datatocare_cdcpresentation_final
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© 2014 Denver Public Health
Localizing HIV: the Data to Care Tool2014 National HIV Surveillance Grantees’ Meeting
Dec. 5, 2014
Lauren Snyder, MPH
Applied Public Health Informatics Fellowship Program
Denver Public Health
Mark Thrun, MD
Associate Professor, University of Colorado
Division of Infectious Diseases
Director, HIV/STD Prevention and Control
Denver Public Health
Director, Denver Prevention Training Center
© 2014 Denver Public Health
Opportunity and Need
• Mandatory reporting of HIV labs – CD4/VL – and increasing adoption of EHRs means more robust data available to help monitor epidemic
• Democratized data puts tools in hands of those most in need of it, but a user interface needed
• Real-time, local data more useful for both program planning and intervening at patient level
© 2014 Denver Public Health
Development Process - Phased Planning
HIV 1• Requirements document
• What do we want and how does it back translate with data being collected
HIV 2• Merging of primary data into one warehouse
• Common variable names, etc
HIV 3 • Visualization process
• Translating the data for web consumption
HIV4 • Redefining requirements and modifying visualized output
© 2014 Denver Public Health
eHARS
CD4/VL
DH Labs
Eval WebStaging
Data Warehouse
Invision
Web page access points
Diagnoses
Linkage
Retention/Re-engagement
Other: CVLCare, etc
© 2014 Denver Public Health
eHARS
CD4/VL
DH Labs
Eval WebStaging
Data Warehouse
Invision
Web page access points
Diagnoses
Linkage
Retention/Re-engagement
Other: CVLCare, etcHIV 2
© 2014 Denver Public Health
eHARS
CD4/VL
DH Labs
Eval WebStaging
Data Warehouse
Invision
Web page access points
Diagnoses
Linkage
Retention/Re-engagement
Other: CVLCare, etcHIV 3
© 2014 Denver Public Health
Diagnosis HIV Summary – Denver County
Residence at Diagnosis, Denver,1/1/2012-12/31/2012
© 2014 Denver Public Health
Data to Care: Uses of the Tool
Program planning
• Improved understanding of the nuances of the local epidemic
• Improve communication regarding prevention needs
• Better allocation of staffing resources/needs– Within the HD
– In the community
• Greater efficiency in evaluation of program
Patient management
• Improved linkage assessment
• Real-time assessment of retention and reengagement efforts by subpopulations– Develop NIC lists
– Allow for outreach interventions
• Assess clinical outcomes : OI’s, STD screening, etc
© 2014 Denver Public Health
Team approach
• Prep team
– What are we talking about as an end result
– How does that back translate to current data
• Very specific – Date of certain test; Need to merge or limit variables, etc
• Build team
– IT experts creating code and software
• Test team/Data reconciliation
– Validate Build team’s output with known data
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