This is my fourth blog post from the International Conference on Biomedical Ontology (ICBO) 2011, in Buffalo, NY. This time I will focus on disease vocabularies. In earlier blog posts I have highlighted the differences between two types of vocabularies:
- Vocabularies of terms for concepts organized as terminology hierarchies (e.g SNOMED CT), classification systems (e.g. ICD and MedDRA) being used as coding nomenclatures for diseases, or rather diagnoses, in EHR, clinical trials and patient safety databases.
- Vocabularies of terms for types of entities in reality, and of the relationships between such entities, structured in ontologies according to the best current scientific understanding of physiological and pathological processes.
In my previous blog post from ICBO I listed examples of high quality, "true", ontologies, and also different approaches to manage "Mapping mania" for the legacy of terminologies. See also another blog post that describes very well how terminologies, relates to ontologies, and also to information models etc.: Why Do We Need Ontologies in Healthcare Applications.
In this blog post I use a review of a common terminology, that is SNOMED CT, and the Mental Disease Ontology under development, as examples to highlight problems and potentials with these two types of vocabularies.
Terms for concepts organized as terminology hierarchies
While working on this blog post I saw a posting on Google+ (that is the new social media tool excellent for online discussions) pointing to a recent report from practical use of SNOMED CT in a commercial clinical system focused on cardiovascular and respiratory diseases, and diabetes mellitus. The Google+ posting came from Alan Ruttenberg, one of the key people in the biomedical ontology (OBO) community and organiser of the ICBO event. The main author of the paper Alan pointed to, Getting the foot out of the pelvis: modeling problems affecting use of SNOMED CT hierarchies in practical applications, is Alan Rector, one of the key people in the biomedical terminology community.
Systematized Nomenclature of Medicine–Clinical Terms (SNOMED CT) is now mandated in the USA, UK, and several other countries for coding of clinical problems in EHR. The SNOMED identifiers, codes such as 38341003 for the term 'hypertensive disorder', provide a stable reference point for coding of diagnoses. And it is one the key terminologies in the EHR4CR IMI-project, for example when querying EHR data for protocol feasibility.
"When doctors apply SNOMED codes to a patient, they are stating that those codes and all their ancestors in the hierarchy apply to that patient. When researchers use codes in queries, they are querying for those codes and all of their descendants."
Source: Getting the foot out of the pelvis: modeling problems
affecting use of SNOMED CT hierarchies in practical
applications, J Am Med Inform Assoc. 2011 July; 18(4): 432–440.
The article lists, and exemplifies, the major types of problems when using SNOMED-CT hierarchies. It also illustrates existing hierarchies, for example for hypertensive disorder (A) and a suggested revised hierarchy for Hypertension (B).
The authors’ conclusion is quite tough:
“… anyone using SNOMED codes should exercise caution. Errors in the hierarchies, or attempts to compensate for them, are likely to compromise interoperability and meaningful use.”Terms for types of entities in reality structured in ontologies
In preparations for the conference I studied one of the disease area ontologies under development: Mental Disease Ontology. I do not have any medical insights into this disease area, but became interested in it because it uses the Ontology of General Medical Science (OGMS).
|Source: Toward an Ontological Treatment of Disease and Diagnosis|
OGMS is a so called mid-level ontology. The objective for it is to support research on Electronic Health Record (EHR) technology and integration of clinical and research data. My interested in OGMS started at the Clinical Trial Ontology workshop at the NIH Campus in Bethesda, MD., in 2007. When the OBO community took the insights and best practice from developing large biology ontologies (such as the Gene Ontology and the Protein Ontology) the framework called OBO Foundry, into the clinical space a couple of things were often confused:
- The process of observing, the results of the observation and what is being observed
- Disorders and diseases on the one hand and diagnoses on the other
To address these, and other confusions, the development of OGMS started.
"OGMS comprises representations of highly general universals in the domains of anatomy, physiology and pathology, of diagnosis and treatment, and of information artifacts such as clinical histories and lab test results.”
From the paper: Research Foundations for a realist ontology of mental disease, authored by Barry Smith and Werner Ceusters, two of the key people in the biomedical ontology (OBO) community. In this paper the authors describe how the development of an ontology for mental disease addresses the need for acceptable definitions for 'mental disorder', 'disease' and 'illness' as it has been called out in the research agenda for the new edition (DSM-V) of the Diagnostic and Statistical Manual, scheduled for release in May 2013.
The authors defines three different list of types of entities according to the best current scientific understanding in the domain of mental diseases:
- Mental health related entities that can exist in the absence of any mental disorder, using terms to denote these entities such as behavior and interpersonal process
- Mental disorder related core entities, e.g. using terms to denote these entities such as pathological mental process and mental disease course
- Diagnosis related core entities using terms to denote these entities such as disease picture components and collection of marker features for disease X (e.g. Diagnostic Criteria for Asperger's Syndrome and for ADHD)
I find this statement of the authors highly interesting:
“We do not suggest that all the terms proposed in the above should be used by clinicians, although moves in this direction would help to make medical jargon less ambiguous (while at the same time potentially bringing other costs). What is more important is a broad recognition of the existence of the types of entities denoted by these terms, since without this broad recognition we will not achieve the sort of terminological clarity that is needed for computational purposes such as integration of mental health data with biological and other sorts of data. Finding better terms for the entities in question is, in this light, a secondary issue.”Some reflections
As outlined in one of my earlier blog post in preparation for ICBO I hoped to better understand the emerging trend of well design “true” ontologies. And at the same time understand how we better can use legacy terminologies, such as SNOMED CT, and data coded with their aid can be successfully used for information-driven clinical and translational research. By attending ICBO I have got a much better understanding of the problems and potentials of the two different types of vocabularies. However, I still struggle to understand how to combine them short and long term.