As a part of the Space Health Innovation Challenge, Bill Hogan from Arkansas Biomedical Informatics led a lively discussion of the role of ontological systems in medical technology. If information technology is to improve diagnosis and treatment, the underlying ontologies behind the government mandated medical records systems must be accurate and robust enough to allow for both basic research and better clinical care. Currently, much medical data is driven not by care standards but by billing requirements. Such billing coding can better be described as a controlled vocabulary than a true ontology.
In information science, an ontology formally represents knowledge as a set of concepts within a domain, using a shared vocabulary to denote the types, properties and interrelationships of those concepts. Ontologies are the structural frameworks for organizing information for the purpose of enabling knowledge sharing and reuse. When working with complex data, well structured, hierarchical ontologies can be especially helpful. For example, a good drug classification system allows logical grouping of related drugs. If a pharmacist or doctor can be automatically informed that the patient shows an allergy to a sister drug as a prescription is entered, a less risky alternative can be selected.
What makes a good ontology? Dr. Hogan suggests that the periodic table of elements provides a simple example. Chemical elements are uniquely identified by number of protons and designated by a 2 character ID. Predictions of a substances chemical properties can be made based on it’s position in the table. Early researchers improved their searches for the missing elements flagged by a hole in the table, based on the predicted chemical properties. The history of the period table also is a lesson in the difficulty of selecting among competing ontologies. High profile individuals and influential intuitions can block the implementation of a more useful ontology by using their power and prestige to push their own competing system. John Dalton, the English chemist refused to use Dmitri Mendeleev’s system long after most chemists had concluded it was the most functional method.
A modern medical example is the Gene Ontology project, a bold attempt to make compiling research data more efficient by reducing the variations in usage that inhibit effective searching. The “project is a collaborative effort to address the need for consistent descriptions of gene products in different databases.” On the other hand, medical billing codes, although a controlled vocabulary, are not intended to facilitate research nor to improve clinical outcomes. In addition, some parts of the coding system are maintained as the IP of a particular billing software and so are not available to researches in an open source. If one is looking for a place to reduce medical costs while improving outcomes, mandating a better ontology for describing both diagnosis and treatment within a billing system is a good place to start.