Using a Service Oriented Architecture Approach to Clinical Decision Support: Performance Results from Two CDS Consortium Demonstrations

The Clinical Decision Support Consortium has completed two demonstration trials involving a web service for the execution of clinical decision support (CDS) rules in one or more electronic health record (EHR) systems. The initial trial ran in a local EHR at Partners HealthCare. A second EHR site, associated with Wishard Memorial Hospital, Indianapolis, IN, was added in the second trial. Data were gathered during each 6 month period and analyzed to assess performance, reliability, and response time in the form of means and standard deviations for all technical components of the service, including assembling and preparation of input data. The mean service call time for each period was just over 2 seconds. In this paper we report on the findings and analysis to date while describing the areas for further analysis and optimization as we continue to expand our use of a Services Oriented Architecture approach for CDS across multiple institutions.

[1]  Adam Wright,et al.  Challenges in creating an enterprise clinical rules service. , 2008, AMIA ... Annual Symposium proceedings. AMIA Symposium.

[2]  Jonathan M. Teich,et al.  Application of Information Technology: Automating Complex Guidelines for Chronic Disease: Lessons Learned , 2003, J. Am. Medical Informatics Assoc..

[3]  Paolo Traverso,et al.  Service-Oriented Computing: State of the Art and Research Challenges , 2007, Computer.

[4]  Kensaku Kawamoto,et al.  Model Formulation: The HL7-OMG Healthcare Services Specification Project: Motivation, Methodology, and Deliverables for Enabling a Semantically Interoperable Service-oriented Architecture for Healthcare , 2009, J. Am. Medical Informatics Assoc..

[5]  C. McDonald,et al.  Regenstrief Medical Informatics: Experiences with Clinical Decision Support Systems , 2007 .

[6]  Filip De Turck,et al.  Towards computerizing intensive care sedation guidelines: design of a rule-based architecture for automated execution of clinical guidelines , 2010, BMC Medical Informatics Decis. Mak..

[7]  L. Hayden,et al.  Ten Commandments for Effective Clinical Decision Support: Making the Practice of Evidence-based Medicine a Reality , 2011 .

[8]  Kensaku Kawamoto,et al.  Implementation of a Clinical Decision Support System using a Service Model: Results of a Feasibility Study , 2010, MedInfo.

[9]  Liming Zhu,et al.  Performance Prediction of Service-Oriented Applications based on an Enterprise Service Bus , 2007, 31st Annual International Computer Software and Applications Conference (COMPSAC 2007).

[10]  Tejal K. Gandhi,et al.  Design and implementation of an application and associated services to support interdisciplinary medication reconciliation efforts at an integrated healthcare delivery network. , 2006, Journal of the American Medical Informatics Association : JAMIA.

[11]  Blackford Middleton,et al.  The Clinical Decision Support Consortium , 2009, MIE.

[12]  Adam Wright,et al.  SANDS: A service-oriented architecture for clinical decision support in a National Health Information Network , 2008, J. Biomed. Informatics.

[13]  Sanjeev Kumar,et al.  Does SOA Improve the Supply Chain? An Empirical Analysis of the Impact of SOA Adoption on Electronic Supply Chain Performance , 2007, 2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07).

[14]  J. Marc Overhage,et al.  Details of a Successful Clinical Decision Support System , 2007, AMIA.

[15]  D. Bates,et al.  Detecting alerts, notifying the physician, and offering action items: a comprehensive alerting system. , 1996, Proceedings : a conference of the American Medical Informatics Association. AMIA Fall Symposium.

[16]  Tonya Hongsermeier,et al.  Creating shareable decision support services: an interdisciplinary challenge. , 2010, AMIA ... Annual Symposium proceedings. AMIA Symposium.

[17]  Jonathan M. Teich,et al.  Improving allergy alerting in a computerized physician order entry system , 2000, AMIA.

[18]  Kevin Smith,et al.  Evaluation of a Commercial Rule Engine as a Basis for a Clinical Decision Support Service , 2006, AMIA.

[19]  Diane L. Seger,et al.  Viewpoint Paper: Tiering Drug-Drug Interaction Alerts by Severity Increases Compliance Rates , 2009, J. Am. Medical Informatics Assoc..