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South Africa Data Warehouse for PEPFAR Presented by: Michael Ogawa Khulisa Management Services...
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Transcript of South Africa Data Warehouse for PEPFAR Presented by: Michael Ogawa Khulisa Management Services...
South Africa Data Warehouse for PEPFARPresented by:Michael OgawaKhulisa Management [email protected]
Context PEPFAR South Africa
USG-funded Over 100 implementing
partners, many with multiple sites
Need to monitor up to 80 indicators twice a year
2008 Targets for SA Prevent 1.75m HIV
infections Treat 500,000 AIDS
patients Care for 2.5m OVCs &
HIV infected individuals
Monitoring and Evaluation
M&E provides strategic information to USG and implementing partners to:Plan and monitor programs; Document and report on progress; andEnsure that resources are used effectively
and efficiently
Challenges
SA PEPFAR program has a large number of partners who need to report and plan Reporting burden on USG
MS Word and MS Excel templates were historically used for capturing reports and annual plans
Office of The US Global AIDS Coordinator (OGAC) regularly makes changes to the PEPFAR indicator model
Access to the Internet varies among partners
SHARING Website
Secure web portal for accessing: Web-based forms for
reporting and planning templates
Indicator definition guides Data extracts (CSV files) Adjustment tool to
eliminate double counts User administration Budget/target grids
Solutions
Web-based data warehouse designed using Open Source software Only Internet browser software required Data warehouse can be accessed from anywhere in the world
(some partners have parent organizations outside of SA) Forms are database generated
RTF downloads (paper forms) HTML interface (web forms)
“Live” extracts for reporting indicators Reduced reporting burden for USG
Content Management System Indicator definitions Track changes for planning
Solutions
Speeding up web page loading Web page data are compressed before upload Data for a web page is separated so that formatting
information is not repeated One file contains formatting information Second file contains data that needs to be formatted
Asynchronous saving of data Users can carry on capturing data while the save for a
previous page is being processed Users do not have to wait for new form pages to load
Data Warehouse Approach
On Line Analytical Processing (OLAP) Measures
Numeric facts (e.g. No. of condoms distributed) Dimensions
Categories under which measures can be grouped (e.g. Gender, age, etc.)
OLAP Cubes OLAP cubes allow users to quickly retrieve queries and reports on
summary data for the organization The summary information being retrieved typically aggregates
detailed transactions at a lower level The aggregated totals stored in the OLAP cube can represent
thousands of rows of transactions within the data source from which it originates
Data Quality Improvements
Input data is checked on client side (cannot enter non-numeric data into a numeric field)
Full transactional audit history Data must be verified before it is submitted Forms locked after submission Forms can be invalidated for changes by partners Double count adjustment tool adjusts aggregate total but
does not adjust partner data System designed to capture down to site level (source
data) and at monthly periods
Future Features: Pivot Table/Cube Viewer
Future Features: Online Mapping
Future Features
Electronic transfer of data From partner systems to data warehouse From data warehouse to USG system in Washington
and SA health information systems
Offline data capture Customizable indicators/dimensions for partners Workflow
Lessons Learned
If time is available, understand your user base Web capturing interface = paper form
Data warehouse needs to move beyond its current role as a one-way conduit for USG results reporting Need to improve data utilization tools for complex, analyses and
basic, menu-driven reports, graphs and maps Need more features (RSS feeds, warehouse more health
data sources, etc.) to bring users to the website on a regular basis
Questions and Answers