期刊论文详细信息
BMC Medical Informatics and Decision Making
Health care public reporting utilization – user clusters, web trails, and usage barriers on Germany’s public reporting portal Weisse-Liste.de
Research Article
Lars-Henrik Averdunk1  Alexander Geissler1  Christoph Pross1  Reinhard Busse2  Josip Stjepanovic3 
[1] Dept. of Health Care Management, Berlin University of Technology, Administrative office H80, Str. des 17. Juni 135, 10623, Berlin, Germany;Dept. of Health Care Management, Berlin University of Technology, Administrative office H80, Str. des 17. Juni 135, 10623, Berlin, Germany;European Observatory on Health Systems and Policies, WHO European Centre for Health Policy, Eurostation (Office 07C020), Place Victor Horta/Victor Hortaplein 40/10, 1060, Brussels, Belgium;Weisse Liste gGmbH, Leipziger Straße 124, 10117, Berlin, Germany;
关键词: Public reporting;    Quality transparency;    Hospital quality;    Provider benchmarking portal;    Web usage mining;    Cluster analysis;    Markov chains;    Clickstream analysis;   
DOI  :  10.1186/s12911-017-0440-6
 received in 2016-11-29, accepted in 2017-04-04,  发布年份 2017
来源: Springer
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【 摘 要 】

BackgroundQuality of care public reporting provides structural, process and outcome information to facilitate hospital choice and strengthen quality competition. Yet, evidence indicates that patients rarely use this information in their decision-making, due to limited awareness of the data and complex and conflicting information. While there is enthusiasm among policy makers for public reporting, clinicians and researchers doubt its overall impact. Almost no study has analyzed how users behave on public reporting portals, which information they seek out and when they abort their search.MethodsThis study employs web-usage mining techniques on server log data of 17 million user actions from Germany’s premier provider transparency portal Weisse-Liste.de (WL.de) between 2012 and 2015. Postal code and ICD search requests facilitate identification of geographical and treatment area usage patterns. User clustering helps to identify user types based on parameters like session length, referrer and page topic visited. First-level markov chains illustrate common click paths and premature exits.ResultsIn 2015, the WL.de Hospital Search portal had 2,750 daily users, with 25% mobile traffic, a bounce rate of 38% and 48% of users examining hospital quality information. From 2013 to 2015, user traffic grew at 38% annually. On average users spent 7 min on the portal, with 7.4 clicks and 54 s between clicks. Users request information for many oncologic and orthopedic conditions, for which no process or outcome quality indicators are available. Ten distinct user types, with particular usage patterns and interests, are identified. In particular, the different types of professional and non-professional users need to be addressed differently to avoid high premature exit rates at several key steps in the information search and view process. Of all users, 37% enter hospital information correctly upon entry, while 47% require support in their hospital search.ConclusionsSeveral onsite and offsite improvement options are identified. Public reporting needs to be directed at the interests of its users, with more outcome quality information for oncology and orthopedics. Customized reporting can cater to the different needs and skill levels of professional and non-professional users. Search engine optimization and hospital quality advocacy can increase website traffic.

【 授权许可】

CC BY   
© The Author(s). 2017

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