Data Needs of Health Care and Life Sciences

1. Data Needs of Health Care and Life Sciences Chimezie Ogbuji

2. The HCLS data crisis • U.S. Clinical research productivity is facing a crisis • Healthcare delivery is under-informed • Recruitment of clinicians and patients is low • Today’s ad hoc medical informatics methods are inadequate for current demands for drugs, personalized medicine, and diagnostic tools • A fundamental restructuring is required and will impact basic research institutions, pharmaceutical companies, and care delivery organizations. _____________________________ PricewaterhouseCoopers’ Health Research Institute 2008

3. SW vision for HCLS • Reconstitution of biological research knowledge ecosystem • Retooling the flow from clinical trial to the provision of care • Demand high fidelity, proactive medical records and information-based medicine

4. HCLS domain topology

5. Information-based medicine • Online access of a patients complete Computer-based Patient Record (CPR) • Personalized prescription of medication and treatment • Non-redundant, structured data entry collection

6. A working example • Patient / medical records are a key component of the ecosystem • Focus on the use of Semantic Web representation for patient record content • Demonstrate the ability to meet the requirements for information-based medicine

7. Representing CABG • Coronary Artery Bypass Grafting • Represent a medical record of a patient who is a candidate for CABG • Re-use existing medical ontologies • Demonstrate useful entailments, identification of trial candidates

8. Candidate ontologies • Basic Formal Ontology (OWL) • CPR ontology (OWL) • GALEN ontology (OWL) • Foundational Model of Anatomy (OWL)

9. Key concepts • Anatomy • Pathological body structures • Procedure methods • Pre-operative risk factors for CABG • Patient demographics • Disease findings • Disease finding severity

10. Anatomy • CABG is a procedure that acts on a stricture located in a coronary artery • Graft method involves reusing anatomical parts as conduits for blood flow around the constriction

11. Anatomy (continued) • Formal anatomy definitions burrowed from FMA • Concept of a coronary stricture burrowed from GALEN

12. Procedure methods • GALEN has a rich framework for surgical procedures we can re-use • Model grafting as an operation involving a specific method (SNOMED-CT also classifies procedures in this manner)

13. Grafting in an ontology

14. Adding CABG class

15. Modeling “co-morbidities” • The simultaneous presence of 2+ morbid conditions or diseases in the same [patient], which may complicate a [patient’s] hospital stay _____________________________ McGraw-Hill Concise Dictionary of Modern Medicine • Morbid conditions -> clinical findings • Presence of a disease -> clinical diagnosis

16. Modeling morbidities

17. How can this be used? • In a CPR system where the records are RDF graphs that conform to this ontology …. • You can incorporate patient-specific genetic markers to personalize the (already) rich overview • You can have medical terms that resolve to informative literature • You can incorporate additional risk factors

18. How can this be used? • You can present entailments to a clinician to facilitate their clinical problem solving process • You can identify candidates for CABG research by (SPARQL) querying for risk factors against all patients • You can extend the domain easily and in a controlled way • You can “apply” general guidelines against a specific patient context