1. VACS Data Build Process of Cleaning and versioning of data sources
Creating faster and efficient data access for analysis
Provide a single, secure and centralized location for all data sources.

2. Administrative (Austin) data (1997-2006)
Survey (full study baseline,) no follow-ups yet right? FU1,2,3)
PBM (October 1998 – July 2005)
ICR (fiscal year , HIV +)
Pharmacy, Labs, Diagnoses
Enrollment (demographics, consent)
VISTA EMR direct from sites

3. VACS Data Build 1 Goals: Accurate clean data Centralized Documented
Correct enrolled full study – documented consent and completed baseline survey
Data integrity – to prevent duplication and redundancy
Centralized
Documented
Secure

4. VACS Data Build Status Data in SQLServer Data in SAS, STATA, Text
Master “Enrolled”
Baseline surveys, cause of death, TLFB
Admin Data – ICR, Austin, PBM
Vista – labs (06)
Data in SAS, STATA, Text
VACS3,5 surveys, TLFB
SAS cleaning code
VISTA other - such as clean site labs
Documentation – Metadata for survey questions, choices, lab codes, med. Codes (ARV), diagnostic codes

5. What does this mean?
Faster turn-around of data requests will be possible
- Main coordinating staff will have access to data (not just MS)
- Data will be linkable for ease of combining various data sources
Easy tracking of methods for papers, abstracts and presentations

6. What does this mean?
BUT—data is ‘clean’ at the row/record level not subject
Programming still required to create data sets for requests such as:
- selecting specific labs, pharmacy data for subjects within +- of enrollment dates
- comorbidities (ICDs) at different times – Baseline, FU’s

7. Subsequent Builds Data – normalized and cleaned
Surveys FU1, FU2, FU3
Other such as Vista/EMR site data
Automated load/extract processes
Security enhancements
Stored objects for queries and statistical analysis
Web interfaces for data analysis and requests using metadata
Documentation on data sources such as Austin, PBM

8. Credits
The VACS team for their functional and technical input.