Source:http://linkedlifedata.com/resource/pubmed/id/12807809
Switch to
Predicate | Object |
---|---|
rdf:type | |
lifeskim:mentions | |
pubmed:issue |
5
|
pubmed:dateCreated |
2003-10-13
|
pubmed:abstractText |
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.
|
pubmed:commentsCorrections |
http://linkedlifedata.com/resource/pubmed/commentcorrection/12807809-11120721,
http://linkedlifedata.com/resource/pubmed/commentcorrection/12807809-7580494,
http://linkedlifedata.com/resource/pubmed/commentcorrection/12807809-8256973,
http://linkedlifedata.com/resource/pubmed/commentcorrection/12807809-8917873,
http://linkedlifedata.com/resource/pubmed/commentcorrection/12807809-8930856
|
pubmed:language |
eng
|
pubmed:journal | |
pubmed:citationSubset |
IM
|
pubmed:status |
MEDLINE
|
pubmed:issn |
1067-5027
|
pubmed:author | |
pubmed:issnType |
Print
|
pubmed:volume |
10
|
pubmed:owner |
NLM
|
pubmed:authorsComplete |
Y
|
pubmed:pagination |
425-32
|
pubmed:dateRevised |
2009-11-18
|
pubmed:meshHeading |
pubmed-meshheading:12807809-Accidental Falls,
pubmed-meshheading:12807809-Artificial Intelligence,
pubmed-meshheading:12807809-Australia,
pubmed-meshheading:12807809-Decision Support Systems, Clinical,
pubmed-meshheading:12807809-Decision Support Techniques,
pubmed-meshheading:12807809-Family Practice,
pubmed-meshheading:12807809-Humans,
pubmed-meshheading:12807809-Questionnaires,
pubmed-meshheading:12807809-Risk Assessment,
pubmed-meshheading:12807809-Software,
pubmed-meshheading:12807809-Terminology as Topic
|
pubmed:articleTitle |
Falls prevention within the Australian general practice data model: methodology, information model, and terminology issues.
|
pubmed:affiliation |
MBBS, Department of General Practice, The University of Melbourne, 200 Berkeley Street, Carlton, VIC 3053, Australia. t.liaw@unimelb.edu.au
|
pubmed:publicationType |
Journal Article,
Research Support, Non-U.S. Gov't
|