Standardizing Anatomy Nomenclature for Enterprise Imaging Globally
Despite the availability of mature data language and communication standards, a standard anatomy nomenclature applied across healthcare provider organizations and medical imaging specialties does not exist. For enterprise imaging and medical image exchange to be successful, a standard to categorize and classify image metadata is essential. In response to this need, the HIMSS-SIIM Enterprise Imaging Community established the Data Standards Evaluation Working Group, with the primary goal of analyzing existing standards for anatomy nomenclature to support multi-disciplinary relativity and semantic interoperability across internal and external systems. Over the past three years, the workgroup has conducted surveys and interviews with stakeholders from a variety of specialties to identify key clinical and system requirements. Using the results from the survey and interviews, the working group to developed an assessment criterion, including structured use cases that would be leveraged to collect and evaluate responses from ontologies providing an anatomy nomenclature. This session will review the actions involved in capturing requirements from key stakeholders, analyze the results of the anatomy nomenclature assessments to include key gaps noted, and discuss the workgroup's recommendations including key elements required to support adoption and implementation of a single, standard anatomy nomenclature across enterprise imaging globally.
- Describe the challenges resulting from provider organizations using varied anatomy nomenclatures and assess the benefits of global standardization
- Identify needed characteristics and criteria for an enterprise imaging anatomy nomenclature
- Compare three widely utilized anatomy nomenclatures and their respective Ontologies
- Summarize gaps in existing standard anatomy nomenclatures impacting viability for use in Enterprise Imaging
- Discuss steps needed towards adoption and implementation of a single anatomy nomenclature for enterprise medical imaging