	0.45	100	100	100	100 search engine
Intensive Free Timers	17	16.4	731	46	13	100	0.42	43	0	100	100 search engine
Diagnosis Translator	13	5.7	182	32	19	-	-	100	100	100	100 search engine
Challenged Aborts	12	6.1	255	48	8	-	-	53	12	69	100 search engine
Patient Experts	9	16.7	851	54	24	100	0.33	63	12	66	100 direct
Curious	7	14.9	747	49	28	78	0.60	83	53	83	35 payer, 30 media
Professionals	7	15.9	884	53	56	100	0.32	100	100	100	100 direct
Results Mobiles	7	14.5	696	49	8	100	0.50	65	30	0	100 search engine
Explorers	4	13.4	571	47	14	72	0.67	77	48	80	100 health website
Other	5	6.5	456	72	40		-	79	42	74	100 direct
Average User	100	12.7	596	47	22	68	0.42	76	51	83	67 search engine

Clustering based on clickstream data and repeated sampling from data sample from 01/2015 – 05/2015 excluding bounce visits
1. Search steps required relative to number of results viewed; 2. all clicks or visit lengths in sec per user cluster/number of users in cluster (weighted average); 3. Calculated per session and then averaged for user cluster (simple, non-weighted average)

ISSN: 1472-6947