1. Uses for Data

2. Part of the M&E Plan M&E Plan Data Use and Reporting Framework
Indicators
Data Collection
Data Quality
Data Use and Reporting
Evaluation Strategy
Budget
Data use and reporting are other key parts of our M&E plan where we show how we will use our data. It takes a lot of effort and resources to collect data, so we should have a plan for how we will reap the benefit of all that hard work. Along with data use, we must also consider how we will ensure that our data are accurate, complete, and unbiased. That is called data quality and we will talk more about that in the next session.

3. Data Use Who is using data? Who is happy? Look at these two pictures.
Who do you think is actually using their data? Who do you think is happier?
Who is happy?

4. How Can We Use Data? To know if we are meeting targets.
To make decisions about programs and policies.
To prioritize activities.
To identify support/supervision needs.
To report back to donors (get more funding!).
THIS SLIDE IS ANIMATED.
There are so many uses for our data. What are some ways we can use our data?
Solicit ideas. Then CLICK to display each bullet and briefly discuss.

5. What Data Do OTHERS Need?
Foreign donor gives us pilot money to train local market vendors to be DOTS observers.
NTP  Treatment completion, reduced morbidity.
Donor  Feasibility: Will it work?
Vendors  # recruited, impact on business.
Politicians  Will it save money?
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Of course we have an interest in our data, but others are interested in our data as well. And different stakeholders might be interested in different data. Let’s say we start a pilot program with donor money to see if we can recruit and train market vendors to be DOTS observers.
CLICK to display and review each one.
The NTP cares most about case detection and treatment completion and their impacts on morbidity and mortality. They will want to know how this approach contributed to treatment outcomes.
Because this is a pilot, the donor will want to know if it worked and if we met our target objectives.
The vendors themselves might be interested in the results as well. Vendors we are trying to recruit might want to know how many other vendors are participating and how this activity has impacted their business.
And finally, politicians are always interested in money. If we can show that this approach saves treatment money, politicians might be willing to give us more money for scale-up.

6. Data Stakeholders NTP staff Law/Policymakers Other NTPs
TV, radio, print media
Community-based org.
Evaluators, researchers
Faith-based org.
Donors
Int’l/National NGOs
Partner organizations
Health profession groups
TB clients
The public
Medical centers, clinic administrators
Our own staff/volunteers
THIS SLIDE IS ANIMATED.
Let’s think of all the people or organizations that might have some interest in our data. We will call them our data stakeholders.
Solicit ideas.
CLICK to display list and review, highlighting those not mentioned by participants.

7. Importance of Feedback
Data should not flow in just one direction!
National Program
Regional Office
Facility Manager
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What is the usual direction of data? Who sends the data and who looks at it?
Let participants respond. Then CLICK to show UP arrows.
Usually, data flow upward from the ground to higher levels of ministry or the government.
CLICK to show DOWN arrows.
But data should also flow back to the field in the form of feedback. How else can ground-level providers know how they are performing without established timelines around supervision and feedback? Therefore, data are critical to supportive supervision as well.
CLICK to show red arrows.
Then often we have mini “feedback loops” within the main up and down cycle. Can anyone give us an example of how data might be looped up and back? (Quarterly data review meetings at each level.)
Encourage responses.
DOTS Nurse

8. Reporting Data Think about your audience!
What do they know about the program?
What do they know about ACSM and TB?
How can you “interpret” the data for them?
What are the most important trends?
More data are not always better!
What is the best way to report the data?
Narratives, in person, newsletters, online, charts/graphs/tables.
Because we understand our program and know the activities SO well, we can forget that our stakeholders might not. They may not be as familiar with the terms we use or the context. So always think about your audience for our data: How much do they know about ACSM and TB? How well do they understand the local context? You may need to explain or “interpret” data for them that seem really obvious to you.
When we share data, it is helpful to focus more on trends than on separate pieces of data. Busy managers do not have time to read through pages and pages of tables, especially if the data do not provide any insight on performance. So more data is not always better. Choose tables, charts, and graphs that show only the trends and patterns of most interest to the reader.
In our market vendor example, how would a report to the Ministry of Health look different from a report to community stakeholders like the vendors?
Solicit opinions and discuss briefly, emphasizing the need for more simple language and more visual images for community stakeholders.
What could you do to make sure data and feedback about that data flow in both directions?
Solicit opinions and discuss briefly.

9. Interpreting Data: Example
District
# TB suspects screened
by volunteer
SS+
diagnosis A
234 5 B
124 9 C 26 2 D 32 E
779
116
Total
1195
137
THIS SLIDE IS ANIMATED.
Here is an example of the need to interpret or “explain” data. A team included this table in their quarterly donor report with the sentence: “As you can see, the program is doing well.”
Review contents of table briefly.
What do you think? What could these numbers mean?
CLICK to display questions and review.
As it turns out, there were very reasonable explanations for this. District E is a mining area with much higher incidence of TB. District C is a very remote, rural area. The volunteer in District D moved away to another state in the middle of the quarter. Since the donor is not sitting in the country, the donor does not know this context.
The main message here is to be sure you provide interpretation of your data so that the data are more meaningful.
We will talk next about data quality, but first we will do an exercise to think about data use.
What do these numbers tell you?
The volunteers in District E are superstars!
Volunteer problems in Districts C and D?
Why such wide variability in smear positivity (2% to 15%)?