Towards a Traceable Clinical Guidelines Application

OBJECTIVES The goal of this research is to provide an overall framework to enable model-based development of clinical guideline-based decision support systems (GBDSSs). The automatically generated GBDSSs are aimed at providing guided support to the physician during the application of guidelines and automatically storing guideline application data for traceability purposes. METHODS The development process of a GBDSS for a guideline is based on model-driven development (MDD) techniques which allow us to carry out such a process automatically, making development more agile and saving on human resource costs. We use UML Statecharts to represent the dynamics of guidelines and, based on this model, we use a MDD-based tool chain to generate the guideline-dependent components of each GBDSS in an automatic way. In particular, as for the traceability capabilities of each GBDSS, MDD techniques are combined with database schema mappings for metadata management in order to automatically generate the GBDSS-persistent component as one of the main contributions of this paper. RESULTS The complete framework has been implemented as an Eclipse plug-in named GBDSSGenerator which, starting from the statechart representing a guideline, allows the development process to be carried out automatically by only selecting different menu options the plug-in provides. We have successfully validated our overall approach by generating the GBDSS for different types of clinical guidelines, even for laboratory guidelines. CONCLUSIONS The proposed framework allows the development of clinical guideline-based decision support systems in an automatic way making this process more agile and saving on human resource costs.

[1]  Martin Gogolla,et al.  Realizing UML Metamodel Transformations with AGG , 2004, GT-VMT@ETAPS.

[2]  Antonio Moreno,et al.  Computer-based execution of clinical guidelines: A review , 2008, Int. J. Medical Informatics.

[3]  S. Timmermans,et al.  The promises and pitfalls of evidence-based medicine. , 2005, Health affairs.

[4]  Yingjun Zhang,et al.  Broad-spectrum studies of log file analysis , 2000, Proceedings of the 2000 International Conference on Software Engineering. ICSE 2000 the New Millennium.

[5]  Silvia Miksch,et al.  Improving Clinical Guideline Implementation Through Prototypical Design Patterns , 2005, AIME.

[6]  John Fox,et al.  Comparing computer-interpretable guideline models: a case-study approach. , 2003, Journal of the American Medical Informatics Association : JAMIA.

[7]  Ralph Johnson,et al.  design patterns elements of reusable object oriented software , 2019 .

[8]  D. Bates,et al.  Effects of computerized physician order entry on prescribing practices. , 2000, Archives of internal medicine.

[9]  G J Kuperman,et al.  A randomized trial of a computer-based intervention to reduce utilization of redundant laboratory tests. , 1999, The American journal of medicine.

[10]  Martin Gogolla,et al.  Analysis of UML Stereotypes within the UML Metamodel , 2002, UML.

[11]  D. Bates,et al.  Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review. , 2003, Archives of internal medicine.

[12]  Bran Selic,et al.  The Pragmatics of Model-Driven Development , 2003, IEEE Softw..

[13]  Omolola Ogunyemi,et al.  Design and implementation of the GLIF3 guideline execution engine , 2004, J. Biomed. Informatics.

[14]  Carla Simone,et al.  Knowledge Artifacts as Bridges between Theory and Practice: The Clinical Pathway Case , 2008 .

[15]  Iftikhar Azim Niaz,et al.  Automatic code generation from UML class and statechart diagrams , 2005 .

[16]  Ana R. Cavalli,et al.  New approaches for passive testing using an Extended Finite State Machine specification , 2003, Inf. Softw. Technol..

[17]  Frank van Harmelen,et al.  Improving medical protocols by formal methods , 2006, Artif. Intell. Medicine.

[18]  Sushil Jajodia,et al.  Temporal Databases: Theory, Design, and Implementation , 1993 .

[19]  Arie Hasman,et al.  Approaches for creating computer-interpretable guidelines that facilitate decision support , 2004, Artif. Intell. Medicine.

[20]  Jiexin Lian,et al.  Simulation-based analysis of UML statechart diagrams: methods and case studies , 2007, Software Quality Journal.

[21]  Gerhard Weikum,et al.  Workflow history management in virtual enterprises using a light-weight workflow management system , 1999, Proceedings Ninth International Workshop on Research Issues on Data Engineering: Information Technology for Virtual Enterprises. RIDE-VE'99.

[22]  Yuval Shahar,et al.  Timing Is Everything: Temporal Reasoning and Temporal Data Maintenance in Medicine , 1999, AIMDM.

[23]  Alexander Ran,et al.  Tracing execution of software for design coverage , 2001, Proceedings 16th Annual International Conference on Automated Software Engineering (ASE 2001).

[24]  Ivan Porres,et al.  A Model Driven Approach to Automate the Implementation of Clinical Guidelines in Decision Support Systems , 2008, 15th Annual IEEE International Conference and Workshop on the Engineering of Computer Based Systems (ecbs 2008).

[25]  Ivan Porres,et al.  Verification of Clinical Guidelines by Model Checking , 2008, 2008 21st IEEE International Symposium on Computer-Based Medical Systems.

[26]  Ivan Porres,et al.  Development of an Ubiquitous Decision Support System for Clinical Guidelines using MDA , 2007, CAiSE Forum.

[27]  Eladio Domínguez,et al.  Tracing the Application of Clinical Guidelines , 2008, APWeb Workshops.

[28]  Eladio Domínguez Murillo,et al.  Protocolos médicos para la toma de decisiones en un contexto de Computación Ubicua , 2005 .