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]

CELDACCELDAC 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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CELDAC Team

Faculty

• Jim G. Kahn• Janet Coffman• Claire Brindis• Steve Takemoto• Adams Dudley• Kirsten Johansen

IHPS Staff

• Leon Traister• Claire Will

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ARS Staff• Rob Wynden• Ketty Mobed• Hari Rekapalli• Prakash Lakshminarayanan

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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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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Find Large Datasetshttp://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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Search Results –Search for administrative data on infants’ use of health care services

http://ctsi.ucsf.edu/research/celdac

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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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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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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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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

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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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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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-

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• http://ctsi.ucsf.edu/research/large-datasets

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