bluemedics evidence-based patient empowerment. challenges integration of clinical data –horizontal...
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BlueMedics
Evidence-based Patient Empowerment
Challenges
• Integration of clinical data– Horizontal - Sources
– Vertical – Data
• Dynamic incorporation of public knowledge
– Structure, unstructured and semi-structured
• Scalable enablement platform
– Support analytical services
– 3rd-Party service providers
• Intuitive portal
– Patients are from Mars, Physician are from Venus
• Leverage social networks for the benefits of physicians and patients
PHR
CDA
Pharmacy
Clinical Trials
Imaging
Clinical Genomics
Lab Results
About The Project
• Joint project between IBM and Gil Hospital (Korea)
• 5 years project, currently in 2nd 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 3rd-party services
• Incorporate public knowledge bases (e.g. PharmKGB)
• 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
Patient
Patient
Patient
Patient
Patient
Physician
Physician
Physician
Physician
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
Search Filter by:
• Patient attributes
Gender (100)
Male (46)
Female (54)
…
Advance search
• Relationship type
Treated By (23)
John Doe – 0122-333-444
Results filtered by: facet1 >> facet2 >> facet3
Displaying entities 1-10 out of 112 1 2 3 4… 12 13 next
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.
Medications (12)
Allergies (1)
Treating Physicians (3)
Dr. Li-Chang
Dr. RozenbaumDr. Bang
Dr. Swarch
Dr. Cohen
Dr. Chen-LiDr. Davis
Dr. Robson Dr. Rim
Dr. Morgan
Dr. Akmed
Dr. Darry
Dr. Mike
Dr. Dark Dr. Mark
Dr. WeissDr. Smark
Donald Smith
Klara Wood