Concept creation

Avoid Duplicates!  Avoid Duplicates!

When creating a new concept, use the "similar concepts" resources and/or search your dictionary carefully to be certain that there is not already a concept that meets your needs.

• Create synonyms (alternative, valid names) for your concepts.  This helps people find the concept and will help you avoid creating duplicates.

Concept Naming

• Only use alphanumeric characters (letters and numbers) and simple punctuation sparingly – e.g., comma (","), parentheses ("(" and ")"), and forward slash ("/").
  • Descriptions may contain non-alphanumeric characters
• Sentence-casing is recommended – i.e., either all lowercase or uppercase first letter.
  • Avoid using all uppercase
  • For drug names, some people use Tall Man Lettering to uppercase certain parts of drug names that are confused by providers, since this has been proven to reduce medication errors.
• Be consistent!
  • Consistency in naming helps users predict concept names and makes the dictionary much easier to manage.

Design for Re-use

Well-designed concepts can be used in several different contexts (e.g., multiple, different forms).

• Avoid making your symptoms & diagnoses concepts boolean; rather, use datatype N/A for these and use them as answers (not questions).  This promotes re-use of these concepts.
  • POOR DESIGN: a boolean "HIV" concept answered yes/no based on whether or not the patient has HIV.
  • GOOD DESIGN: a coded  "DIAGNOSES" or "PROBLEM ADDED" concept that is answered with the concept HIV (the HIV concept has datatype N/A).

Concept naming

• Always work with your end users to ensure the your concept names make sense to them and match their workflows.

Modeling diagnoses

Here are some notes/conversations related to concept modeling that may be helpful resources when confronting modeling issues.

Hamish wrote:

I would use DIAGNOSIS or PATIENT REPORTED DIAGNOSIS or similar generically and then record the diagnoses as answers (e.g. MALARIA) for most cases. That gives you the choice of recording the date of diagnosis into the obs date (probably simpler) or creating a DATE OF DIAGNOSIS observation to link dates to diagnoses through an obs_group_id.

If someone wants multiple choice answers for 1..n diagnois, then you are collecting two observations in each case: a multiple choice answer and the diagnosis for which the answer applies. There are a several ways to skin this.

Flat by diagnosis (add coded answers for each diagnosis)

PRO
simple, MALARIA/etc could still be used as answers

CON
not scalable, ties you to one model of answers to diagnoses and these must be replicated/managed for every diagnosis in the system.

Fully abstract (one concept for diagnsosis and a 2nd for answer to multiple choice question)

PRO
easily scalable

CON
needs tools/knowledge to convert back to one complex data point, diagnoses stored in a questionnaire-specific manner

Abstract, but use existing DIAGNOSIS concept

PRO
re-use of DIAGNOSIS, so you can still search DIAGNOSIS concept for all known diagnoses

CON
application must know to treat TRUE answers differently

Flat by answer (one concept per answer for questionnaire)

PRO
scalable, could re-use DIAGNOSIS concept or have a separate concept for diagnosis = true on questionnaire

CON
requires search for multiple concepts (could be facilitated by concept_set)

Additional information

• The MVP-CIEL concept dictionary is a valuable resource (either as a starting dictionary or to look for best practices)
• Notes or recording from the 2012-Sep-12 OpenMRS University forum, where concept management experts discussed best practices.