School of Health Systems and Public Health Monitoring & Evaluation of HIV and AIDS Programs INDICATORS Wednesday March 2, 2011 Win Brown USAID/South Africa Slide 1 of 25

Objective: Introduce the 4 stages in the data handling (information management) process & explain indicators. Slide 2 of 25

Learning Outcomes: Explain the concepts of data and information Analyze the data handling process Evidence-based decision making Select indicators & critique indicators Slide 3 of 25

What’s Our Raw Material? Data: Information: Knowledge: Data Information Knowledge Slide 4 of 25

Types of Data Quantitative: Qualitative: Routine: Non-Routine: Slide 5 of 25

Routine Data Collection Patient or Client Data: Let’s talk about the lowest level . . . “Data Capture” Who How When Where How are these data aggregated? Slide 6 of 25

Routine Health Information Management? Monitoring & Evaluation of Routine vs. Non-Routine Information . . . Which is more useful? Why? Slide 7 of 25

Information Management Process Slide 8 of 25

Current Problems and the Way Forward The Deadly Sin of Creating Parallel Structures in Reporting Systems The “H” Word . . . Alignment with Government Systems Slide 9 of 25

Ready for Indicators? Slide 10 of 25

What’s an Indicator? A quantitative or qualitative variable (something that changes) that provides a simple and reliable measurement of one aspect of performance, achievement or change in a program or project. Slide 11 of 25

Why Indicators? Directing resources to areas where needs are greatest Reducing large amount of data down to its simplest form Measuring program or project towards targets and desired outcomes Measuring trends over time Providing a yardstick whereby organizations, facilities etc. can compare themselves to others doing similar work Providing evidence for achievement (or lack of) of results and activities Slide 12 of 25

Slide # 13: The Evil Eye Don’t say anything! Slide 13 of 25

Indicator Structure Numerator Denominator Both . . . Numerators are the things we count: number of clients, infants immunised, new cases of TB, number of doctors. Activities/interventions/events a count of the event being measured How many occurrences are there: morbidity (health problem, disease) mortality (death) resources (manpower, money, materials) Generally raw data (numbers) Denominators are the group with which the thins we count are compared: total population, all births in a year, number of adults or clinics, total miles travelled, number of beds in the hospital What group do they belong to: general population (catchments / at risk) gender population (male / female) age group population (<1, >18, 15-44) cases / events – per (still births, children weighed) Slide 14 of 25

Example 1 ? ________________ Percent of Individuals Initiating ART with a CD4 Count of Less than 50. ? ________________ Slide 15 of 25

Example 2 ? ________________ ? Total Number of OVC Reached During the Reporting Period. ? ________________ ? Slide 16 of 25

Example 3 ? ________________ ? Total Number of Individuals Provided with Cotrimoxazole during the Reporting Period. ? ________________ ? Slide 17 of 25

Example 4 ? ________________ ? Total Number of Family Members Reached with HIV-Related Palliative Care during the Reporting Period. ? ________________ ? Slide 18 of 25

Example 5 ? ________________ ? Total Number of Individuals Counseled and Tested as a Couple. ? ________________ ? Slide 19 of 25

Don’t Let Indicators . . . Drive the Programme! Slide 20 of 25

SMART Indicators Specific Measurable Achievable Relevant Time-bound Slide 21 of 25

OPUDATA Objective Practical Useful for management Direct Attributable to your project’s efforts Timely Adequate Slide 22 of 25

How Does An Indicator Get Selected? Good Luck! Slide 23 of 25

Why Aren’t Managers Using Data? 1. 2. 3. 4. 5. Slide 24 of 25

To Be Useful, Data Should Be… 1. 2. 3. 4. 5. Slide 25 of 25