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

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

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

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

Example:

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

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

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

Bridge – Composition Ontology

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?

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!