Apr 01

Terminology “as a Service”

standards (1 of 1)-2


In this era of the ‘’as a service’’ models we need to be looking for easier ways of implementing  standards needed to support eHealth tools like decision support and analytics. No longer should standards be something we see in passing. We need ways to implement and update them quickly and efficiently into mainstream eHealth technology products. Products like Intelligent Medical Objects (IMO) may be a way of providing assistance.



3 benefits a terminology service like IMO can provide for you

  • Provide a lexicon for problem management lists.
  • Provide maps to other classifications and codes invisibly to the user.
  • Provide regular updates.

3 issues with IMO you should be aware of:

  • If you are trying to implement SNOMED CT you may need a license for usage in your country. However many countries often have national memberships for all of their citizens to use SNOMED CT from IHTSDO. The same may apply to ICD maps from the World Health Organization.
  • It does not include drug codes which limits its value in decision support.
  • The mapping to SNOMED CT may not be an equivalence map for all codes ie the associated codes may be a more general code which groups a number of the terms in your problems list. This may not be a bad thing but it is definitely something you need to be aware of.

Once terminology and lexicon management tools are readily available, the challenge becomes how they will make a difference in eHealth products. One such advantage being intelligent problem lists where the eHealth products can provide weighted problem lists for better selection of the most common terms to improve the adoption and accuracy of terms selected by clinician.

For great things to happen in this area, multiple parties will need to come together and bring their expertise and tools. In April 2015 it was announced that IMO was collaborating with Nuance’s Dragon 360 and their Clinical Language Understanding (CLU) engine to analyzes the physician free text narrative and extract key patient information, such as patient problems and allergies in real time as discrete, structured data and view this in MEDITECH’s electronic health record. I look forward to seeing the results of this collaboration.


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