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 Ken Baker and John Wilkerson, VA Office of Information and Technology Stephen Chermack, PhD, Chief, Mental Health Clinic and Substance Use Disorders Clinic Stephen Chermack, PhD, Chief, Mental Health Clinic and Substance Use Disorders Clinic University of Michigan Dale Fitch, PhD, Asst. Prof, School of Social Work Dale Fitch, PhD, Asst. Prof, School of Social Work

3. Presentation overview Potential that VistA has for conducting research Potential that VistA has for conducting research Methods used to harvest and collect data using VistA Methods used to harvest and collect data using VistA Examples of studies that have used VistA Examples of studies that have used VistA Brainstorming / Discussion Brainstorming / Discussion

4. VistA’s research potential Utilizing data already in VistA Utilizing data already in VistA VistA as a data collection tool VistA as a data collection tool VistA as a research data storage tool VistA as a research data storage tool

5. Utilizing data already in VistA Demographics Demographics Age, gender, race, marital status, income, disability status, military status Age, gender, race, marital status, income, disability status, military status Predictors and/or outcome variables: Interventions Interventions Medications, specialty care, clinic appointments Medications, specialty care, clinic appointments Health factors Health factors Medical and psychiatric diagnoses, weight, glucose Medical and psychiatric diagnoses, weight, glucose Screening results Screening results Diabetes, depression, PTSD, alcohol Diabetes, depression, PTSD, alcohol Outcomes Outcomes Inpatient hospitalization, resource utilization, mental health outcome measures, Addiction Severity Index Inpatient hospitalization, resource utilization, mental health outcome measures, Addiction Severity Index

6. VistA as a data collection tool Clinical Reminders Clinical Reminders Use to identify research participants Use to identify research participants Reminders can trigger need for assessment Reminders can trigger need for assessment Reminder templates Reminder templates Avoids narrative data storage (typically bad for research) Avoids narrative data storage (typically bad for research) Implement short questionnaires Implement short questionnaires Data stored VistA, rather than Excel spreadsheet or MS Access Data stored VistA, rather than Excel spreadsheet or MS Access

7. continued: VistA as a data collection tool Mental Health Assistant Mental Health Assistant Self-assessment, clerk entry Self-assessment, clerk entry Stores data in VistA Stores data in VistA Version 3: Add your own measures! Version 3: Add your own measures!

8. VistA as a data storage tool Centralized storage: eliminate hundreds of spreadsheets floating around your clinic Centralized storage: eliminate hundreds of spreadsheets floating around your clinic Query one database for all the information you need 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 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. … But not many ways to get it out.

11. Harvesting Methods Mumps Data Extractor Mumps Data Extractor Cache Shadowing Cache Shadowing FileMan FileMan Others Others

12. Mumps Data Extractor Commercial: Strategic Reporting Systems Commercial: Strategic Reporting Systems Quick installation Quick installation Natively reads VistA files and dumps to SQL Natively reads VistA files and dumps to SQL Maps variables correctly Maps variables correctly Manages data types Manages data types Batch dumps may take a while, should schedule at night 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 Real-time mirroring of live VistA data Stored on a separate server Stored on a separate server Avoid taxing production server Avoid taxing production server Cache has SQL support Cache has SQL support Built-in ODBC access Built-in ODBC access

15. Others Fileman Fileman RPC RPC Mumps programming Mumps programming

16. Comparison: Extraction Utilities ProsCons Mumps Data Extractor SQL ready SQL ready Maps variable names automatically Maps variable names automatically Translates variables types, escape codes Translates variables types, escape codes Quick implementation Quick implementation Extra cost Extra cost Taxes production server Taxes production server Older data Older data Frequent IT intervention Frequent IT intervention Cache Shadowing Real-time data: Clinically useful Real-time data: Clinically useful SQL ready SQL ready Cost Included in Cache license Cost Included in Cache license Requires variable mapping and translation Requires variable mapping and translation Hard to implement Hard to implement Fileman Free Free Gets the job done Gets the job done No “dump to SQL” option No “dump to SQL” option Every query uses production resources Every query uses production resources Requires end user to learn a specialized language Requires end user to learn a specialized language Recommendation: Use Cache Shadowing

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 Implementations must meet user ability Cost, specialized knowledge Cost, specialized knowledge Disconnect between IT and clinicians/researchers Disconnect between IT and clinicians/researchers Communication barriers Communication barriers How can we improve VistA research? How can we improve VistA research?

20. Resources Finding the data you need Database/files list Database/files list http://openforum.worldvista.org/~forum/index.php?title=VistA_Database_Globals http://openforum.worldvista.org/~forum/index.php?title=VistA_Database_Globals Vista Documentation Library Vista Documentation Library http://www.va.gov/vdl/ http://www.va.gov/vdl/