south africa data warehouse for pepfar

South Africa Data Warehouse for PEPFARPresented by:Michael OgawaKhulisa Management Servicesmogawa@khulisa.com011-447-6464

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