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

Overview of attention for article published in BMC Medical Informatics and Decision Making, April 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (54th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

Mentioned by

policy
1 policy source

Citations

dimensions_citation
18 Dimensions

Readers on

mendeley
75 Mendeley
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Title
Health care public reporting utilization – user clusters, web trails, and usage barriers on Germany’s public reporting portal Weisse-Liste.de
Published in
BMC Medical Informatics and Decision Making, April 2017
DOI 10.1186/s12911-017-0440-6
Pubmed ID
Authors

Christoph Pross, Lars-Henrik Averdunk, Josip Stjepanovic, Reinhard Busse, Alexander Geissler

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 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. In 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. Several 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.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 75 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 20 27%
Student > Ph. D. Student 8 11%
Researcher 6 8%
Student > Bachelor 5 7%
Student > Doctoral Student 3 4%
Other 10 13%
Unknown 23 31%
Readers by discipline Count As %
Medicine and Dentistry 11 15%
Nursing and Health Professions 8 11%
Computer Science 4 5%
Business, Management and Accounting 4 5%
Economics, Econometrics and Finance 4 5%
Other 17 23%
Unknown 27 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 April 2022.
All research outputs
#7,454,066
of 22,788,370 outputs
Outputs from BMC Medical Informatics and Decision Making
#763
of 1,986 outputs
Outputs of similar age
#119,186
of 309,253 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#13
of 35 outputs
Altmetric has tracked 22,788,370 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,986 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 58% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 309,253 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.