Literature DB >> 19448882

Clinical decision support system for point of care use--ontology-driven design and software implementation.

K Farion1, W Michalowski, S Wilk, D O'Sullivan, S Rubin, D Weiss.   

Abstract

OBJECTIVES: The objective of this research was to design a clinical decision support system (CDSS) that supports heterogeneous clinical decision problems and runs on multiple computing platforms. Meeting this objective required a novel design to create an extendable and easy to maintain clinical CDSS for point of care support. The proposed solution was evaluated in a proof of concept implementation.
METHODS: Based on our earlier research with the design of a mobile CDSS for emergency triage we used ontology-driven design to represent essential components of a CDSS. Models of clinical decision problems were derived from the ontology and they were processed into executable applications during runtime. This allowed scaling applications' functionality to the capabilities of computing platforms. A prototype of the system was implemented using the extended client-server architecture and Web services to distribute the functions of the system and to make it operational in limited connectivity conditions.
RESULTS: The proposed design provided a common framework that facilitated development of diversified clinical applications running seamlessly on a variety of computing platforms. It was prototyped for two clinical decision problems and settings (triage of acute pain in the emergency department and postoperative management of radical prostatectomy on the hospital ward) and implemented on two computing platforms--desktop and handheld computers.
CONCLUSIONS: The requirement of the CDSS heterogeneity was satisfied with ontology-driven design. Processing of application models described with the help of ontological models allowed having a complex system running on multiple computing platforms with different capabilities. Finally, separation of models and runtime components contributed to improved extensibility and maintainability of the system.

Entities:  

Mesh:

Year:  2009        PMID: 19448882     DOI: 10.3414/ME0574

Source DB:  PubMed          Journal:  Methods Inf Med        ISSN: 0026-1270            Impact factor:   2.176


  7 in total

1.  Implementing an integrative multi-agent clinical decision support system with open source software.

Authors:  Jelber Sayyad Shirabad; Szymon Wilk; Wojtek Michalowski; Ken Farion
Journal:  J Med Syst       Date:  2010-03-18       Impact factor: 4.460

2.  [International outcomes from attempts to implement a clinical decision support system in gastroenterology].

Authors:  Josceli Maria Tenório; Anderson Diniz Hummel; Vera Lucia Sdepanian; Ivan Torres Pisa; Heimar de Fátima Marin
Journal:  J Health Inform       Date:  2011 Jan-Mar

3.  A Semantic-Based Model for Triage Patients in Emergency Departments.

Authors:  Guilherme Wunsch; Cristiano A da Costa; Rodrigo R Righi
Journal:  J Med Syst       Date:  2017-03-10       Impact factor: 4.460

4.  Clinically derived early postoperative pain trajectories differ by age, sex, and type of surgery.

Authors:  Patrick J Tighe; Linda T Le-Wendling; Ameet Patel; Baiming Zou; Roger B Fillingim
Journal:  Pain       Date:  2015-04       Impact factor: 7.926

5.  Design of activation functions for inference of fuzzy cognitive maps: application to clinical decision making in diagnosis of pulmonary infection.

Authors:  In Keun Lee; Hwa Sun Kim; Hune Cho
Journal:  Healthc Inform Res       Date:  2012-06-30

6.  Mobile monitoring and reasoning methods to prevent cardiovascular diseases.

Authors:  Ramón Hervás; Jesús Fontecha; David Ausín; Federico Castanedo; José Bravo; Diego López-de-Ipiña
Journal:  Sensors (Basel)       Date:  2013-05-16       Impact factor: 3.576

7.  TrhOnt: building an ontology to assist rehabilitation processes.

Authors:  Idoia Berges; David Antón; Jesús Bermúdez; Alfredo Goñi; Arantza Illarramendi
Journal:  J Biomed Semantics       Date:  2016-10-04
  7 in total

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