2019  Clinical Data and Beyond…
 

Wednesday, November 6th
Mission Bay Conference Center

Fisher Banquet Hall,1675 Owens St. San Francisco

Final Agenda

8:30 - 9:00  LIGHT BREAKFAST

9:00 - 9:10 Opening Remarks
Talmadge King, MD, Dean, School of Medicine

9:10 - 9:30  Medical Research - on the Move with AI
Atul Butte, MD, PhD,Director, Bakar Computational Health Sciences Institute (BCHSI)

9:30 - 9:45 Medicine in the Age of AI and the Need for New Collaborations
Robert Wachter, MD, Chair, Department of Medicine

9:45 - 10:00  Population Health and Health Equity
Kirsten Bibbins-Domingo, PhD, MD, MAS, Vice Dean Population Health & Health Equity

10:00 - 10:30 Digital and Informatics Platform for Research
Rick Larsen, Director, IT, Academic Research Systems
Eugenia Rutenberg, Sr. Director of Research Computing, BCHSI
Angela Rizk-Jackson, PhD, Director of Operations, BCHSI

10:30 - 10:45 BREAK

10:45 - 11:00 Fracture Studies Using Clinical Notes and Images
Valentina Pedoia PhD, Assistant Professor, Radiology

11:00 - 11:15 We3health: A UCSF led, family partnered digital health innovation
Linda Franck, RN, PhD, Professor, Family Health Care Nursing
Yao Sun, MD, PhD, Professor, Pediatrics

11:15 - 11:30 Leveraging Clinical Data for Population Health and Place-based Research
Courtney Lyles, PhD, Associate Professor, Medicine

11:30 - 11:45 Priorities and Perspectives from the Vice Chancellor of Research
Lindsey Criswell, MD, MPH, Vice Chancellor of Research

11:45 - 12:45 LUNCH
Meet and Greet the Staff who provide support to the UCSF Research enterprise 

AFTERNOON: 12:45 - 3:30 PM The afternoon is comprised of 2 tracks, where we will host a deeper dive into the topics below.

Time

Track 1
Focused on Clinical Research
Track 2
Focused on Data Science
12:45-1:45

Integrating research-based clinical decision support into APeX: how and what to expect
Learning Objectives: This talk with cover:

  • APeX-Enabled Research
  • Randomized quality improvement trials and embedded RCTs
  • How to start designing your own APeX-embedded RCT
  • 4 randomized controlled studies embedded into APeX, and what was needed to implement these studies

Natural Language Processing and Working with Clinical Text
Learning Objectives:

  • Approaches to extract information from clinical test
  • Specific examples that incorporate Machine Learning, Protected Health Information and standardized medical concepts (UMLS)
  • Data Sampling and annotation
  • NLP community engagement
1:45 - 2:15

Introducing the UCSF De-Identified Clinical Data Warehouse (De-ID CDW)
Learning Objectives: Learn the scope, clinical content and research use cases of the UCSF De-ID CDW

Imaging: Tools and how tos
Learning Objectives: 

  • Overview of currently available resources for conducting computational health research with radiological imaging data
  • The near-term roadmap and example use cases
2:15 - 2:30 Break Break
2:30 - 3:00

Realities of using EMR data for Research
Learning Objectives: This talk will cover the complexity of using EMR data for research

  • How best to approach UCSF's De-Identified self-service data assets and
  • The process of requesting and costs related to UCSF's Identified Data Assets. 

Building BRIDGE: A Clinical Precision Medicine Platform
Learning Objectives: 

  • Overview of BRIDGE, a Smart-on-FHIR clinical application
  • Data integrations and architecture
  • Methodology for data processing and visualization
3:00 - 3:30

4 New Tools in Action!
Learning Objectives: See demo of 4 tools including:

  • querying and visualizing genetic alterations that occur in different types of cancer using cBioPortal
  • visualizing a REDCap research data set using Tableau
  • how to use the PatientExplorR tool to define study cohorts
  • new way to query de-identified clinical notes using EMERSE

SPOKE Knowledge Network
Learning Objectives: 

  • Introduce knowledge networks
  • Understand the utility of big data integration for biomedicine
  • Introduction of SPOKE to the UCSF Community