Enhancing Our Capacity for Large Health Dataset Analysis

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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.

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Enhancing Our Capacity for Large Health Dataset Analysis

  1. 1. UCSF’s Comparative EffectivenessLarge Dataset Analytic Core Janet Coffman, PhD Philip R. Lee Institute for Health Policy Studies University of California, San Francisco [insert date]
  2. 2. 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 InstituteFunding is from an administrative supplement tothe NCRR grant for UCSF’s Clinical &Translational Science Institute.Seeking funding from the California HealthCareFoundation to sustain once NCRR grant ends. 2
  3. 3. CELDAC TeamFaculty 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 3
  4. 4. CELDAC MissionThe mission of CELDAC is to enhanceUCSFs capacity for analysis of large local,state, and national health datasets toconduct comparative effectivenessresearch and other types of healthservices and health policy research. 4
  5. 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 5
  6. 6. Find Large Datasets http://ctsi.ucsf.edu/research/celdacA guided search tool to find the best datasets for a project. Builds on previousefforts by Andy Bindman, Nancy Adler, Claire Brindis, Charlie Irwin and others. 6
  7. 7. Search Results –Search for administrative data on infants’ use of health care services http://ctsi.ucsf.edu/research/celdac 7
  8. 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 8
  9. 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 9
  10. 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 10
  11. 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 11
  12. 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 12
  13. 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? 13 13
  14. 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 14

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