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Falls prevention within the Australian general practice data model: methodology, information model, and terminology
Siaw-Teng Liaw1, Nabil Sulaiman, Christopher Pearce
1MBBS, Department of General Practice, The University of Melbourne, 200 Berkeley Street, Carlton, VIC 3053, Australia. t.liaw@unimelb.edu.au
Summary
Developing a falls risk assessment system requires a comprehensive terminology and standardized interfaces for effective clinical decision support. Patients showed more enthusiasm than clinicians for this online tool.
Area of Science:
- Health Informatics
- Clinical Decision Support Systems
- Gerontology
Background:
- Falls are a significant health concern for older adults.
- Effective risk assessment and management are crucial for preventing falls.
- Existing clinical systems often lack integrated falls prevention support.
Purpose of the Study:
- To describe the iterative development of the Falls Risk Assessment and Management System (FRAMS).
- To evaluate the feasibility of implementing a standards-based, online decision support system for falls prevention within the Australian General Practice Data Model (GPDM).
- To identify challenges and requirements for terminology and architectural standardization in clinical informatics.
Main Methods:
- Iterative development incorporating research evidence, consumer, and clinician input.
- Utilized focus groups, interviews, observations, and online questionnaires for development and validation.
- Employed clinical vignettes for model and logic validation.
- Developed the information model within the GPDM framework, leveraging Internet, HL7, XML, Arden Syntax, ICD10-AM, and ICPC2 standards.
Main Results:
- The FRAMS system could be implemented within the GPDM, but extensions were needed for prevention and prescribing risk management.
- Existing classifications could not encompass all falls prevention concepts.
- Lack of explicit rules for terminology and data definitions led to concept representation variability.
- Patients were more receptive to the online system than clinicians.
Conclusions:
- A standards-based online decision support system for falls prevention is feasible within the GPDM, but requires a comprehensive terminology.
- Standardization of the terminology-architecture interface, preferably within a reference information model, is essential.
- Future electronic decision support development should be guided by evidence-based models and ontologies, with ongoing monitoring of safety and quality.