Open Access Research article

A study of diverse clinical decision support rule authoring environments and requirements for integration

Li Zhou123*, Neelima Karipineni13, Janet Lewis1, Saverio M Maviglia123, Amanda Fairbanks1, Tonya Hongsermeier1, Blackford Middleton123 and Roberto A Rocha123

Author Affiliations

1 Clinical Informatics Research and Development, Partners HealthCare, 93 Worcester Street, 2nd floor, Wellesley, MA 02481, USA

2 Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, 1620 Tremont Street, Boston, MA 02120, USA

3 Harvard Medical School, 651 Huntington Avenue, Boston, MA 02115, USA

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BMC Medical Informatics and Decision Making 2012, 12:128  doi:10.1186/1472-6947-12-128

Published: 12 November 2012



Efficient rule authoring tools are critical to allow clinical Knowledge Engineers (KEs), Software Engineers (SEs), and Subject Matter Experts (SMEs) to convert medical knowledge into machine executable clinical decision support rules. The goal of this analysis was to identify the critical success factors and challenges of a fully functioning Rule Authoring Environment (RAE) in order to define requirements for a scalable, comprehensive tool to manage enterprise level rules.


The authors evaluated RAEs in active use across Partners Healthcare, including enterprise wide, ambulatory only, and system specific tools, with a focus on rule editors for reminder and medication rules. We conducted meetings with users of these RAEs to discuss their general experience and perceived advantages and limitations of these tools.


While the overall rule authoring process is similar across the 10 separate RAEs, the system capabilities and architecture vary widely. Most current RAEs limit the ability of the clinical decision support (CDS) interventions to be standardized, sharable, interoperable, and extensible. No existing system meets all requirements defined by knowledge management users.


A successful, scalable, integrated rule authoring environment will need to support a number of key requirements and functions in the areas of knowledge representation, metadata, terminology, authoring collaboration, user interface, integration with electronic health record (EHR) systems, testing, and reporting.

Clinical decision support; Knowledge management; Knowledge engineering; Knowledge authoring tool; Rule-based decision support; Knowledge lifecycle