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Main Title: Health care public reporting utilization
Subtitle: user clusters, web trails, and usage barriers on Germany’s public reporting portal
Author(s): Pross, Christoph
Averdunk, Lars-Henrik
Stjepanovic, Josip
Busse, Reinhard
Geissler, Alexander
Type: Article
Language Code: en
Is Part Of: 10.14279/depositonce-6139
Abstract: Quality 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. This study employs web-usage mining techniques on server log data of 17 million user actions from Germany’s premier provider transparency portal ( 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. In 2015, the 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.
Issue Date: 2017
Date Available: 30-Jan-2018
DDC Class: 610 Medizin und Gesundheit
Subject(s): public reporting
quality transparency
hospital quality
provider benchmarking portal
web usage mining
cluster analysis
Markov chains
clickstream analysis
Sponsor/Funder: TU Berlin, Open-Access-Mittel - 2017
Journal Title: BMC medical informatics and decision making
Publisher: BioMed Central
Publisher Place: London
Volume: 17
Article Number: 48
Publisher DOI: 10.1186/s12911-017-0440-6
ISSN: 1472-6947
Appears in Collections:FG Management im Gesundheitswesen » Publications

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