Scalable Methodologies for Distributed Development of Logic-Based Convergent Medical Terminology

Abstract

As the size and complexity of medical terminologies increase, terminology modelers are increasingly hampered by lack of tools and methods to manage the development process. This paper presents our use and ongoing evaluation of a description-logic classifier to support cognitive scalability of the underlying terminology and our enhancements to that classifier to support concurrent development utilizing semantics-based concurrency control methods. Our enhancements, collectively referred to as the Galapagos, consist of several applications that take locally-developed terminology enhancements from multiple sites, identify conflicting design decisions, support the modelers' reconciliation of the conflicting designs, and efficiently disseminate updates tailored for locally enhanced terminologies. We have tested our ideas through concurrent evolutionary enhancement of SNOMED International at three Kaiser Permanente regions and the Mayo Clinic. We have found that the underlying environment has met our design objectives, and supports semantic-based concurrency control, and identification and resolution of conflicting design decisions.