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Ways of representing data:

  1. Stand alone value with units

  2. Relative to a reference value or range (above normal; low-normal-high)

  3. Z-score (incorporating mean and SD)

  4. Multiple of mean (MOM)

  5. Multiple of upper limit of normal (ULN)

Classification of Data Items

  1. (1) simple vs complex (structure)

  2. (2) constant vs variable/changing

  3. (3) predictable vs unpredictable

  4. (4) situational

 

Query: Does the person have a history of heart disease?

  • Simple response: Yes or No.

  • Complex data structure: date of occurrence, anatomic distribution, severity

 

Date of birth is constant.

Age is constantly changing at a rate of 1 per year.

Blood pressure changes but not in a constant manner.

 

Predictability: if a patient is normal, then the measure should be within a defined range.Fundamentals are basic, atomic patterns that solve very fine-grained problems, common across a variety of healthcare models. Fundamentals can be used independently, or combined into more complex patterns.

Data Items - Patterns on

EHR Data - Integration of

DMN Functionality

DMN Goals and Best Practices

BPMN Models and Methodology