1. Role of Semantic Web Technologies in Managing Knowledge Change and Provenance
Vipul Kashyap1, Alfredo Morales2 ;
1Clinical Informatics R&D, Partners Healthcare System
2 Cerebra, Inc.
HCLSIG Face to Face Meeting, Cambridge MA
January 25, 2006

2. Outline Some definitions The Business Problem: Example
Structured Clinical Documentation in HealthCare
Example
Semantics-based approach for Clinical Documentation
Dependency Propagation and Management
Conclusions

3. What does it mean to manage Knowledge Change and Provenance
There is a close interrelationship between knowledge change and provenance
What has changed? – Change
Why did it change? – Provenance
Did someone change it? – Provenance
Did its components change? – Change
Who changed it? – Provenance
Significance:
Rapid Knowledge Discovery and Evolution in Healthcare and Life Sciences

4. The Business Problem
Difficulty of identifying targeted templates for particular conditions and diseases
Inflexibility for documenting unforeseen findings
Lack of consistency and maintenance of documentation templates as clinical knowledge and content evolves over time.
Inefficiency, complexity and slow pace of navigating through user interfaces
leads to decreased overall efficiency for generating complex documents

5. Example:

6. Example Instrument
1. Do you know if there any contraindications to fibric acid for this patient?
__ Yes
__ No
2. Does this patient suffer from gallstones?
What is the AST Value for this patient?
______ mg/ml?
4. Which of the following range of values does the AST values for this patient apply to?
_ < 10
_ [10,20]
_ [20,40]
5. Are the liver panel values more than the normal values for this patient?
6. If the answer to Question 5 is Yes, then the liver panel values are:
__ 2 x Normal
__ 3 x Normal

7. Documentation Ontology
A Data Collection Item
consists of:
- A domain (Patient)
- A question
- An attribute (has_contraindication_to)
- A value
A Data Collection Item can
depend on the results of
other data collection items

8. Domain Ontology Suppose AST values change from
0  AST  40 to 20  AST  40

9. Bridge – Composition Ontology

10. Knowledge Change and Provenance
At each stage, Knowledge Engineer gets notified of:
What has changed?
The definition of Fibric Acid Contraindication
Why did it change?
Fibric Acid Contraindication  Patient with Abnormal Liver Panel  Abnormal Liver Panel  Abnormal AST  Change in AST Values
Who was responsible for the change?
Knowledge Engineer who entered the changed AST values?
Change in a Clinical Guideline?

11. The Value Proposition of Semantics
Managing change and provenance is a very difficult problem
Semantics can play a crucial role in it:
A reasoner can navigate a semantic model of knowledge and propagate change
One can declaratively change the model at any time…
The reasoner will compute the new changes!
Configuration v/s coding…. Could lead to huge ROI!