Clinical modeling--a critical analysis

Int J Med Inform. 2014 Jan;83(1):57-69. doi: 10.1016/j.ijmedinf.2013.09.003. Epub 2013 Oct 3.

Abstract

Background: Modeling clinical processes (and their informational representation) is a prerequisite for optimally enabling and supporting high quality and safe care through information and communication technology and meaningful use of gathered information.

Objectives: The paper investigates existing approaches to clinical modeling, thereby systematically analyzing the underlying principles, the consistency with and the integration opportunity to other existing or emerging projects, as well as the correctness of representing the reality of health and health services.

Methods: The analysis is performed using an architectural framework for modeling real-world systems. In addition, fundamental work on the representation of facts, relations, and processes in the clinical domain by ontologies is applied, thereby including the integration of advanced methodologies such as translational and system medicine.

Results: The paper demonstrates fundamental weaknesses and different maturity as well as evolutionary potential in the approaches considered. It offers a development process starting with the business domain and its ontologies, continuing with the Reference Model-Open Distributed Processing (RM-ODP) related conceptual models in the ICT ontology space, the information and the computational view, and concluding with the implementation details represented as engineering and technology view, respectively.

Conclusion: The existing approaches reflect at different levels the clinical domain, put the main focus on different phases of the development process instead of first establishing the real business process representation and therefore enable quite differently and partially limitedly the domain experts' involvement.

Keywords: Architectural framework; Clinical models; Data elements; Knowledge representation; Ontologies.

MeSH terms

  • Communication
  • Decision Support Systems, Clinical*
  • Humans
  • Medical Record Linkage*
  • Medical Records Systems, Computerized*
  • Quality of Health Care*
  • Safety Management