Health care providers are hard-pressed to keep abreast of evidence-based treatment practices and implement them within increasingly time-restricted patient interactions. Automated decision support systems (DSSs) hold great promise as a means to implement best practices and improve patient outcomes, while enhancing clinician efficiency. Patient data are analyzed in the context of an encoded practice guideline to generate evidence-based practice recommendations tailored to individual patients and available to providers at the point of patient care.
The primary objectives of this Academic Expert Supplement (AES) for the Center for Health Care Evaluation (CHCE) were to (1) facilitate conceptual knowledge transfer between Stanford Medical Informatics (SMI) experts and VA investigators and project managers in issues underlying the development and implementation of DSSs that can be integrated with VA technology; and (2) facilitate technological knowledge transfer between SMI experts and (a) “knowledge modelers” on the use of PROTEGE for encoding practice guidelines, and (b) IT professionals, such as programmers and software engineers, on the use of the EON technology and software tools developed by SMI, and on interfacing DSSs with the VA clinical information system.
Through formal training workshops and hands-on mentoring, SMI and associated experts trained CHCE investigators and project managers, as well as VA staff more broadly, regarding the development, implementation, and evaluation of automated decision support systems, and the functions of the SMI PROTEGE tool and EON architecture in such systems. PROTEGE can be used to encode practice guidelines in computer interpretable form. The EON architecture can be applied to reason about patient data in the context of an encoded guideline and provide practice advisories. SMI experts also met with staff from the VA Office of Information (OI) to discuss the functions and accommodation of decision support systems in the VA's re-engineered clinical information system.
SMI and other experts presented a two-day workshop on "Using EON Technology to Develop Clinical Decision Support Systems for Guideline-Based Care" in June, 2005. This initial workshop, which had 25 participants, was targeted mainly toward local investigators and IRMS and other staff. The topics included an introduction to clinical decision support; an overview of PROTEGE and guideline knowledge bases; an overview of the EON components and architecture; a description of the ATHENA-Hypertension decision support system, which is based on PROTEGE and EON, and its deployment in VA; and an overview of the VA information technology environment.
A two-day meeting on "Automated Clinical Decision Support: Integrating ATHENA/EON/ PROTÉGÉ with VA Information Systems" was held in July, 2005. The meeting was organized and chaired by Dr. Goldstein of CHCE, and allowed SMI experts to interact with representatives from the Office of Information and other VA entities. OI representatives presented high level functional requirements for clinical decision support in VA. SMI experts provided overviews of the PROTEGE tool and EON architecture. The ATHENA-Hypertension DSS was demonstrated and its integration in the VA clinical information system discussed. Steps for future interaction were outlined. Among the 41 participants were multiple representatives from Office of Information, My Health eVet, CPRS Re-engineering, Laboratory Re-engineering, Pharmacy Re-engineering, Surgery, and VIReC.
A two-day workshop on "Guidelines Modeling" was held in March, 2006. It provided training on how to conceptualize a practice guideline to facilitate encoding. Then, participants used PROTEGE to encode a practice guideline and to test and validate the resulting knowledge base. The workshop had 24 participants, including a Medical Informatist/Physician from VACO, two VIReC representatives, a Clinical Applications Coordinator, two representatives from the CHF QUERI, two attendees from the Atlanta VA Medical Center who are developing decision support for diabetes care, a Stroke QUERI representative, and a member of the Pharmacy Re-engineering team.
Throughout the grant period, AES experts provided intensive hands-on training and mentoring to local VA teams in designing and developing an ATHENA-based decision support system for managing opioid therapy for chronic pain, and in updating the knowledge base and refining the software architecture for the ATHENA-Hypertension DSS. In addition, consulting was provided to another VA team in the design of a proposed decision support system for the management of kidney disease.
This project is contributing to the capacity of VA to develop automated clinical decision support systems and incorporate them in the VA clinical information system, thereby enhancing VA's ability to use rapidly expanding medical knowledge to improve the quality of care for veterans.
None at this time.
Decision support, Implementation