Role of Semantic Web Technologies in Managing Knowledge Change and Provenance

1. Role of Semantic Web Technologies in Managing Knowledge Change and Provenance Vipul Kashyap1, Alfredo Morales2 vkashyap1@partners.org; alfredo.morales@cerebra.com 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: • 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 fromgallstones? • __ Yes • __ No • 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? • __ Yes • __ No • 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!