Health Informatics Journal

 

Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Register here to gain access to SAGE's 500+ Journals Online

Click here to sign up for SAGE Journal Email Alerts today!

Sign In to gain access to subscriptions and/or personal tools.
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Liaw, S.-T.
Right arrow Articles by Lewis, B.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?
Health Informatics Journal, Vol. 12, No. 3, 199-211 (2006)
DOI: 10.1177/1460458206066772

Clinical, information and business process modeling to promote development of safe and flexible software

Siaw-Teng Liaw, PhD, FRACGP, FACHI

School of Rural Health, The University of Melbourne, Graham Street, Shepparton, Victoria 3630, Australia, t.liaw{at}unimelb.edu.au

Elizabeth Deveny

School of Rural Health, University of Melbourne Therapeutic Guidelines Limited

Iain Morrison

Department of Information Systems, University of Melbourne

Bryn Lewis

Department of Information Systems, University of Melbourne National Prescribing Service

Using a factorial vignette survey and modeling methodology, we developed clinical and information models -incorporating evidence base, key concepts, relevant terms, decision-making and workflow needed to practice safely and effectively -to guide the development of an integrated rule-based knowledge module to support prescribing decisions in asthma. We identified workflows, decision-making factors, factor use, and clinician information requirements. The Unified Modeling Language (UML) and public domain software and knowledge engineering tools (e.g. Protégé) were used, with the Australian GP Data Model as the starting point for expressing information needs. A Web Services service-oriented architecture approach was adopted within which to express functional needs, and clinical processes and workflows were expressed in the Business Process Execution Language (BPEL). This formal analysis and modeling methodology to define and capture the process and logic of prescribing best practice in a reference implementation is fundamental to tackling deficiencies in prescribing decision support software.

Key Words: clinical model • electronic decision support • evidence-based practice • information model • safe prescribing


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?