Vista For Research

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  • 1. Using VistA for Research Joseph Glass, MSW VA Ann Arbor Healthcare System Ann Arbor, MI The contents of this presentation are mine personally and do not reflect any position of the Government or the Department of Veterans Affairs .
  • 2. Acknowledgements
    • VA Ann Arbor Healthcare System
    • Ken Baker and John Wilkerson, VA Office of Information and Technology
    • Stephen Chermack, PhD, Chief, Mental Health Clinic and Substance Use Disorders Clinic
    • University of Michigan
    • Dale Fitch, PhD, Asst. Prof, School of Social Work
  • 3. Presentation overview
    • Potential that VistA has for conducting research
    • Methods used to harvest and collect data using VistA
    • Examples of studies that have used VistA
    • Brainstorming / Discussion
  • 4. VistA’s research potential
    • Utilizing data already in VistA
    • VistA as a data collection tool
    • VistA as a research data storage tool
  • 5. Utilizing data already in VistA
    • Demographics
      • Age, gender, race, marital status, income, disability status, military status
    • Predictors and/or outcome variables:
    • Interventions
      • Medications, specialty care, clinic appointments
    • Health factors
      • Medical and psychiatric diagnoses, weight, glucose
    • Screening results
      • Diabetes, depression, PTSD, alcohol
    • Outcomes
      • Inpatient hospitalization, resource utilization, mental health outcome measures, Addiction Severity Index
  • 6. VistA as a data collection tool
    • Clinical Reminders
      • Use to identify research participants
      • Reminders can trigger need for assessment
    • Reminder templates
      • Avoids narrative data storage (typically bad for research)
      • Implement short questionnaires
      • Data stored VistA, rather than Excel spreadsheet or MS Access
  • 7. continued: VistA as a data collection tool
    • Mental Health Assistant
      • Self-assessment, clerk entry
      • Stores data in VistA
      • Version 3: Add your own measures!
  • 8. VistA as a data storage tool
    • Centralized storage: eliminate hundreds of spreadsheets floating around your clinic
    • Query one database for all the information you need
  • 9. Summary: VistA’s potential for research
    • Reuse, collect, and store data in one integrated system
  • 10. Harvesting VistA data
    • Myth:
    • There is a lot of data put into VistA …
    • … But not many ways to get it out.
  • 11. Harvesting Methods
    • Mumps Data Extractor
    • Cache Shadowing
    • FileMan
    • Others
  • 12. Mumps Data Extractor
    • Commercial: Strategic Reporting Systems
    • Quick installation
    • Natively reads VistA files and dumps to SQL
    • Maps variables correctly
    • Manages data types
    • Batch dumps may take a while, should schedule at night
  • 13. http://mde.srs-inc.com/solution.html
  • 14. Cache Shadowing
    • Real-time mirroring of live VistA data
    • Stored on a separate server
      • Avoid taxing production server
    • Cache has SQL support
    • Built-in ODBC access
  • 15. Others
    • Fileman
    • RPC
    • Mumps programming
  • 16. Comparison: Extraction Utilities Recommendation: Use Cache Shadowing
    • No “dump to SQL” option
    • Every query uses production resources
    • Requires end user to learn a specialized language
    • Free
    • Gets the job done
    Fileman
    • Requires variable mapping and translation
    • Hard to implement
    • Real-time data: Clinically useful
    • SQL ready
    • Cost Included in Cache license
    Cache Shadowing
    • Extra cost
    • Taxes production server
    • Older data
    • Frequent IT intervention
    • SQL ready
    • Maps variable names automatically
    • Translates variables types, escape codes
    • Quick implementation
    Mumps Data Extractor Cons Pros
  • 17. Extracting data: Case Study VA Ann Arbor VistA MS SQL Server Mumps Data Extractor (Every 2 weeks) Researcher with SPSS ODBC
  • 18. Future Direction: VA Ann Arbor VistA Cache Shadow Server Researcher with SPSS ODBC Cache Server Pages Email alert to clinician regarding a significant clinical event
  • 19. Potential discussion items
    • Implementations must meet user ability
      • Cost, specialized knowledge
    • Disconnect between IT and clinicians/researchers
      • Communication barriers
    • How can we improve VistA research?
  • 20. Resources
    • Finding the data you need
    • Database/files list
      • http://openforum.worldvista.org/~forum/index.php?title=VistA_Database_Globals
    • Vista Documentation Library
      • http://www.va.gov/vdl/