This Article Full Text Full Text (PDF) Table 2 All Versions of this Article: M1281v1 10/5/425    most recent Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Liaw, S.-T. Articles by Ng, C.-K. Search for Related Content PubMed PubMed Citation Articles by Liaw, S.-T. Articles by Ng, C.-K.

Falls Prevention within the Australian General Practice Data Model: Methodology, Information Model, and Terminology Issues

Affiliations of the authors: The University of Melbourne Department of General Practice, Melbourne, Victoria, Australia (S-TL, NS, CP, JS, JT); National Ageing Research Institute, Melbourne, Victoria, Australia (KH); La Trobe University, Melbourne, Victoria, Australia (HG); Swinburne University, Melbourne, Victoria, Australia (C-KN)

Correspondence and reprints: Professor Siaw-Teng Liaw, MBBS, PhD, Department of General Practice, The University of Melbourne, 200 Berkeley Street, Carlton, VIC 3053, Australia; e-mail: <t.liaw{at}unimelb.edu.au>.

Received for publication: 10/29/02; accepted for publication: 05/15/03.

The iterative development of the Falls Risk Assessment and Management System (FRAMS) drew upon research evidence and early consumer and clinician input through focus groups, interviews, direct observations, and an online questionnaire. Clinical vignettes were used to validate the clinical model and program logic, input, and output. The information model was developed within the Australian General Practice Data Model (GPDM) framework. The online FRAMS implementation used available Internet (TCP/IP), messaging (HL7, XML), knowledge representation (Arden Syntax), and classification (ICD10-AM, ICPC2) standards. Although it could accommodate most of the falls prevention information elements, the GPDM required extension for prevention and prescribing risk management. Existing classifications could not classify all falls prevention concepts. The lack of explicit rules for terminology and data definitions allowed multiple concept representations across the terminology–architecture interface. Patients were more enthusiastic than clinicians. A usable standards-based online-distributed decision support system for falls prevention can be implemented within the GPDM, but a comprehensive terminology is required. The conceptual interface between terminology and architecture requires standardization, preferably within a reference information model. Developments in electronic decision support must be guided by evidence-based clinical and information models and knowledge ontologies. The safety and quality of knowledge-based decision support systems must be monitored. Further examination of falls and other clinical domains within the GPDM is needed.

This article has been cited by other articles:

				D A Ganz, G E Alkema, and S Wu It takes a village to prevent falls: reconceptualizing fall prevention and management for older adults Inj. Prev., August 1, 2008; 14(4): 266 - 271. [Abstract] [Full Text] [PDF]

				S.-T. Liaw, E. Deveny, I. Morrison, and B. Lewis Clinical, information and business process modeling to promote development of safe and flexible software. Health Informatics Journal, September 1, 2006; 12(3): 199 - 211. [Abstract] [PDF]