Overview of UCSF-CTSI Comparative Effectiveness Large Dataset Analysis Core, which offers resources for the analysis of large, public data sets on health and health care.

1. UCSF’s
Comparative Effectiveness
Large Dataset Analytic Core
Janet Coffman, PhD
Philip R. Lee Institute for Health Policy Studies
University of California, San Francisco
[insert date]

2. CELDAC
CELDAC is a partnership at UCSF among the
– Philip R Lee Institute for Health Policy Studies
– Academic Research Systems
– Department of Orthopedic Surgery
– Clinical and Translational Science Institute
Funding is from an administrative supplement to
the NCRR grant for UCSF’s Clinical &
Translational Science Institute.
Seeking funding from the California HealthCare
Foundation to sustain once NCRR grant ends.
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3. CELDAC Team
Faculty IHPS Staff
• Jim G. Kahn • Leon Traister
• Janet Coffman • Claire Will
• Claire Brindis
ARS Staff
• Steve Takemoto
• Rob Wynden
• Adams Dudley
• Ketty Mobed
• Kirsten Johansen
• Hari Rekapalli
• Prakash Lakshminarayanan
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4. CELDAC Mission
The mission of CELDAC is to enhance
UCSF's capacity for analysis of large local,
state, and national health datasets to
conduct comparative effectiveness
research and other types of health
services and health policy research.
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5. CELDAC Goals
• Accelerate access to and use of local, state, and national
health datasets, as a model for other CTSAs and health
research organizations.
• Enhance UCSF researchers’ ability to compete for
funding to use large data sets to conduct CER.
• Develop procedures and infrastructure by conducting
pilot studies.
• Support additional studies on the comparative
effectiveness of clinical interventions.
• Provide consultation to researchers currently working
with or interested in working with large data sets
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6. Find Large Datasets
http://ctsi.ucsf.edu/research/celdac
A guided search tool to find the best datasets for a project. Builds on previous
efforts by Andy Bindman, Nancy Adler, Claire Brindis, Charlie Irwin and others.
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7. Search Results –
Search for administrative data on infants’ use of health care services
http://ctsi.ucsf.edu/research/celdac
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8. Analyze Large Data Sets
• CELDAC has created a repository of select large,
public data sets that are available to UCSF
faculty at no cost.
• These data sets include
– HCUP National Emergency Department Sample
– HCUP National Inpatient Sample
– HCUP Kids Inpatient Databases
– HCUP State Emergency Department and Inpatient
Databases (select states)
– American Hospital Association Annual Survey
– Area Resource File
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9. Provide Consultation
• Study design/conceptualization
• Identification of relevant datasets
• Assistance with data set acquisition
• Cohort selection
• Data cleaning
• Linking data sets
• Strategies to deal with common methodological
issues in analysis of observational data
• Programming support for preliminary analyses
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10. Test New Methods for Working with
Large Data Sets
• Conventional methods for managing large data
sets have important limitations, especially for
studies that draw data from multiple data sets
– Requires programmers with expertise in managing
and querying large data sets
– Source data tables continue as individual entities
– Manipulations and linkages between tables require
awareness of each table’s architecture and
customized “One-Off” programming
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11. Test New Methods for Working with
Large Data Sets
• An Integrated Data Repository (IDR) with an
i2b2 infrastructure offers an alternative
– Supports integration of diverse sources of data
– Can translate diverse coding of the same content into
standard coding
– Flexibility in data exploration
– Intuitive drag-and-drop query interface
– Query result sets can be exported for analysis and
reporting using SAS, STATA, or other software
– Reliable - backed up every 2 hours
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12. Test New Methods for Working with
Large Data Sets
• Pilot Projects
– Integrated repository of data on spine surgery
procedures and outcomes from five data
sources
– Graphical user interface for browsing
California Office of Statewide Health Planning
and Development data on hospital discharges
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13. Questions for Discussion
• What services relating to large data set
analysis are likely to be most useful to you
and your mentees?
• What data sets are of greatest interest to
you and your mentees?
• How could CELDAC partner effectively
with researchers in your
school/department/division?
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14. Contact CELDAC
• Jim G. Kahn: JimG.Kahn@ucsf.edu
• Janet Coffman:
Janet.Coffman@ucsf.edu/415-476-2435
• Claire Will: Claire.Will@ucsf.edu/415-476-
6009
• http://ctsi.ucsf.edu/research/large-datasets
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