Validating archetypes for the Multiple Sclerosis Functional Composite

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• 作者：Michael Braun (5)
  Alexander Ulrich Brandt (6) (7)
  Stefan Schulz (5) (8)
  Martin Boeker (5)
  
  5. Center for Medical Biometry and Medical Informatics ; Medical Center 鈥?University of Freiburg ; Stefan-Meier-Str. 26 ; 79104 ; Freiburg ; Germany
  6. NeuroCure Clinical Research Center ; Charit茅 鈥?Universit盲tsmedizin Berlin ; Charit茅platz 1 ; 10117 ; Berlin ; Germany
  7. Motognosis UG ; Debenzer Str. 73 ; 12683 ; Berlin ; Germany
  8. Institute for Medical Informatics ; Statistics and Documentation ; Medical University of Graz ; Auenbruggerplatz 2 ; 8036 ; Graz ; Austria
  
• 关键词：Electronic health records ; Multiple sclerosis ; Medical documentation ; Information models ; Archetypes
• 刊名：BMC Medical Informatics and Decision Making
• 出版年：2014
• 出版时间：December 2014
• 年：2014
• 卷：14
• 期：1
• 全文大小：590 KB
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  50. The pre-publication history for this paper can be accessed here:6947/14/64/prepub" class="a-plus-plus">http://www.biomedcentral.com/1472-6947/14/64/prepub
  
• 刊物主题：Health Informatics; Information Systems and Communication Service; Management of Computing and Information Systems;
• 出版者：BioMed Central
• ISSN：1472-6947

文摘

Background Numerous information models for electronic health records, such as openEHR archetypes are available. The quality of such clinical models is important to guarantee standardised semantics and to facilitate their interoperability. However, validation aspects are not regarded sufficiently yet. The objective of this report is to investigate the feasibility of archetype development and its community-based validation process, presuming that this review process is a practical way to ensure high-quality information models amending the formal reference model definitions. Methods A standard archetype development approach was applied on a case set of three clinical tests for multiple sclerosis assessment: After an analysis of the tests, the obtained data elements were organised and structured. The appropriate archetype class was selected and the data elements were implemented in an iterative refinement process. Clinical and information modelling experts validated the models in a structured review process. Results Four new archetypes were developed and publicly deployed in the openEHR Clinical Knowledge Manager, an online platform provided by the openEHR Foundation. Afterwards, these four archetypes were validated by domain experts in a team review. The review was a formalised process, organised in the Clinical Knowledge Manager. Both, development and review process turned out to be time-consuming tasks, mostly due to difficult selection processes between alternative modelling approaches. The archetype review was a straightforward team process with the goal to validate archetypes pragmatically. Conclusions The quality of medical information models is crucial to guarantee standardised semantic representation in order to improve interoperability. The validation process is a practical way to better harmonise models that diverge due to necessary flexibility left open by the underlying formal reference model definitions. This case study provides evidence that both community- and tool-enabled review processes, structured in the Clinical Knowledge Manager, ensure archetype quality. It offers a pragmatic but feasible way to reduce variation in the representation of clinical information models towards a more unified and interoperable model.