a72fc00dccb28d110957d235f957c496.ppt
- Количество слайдов: 8
Blue. Medics Evidence-based Patient Empowerment
Challenges PHR • Integration of clinical data CDA – Horizontal - Sources – Vertical – Data • Dynamic incorporation of public knowledge Clinical Genomics – Structure, unstructured and semi-structured Lab Results • Scalable enablement platform – Support analytical services – 3 rd-Party service providers • Intuitive portal – Patients are from Mars, Physician are from Venus • Leverage social networks for the benefits of physicians and patients Pharmacy Clinical Trials Imaging
About The Project • Joint project between IBM and Gil Hospital (Korea) • 5 years project, currently in 2 nd year • 3 IBM centers are involved: – IBM Korea – IBM Research in China – IBM Research in Israel • Building an open platform and services • Web-based rich portal • Testing the system with patients and physicians from the hospital • Support integration with external PHR (e. g. Google Health)
ADE Service • Provide alerts about potential ADE alerts – At the point of care – As a consultancy service (for patients or physicians) • Give an explanation about the alert – Summary of the potential ADE – Why did the system generated it – Reference to relevant paper/article/FDA alert • Suggest recommended dosage if available • Integration between patient data and relevant knowledge
Genetic ADE • Integration of genetic test results in the patient’s medical record – Integration with direct-to-consumer 3 rd-party services • Incorporate public knowledge bases (e. g. Pharm. KGB) • Express evidences in a PGx model • Execution environment to generate ADE notifications that are also considering the genetic profile
Social Medical Service • Everything is an entity • Relationships between entities: – Patient consumes medications – Physician prescribed medication – ADE interactions between drugs – Pharmacogenetics ADE Interaction – Many more… Patient Physician Patient
Social Medical - Example Use Cases • Social Medical Discovery – Unified search over entity-relationship graphs • Textual search • Faceted search – Facets examples: patient age, medication generic name, genetic variation – Support fast navigation by drilling down and up in the results – Fast results navigation and exploration • Similar Patients – Discover similar patients that share similar medical conditions – Create social communities of similar patients • Medical Recommendation • Both patients and physicians will find the above useful
Social Medical Discovery – UI Example Filter by: Search • Patient attributes Displaying entities 1 -10 out of 112 Ø Gender (100) Male (46) Ø Female (54) John Doe – 0122 -333 -444 Ø… Any important detail that needs to be displayed about patient, goes here. Such details come from patient’s attributes. Displayed data can be further summarized and matching keywords, entities can be highlighted. • Relationship type Ø Treated By (23) Dr. Dark Dr. Mark Dr. Li-Chang Dr. Morgan Dr. Chen-Li Dr. Rozenbaum Dr. Bang Dr. Robson 1 2 3 4… 12 13 next Results filtered by: facet 1 >> facet 2 >> facet 3 Ø Dr. Davis Advance search Dr. Swarch Dr. Weiss Dr. Cohen Dr. Rim Dr. Akmed Dr. Darry Donald Smith Dr. Mike Dr. Smark Klara Wood Medications (12) Allergies (1) Treating Physicians (3)
a72fc00dccb28d110957d235f957c496.ppt