Iso tc tc 215/sc n339 Date: August 2003 iso/pdts

10.3.4.3 Community and health system characteristics dimension: Class “resources” Table 30 – Community and health system characteristics dimension: Class “resources”

Attribute	Definition
Concept	An attribute of type long that is a unique identifier, which
	represents each health indicator
Type	Type of resource, For example “MRI scanners” or more
	general needs such as “Electric Power”
Level of funding	The total level of funding for this resource within a given
	population
Source of funding	Government, private, corporate, etc.
Level of expenditure of physician training	The average level of expenditure in this population for physician training
Level of expenditure on research	The total level of expenditure for research within a given community
Number of units used	The number of units utilised for any specific resource instantiation
Cost per unit	The unit cost for any one specific resource instantiation

Annex A

(Informative)

A conceptual framework for linking national health information model and indicator framework structures

This illustrates the connections that apply both horizontally (eg between models and indicators frameworks; between data elements and indicators that are data elements commonly are often derived from existing data elements) and vertically (eg between models and data elements, and between indicator frameworks and indicators). The diagram also recognises the role of data sets that provide information about some specific or topic. Note that ISO 11179-3 can be adapted to the documentation of data elements, indicators, and data sets such as national minimum data sets and indicators sets

Annex B

(Informative)

Reference Terminologies

Introduction

Vocabulary construction and organization is seen as an essential part of a functional Electronic Health Record¹. Concept level understanding of our day-to-day clinical practice will enable more accurate and more available outcomes research, evidence based medicine, and effective cost management of medicine without a decline in service. This promise is hampered by the lack of a robust clinically relevant large-scale vocabulary, with a structure that supports synonymy, multiple ontologies, semantic relationships, and compositionality. As we move toward a greater understanding of the relationships between terms, workers are striving to determine the optimal level of granularity for the terms in these vocabularies. One solution would be to separate the truly atomic terms and their ontologies from the compositions. This multiaxial schema for vocabulary design is clearly controversial. An example of this type of construction would be “Coronary Artery Disease (CAD) Status Post CABG” in which we have multiple atomic concepts. On first cut, the Coronary Artery Disease can be separated from the s/p CABG. This is only possible, if there exists a mechanism for reconstruction. This is clinically very important because the patient with “CAD s/p CABG” is clearly a different presentation than a patient with “CAD” without a history of prior cardiac surgery. More controversial is the corollary, that the construction of “Coronary Artery” and “Atherosclerotic Vascular Disease”, should be an equivalent concept to “CAD”

Although we may wish to say many things about “CAD” as a unit, there are still more granular ways to represent the same concepts. This similarity can be seen in many other constructions, for example the combination of “Large Bowel” and “Neoplasm, malignant” is equivalent to “Colon Cancer”. This is particularly important for billing systems where the code for “colon cancer” must not have a different ICD9-CM code than the composition of the term “neoplasm, malignant” modified by the site “large bowel”. One challenge in the development of a canonical vocabulary is to eliminate redundancy. Composition, while powerful, is also a source of considerable redundancy.

If composition causes such angst, why do it? Why not ignore this functionality? The answer was further reinforced by the results of a recent usability trial conducted at the Mayo Clinic². Users demand the ability to form problem statements that represent the concepts of their practice. We do not and cannot anticipate everything a clinician might wish to say about a patient. Thus without fully functional natural language processing, we require other tools and resources to make the most out of currently available controlled medical vocabularies. One solution is compositionality. All of these complex and varied statements that clinicians make regarding their patients are derived from a manageable number of atomic concepts (estimated to fall somewhere between (20,000 and 1,000,000) ^3,4,5.

Terminology structures

Terminology structures determine the ease with which practical and useful interfaces, for term navigation, entry, or retrieval can be supported (ISO 704, ISO 1087-1, ENV 12264).

Compositional terminologies

Large-scale controlled health vocabularies are becoming commercially available. One of the barriers to implementation of these systems is the perception that they will change the way clinicians must represent data. Clinicians fear that the individual flavour of their institution may be compromised by this mandate. In order to move toward standard representation of our patient’s conditions, we will need to provide a mechanism for mapping local parlance into large-scale concept based controlled health vocabularies.

Although these colloquial local terminologies are appropriate for integration into a controlled representation for a particular organization they may not be appropriate to disseminate to all users of the terminological system. For example, at our institution it is common to list the name of the surgeon who performed the CABG along with the fact that the patient had heart surgery. (This helps clinicians to know the technique used and the accessibility of records such as an Operation Note). Nevertheless, this activity of local colloquial terminology integration will likely be important for most, if not all, efforts to disseminate large-scale controlled health vocabularies.

For a vocabulary to be useful it must evolve and its content must grow. The UMLS contains over 750,000 concepts but still does not cover all clinically useful terminology. Local additions of colloquial terminology fall into one of two categories. One area of needed evolutionary capacity is specialty specific terminology. The other is colloquial additions of a general nature. For example, at Mayo it is common to refer to uncomplicated “low back pain” as “mechanical low back pain.” General and specialty specific local terminologies will likely continue to be used and, indeed, add richness to medical vocabularies.

As Cimino states, “…a formal methodology is needed for expanding content.” ¹ However, if one adds terms to a vocabulary indiscriminately, one risks redundancy and combinatorial explosion making the vocabulary unwieldy and difficult to search in a timely fashion. “An alternative approach is to enumerate all the atoms of a terminology

1, 3, 4

and allow users to combine them into necessary coded terms, allowing compositional extensibili One risk of this approach is that it has the potential of making the use of the vocabulary more complex.

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