PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 15360766

Patterns of usage for a Web-based clinical information system.

Elizabeth S Chen·James J Cimino
View original source ↗Export metadata ↓

Abstract

Understanding how clinicians are using clinical information systems to assist with their everyday tasks is valuable to the system design and development process. Developers of such systems are interested in monitoring usage in order to make enhancements. System log files are rich resources for gaining knowledge about how the system is being used. We have analyzed the log files of our Web-based clinical information system (WebCIS) to obtain various usage statistics including which WebCIS features are frequently being used. We have also identified usage patterns, which convey how the user is traversing the system. We present our method and these results as well as describe how the results can be used to customize menus, shortcut lists, and patient reports in WebCIS and similar systems.

Explore related subjects

Data CollectionDatabases as TopicInformation ServicesInformation SystemsInternetMedical Records Systems, ComputerizedJournal ArticleResearch Support, N.I.H., ExtramuralResearch Support, U.S. Gov't, P.H.S.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Elizabeth S Chen, James J Cimino. 2004. Patterns of usage for a Web-based clinical information system.. https://pubmed.ncbi.nlm.nih.gov/15360766/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2007

Probability estimation when some observations are grouped.

This paper considers the use of additional questions for decreasing survey non-response rates and an approach for estimating a probability based on the results obtained. In a survey, the respondents are asked to answer an original question and follow-up questions, where the answers for the follow-up questions are grouped answers for the original question. For example, respondents are asked to provide an exact number of incidents, but in cases of 'Do not know' or 'Refuse' responses, they are subsequently asked to pick an answer from a less specific categorical scale. The new estimator obtains smaller variance asymptotically and does not depend on a distribution family. This method is applied to income questions in a survey regarding injury prevention and behaviours. Another application is survey data on intimate partner violence, where some amendments were applied for incorporating post-stratification weights and for using non-random grouping. For additional illustration, an example of parameter estimation on artificially generated data is presented.

Data Collection↗