Modelling the Clinical Processes Of Prescribing (MCPOP)

Projects

Methods, tools and technologies

MCPOP
Modelling the Clinical Processes Of Prescribing

Development of models to support decision support in prescribing

keywords

Main objective

Prescribing, electronic prescribing, information model, decision support systems, knowledge representation, evidence-based healthcare, open source, primary care, hospitals, outreach, quality, safety, consistency, cost effectiveness; asthma

Development of a formal information model of pharmaceutical practice to guide the development of integrated and evidence-based decision support systems in prescribing.

summary

The project aims to meet the following objectives defined by the Australian GPCG and the NPS for pharmaceutical decision support:

"Develop a formal information model of pharmaceutical practice (using as a starting point the Australian General Practice Computing Group Data Model and Core Data Set (GPDMCDS))
"Develop a reference implementation of the information model, integrated with the Australian drug database, to be the basis for a functional prototype of prescribing decision support. This will subsequently be extended to include all pharmaceutical practice.

"The information model and reference implementation developed by the project will be open source software, allowing (and encouraging) software developers to develop a functional prototype linking the clinically based information model with the decision support drug reference database. This open-source decision support engine will be made available to organisations that develop prescribing, dispensing and administering software so that they can link to it, thereby facilitating access to best-evidence, decision support resources."

references

Liaw ST, Sulaiman N, Pearce C et al. Falls prevention within the Australian general practice data model: methodology, information model, and terminology issues. J Am Med Inform Assoc. 2003 Sep-Oct;10(5):425-32.

[PubMed] []

('Falls' as in falling down through old age or frailty)

" 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. "

General Practice Data Model and Core Data Set Project Final Project Report. (Prepared by Simsion Bowles and Associates for the Commonwealth Department of Health and Aged Care, September 2000.

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" The General Practice (GP) Data Model and Core Data Set project is one of a suite of projects undertaken as part of the GP IM&T Strategic Framework workplan to build a technological infrastructure to assist general practitioners to improve health outcomes in patient care and practice management. The project objective was to determine and publish an agreed set of “core” data items (the General Practice Core Data Set) that represent the elements of the information appropriate to the clinical management of a patient by a general practitioner and appropriate to the effective management of a practice. "

start date

end date

location

support

January 2004

End 2004

Departments of Rural Health and Information Systems, University of Melbourne

Australian Department of Health and Ageing and the National Prescribing Service

contact

links

Prof. Teng Liaw
University of Melbourne
School of Rural Health
49 Graham Street
PO Box 6500
Shepparton VIC 3632
Australia