Working Effectively with Medicare Data: Limits and Opportunities
 

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Overview of UCSF's Comparative Effectiveness Large Dataset Analysis Core with emphasis on Medicare data.

Overview of UCSF's Comparative Effectiveness Large Dataset Analysis Core with emphasis on Medicare data.

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Working Effectively with Medicare Data: Limits and Opportunities Presentation Transcript

  • 1. UCSF’s Comparative EffectivenessLarge Dataset Analytic Core Janet Coffman, PhD Philip R. Lee Institute for Health Policy Studies University of California, San Francisco September 7, 2011
  • 2. Outline• Overview of CELDAC• New Medicare data resources• Discussion 2
  • 3. 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. 3
  • 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. 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. CELDAC Team – IHPS Members Faculty Staff • Jim G. Kahn • Claire Will • Janet Coffman • Leon Traister • Claire Brindis • Steve Takemoto • Adams Dudley • Kirsten Johansen 6
  • 7. 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. 7
  • 8. Analyze Large Data Sets• CELDAC has partnered with faculty in three departments to purchase national data sets and make them available to additional 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. 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. Medicare Data:New Resources 10
  • 11. Existing Medicare Data Resources• Research identifiable files – Enrollment – Claims – Med PAR• Limited data sets• Non-identifiable data sets• Medicare statistical supplement 11
  • 12. Limitations of Existing Medicare Data Resources• High costs limit number of researchers analyzing the data• Long delays in approving requests make it difficult for researchers to conduct analyses in a timely manner 12
  • 13. New Medicare Public Use Files• In June 2011, CMS released its first public use files (PUFs)• Files available to researchers as free downloads in CSV format (https://www.cms.gov/BSAPUFS/)• Derived from 5% samples de-identified claims from 2008 – Inpatient care – Outpatient procedures – Physician services – Prescription drugs – Skilled nursing care – Home health – Hospice – Durable medical equipment 13
  • 14. New Medicare Public Use Files• Strengths – Data can be downloaded free of charge at any time without prior approval – Useful for conducting preliminary analyses• Limitations – Limited number of variables – Data sets cannot be linked (i.e., cannot track beneficiaries across settings) – No information on geographic location 14
  • 15. Disclosure Treated Controlled Use Files• Attempt to strike a better balance between protecting privacy and analytic utility than public use files• Encompasses five files that can be linked to one another (beneficiary summary data, inpatient claims, outpatient claims, physician claims, prescription drug claims)• Files housed in a secure environment/data enclave to improve timeliness of access and review of analysis output• Uses sophisticated methods to simultaneously minimize both disclosure risk and information loss 15
  • 16. Disclosure Treated Controlled Use Files• CMS and the National Opinion Research Center will begin recruiting researchers to pilot test the secure environment/data enclave during the first quarter of 2012• Applicants will be selected and given access to the data during the second quarter of 2012 16
  • 17. Discussion 17
  • 18. 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 based at the SF VA? 18
  • 19. Contact CELDAC• Janet Coffman or Claire Will <celdac@ucsf.edu>• http://ctsi.ucsf.edu/research/large- datasets• 415-476-2435 19