A task-based support architecture for developing point-of-care clinical decision support systems for the emergency department

Methods Inf Med. 2013;52(1):18-32. doi: 10.3414/ME11-01-0099. Epub 2012 Dec 12.


Objectives: The purpose of this study was to create a task-based support architecture for developing clinical decision support systems (CDSSs) that assist physicians in making decisions at the point-of-care in the emergency department (ED). The backbone of the proposed architecture was established by a task-based emergency workflow model for a patient-physician encounter.

Methods: The architecture was designed according to an agent-oriented paradigm. Specifically, we used the O-MaSE (Organization-based Multi-agent System Engineering) method that allows for iterative translation of functional requirements into architectural components (e.g., agents). The agent-oriented paradigm was extended with ontology-driven design to implement ontological models representing knowledge required by specific agents to operate.

Results: The task-based architecture allows for the creation of a CDSS that is aligned with the task-based emergency workflow model. It facilitates decoupling of executable components (agents) from embedded domain knowledge (ontological models), thus supporting their interoperability, sharing, and reuse. The generic architecture was implemented as a pilot system, MET3-AE--a CDSS to help with the management of pediatric asthma exacerbation in the ED. The system was evaluated in a hospital ED.

Conclusions: The architecture allows for the creation of a CDSS that integrates support for all tasks from the task-based emergency workflow model, and interacts with hospital information systems. Proposed architecture also allows for reusing and sharing system components and knowledge across disease-specific CDSSs.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Asthma / therapy
  • Computer Simulation
  • Computer Systems*
  • Decision Support Systems, Clinical*
  • Emergency Service, Hospital*
  • Humans
  • Knowledge Bases
  • Pilot Projects
  • Point-of-Care Systems*
  • Risk Management
  • Workflow