This document outlines a 7 step approach to using routine data to improve HIV/AIDS programs. The 7 steps are: 1) identify questions of interest, 2) prioritize key questions, 3) identify data needs and sources, 4) transform data into information, 5) interpret information and draw conclusions, 6) craft solutions and take action, and 7) continue to monitor key indicators. The approach aims to facilitate using existing data to answer important questions and inform decision making through collaborative work between data users and producers. Overall, the 7 step approach provides a framework to strategically use routine monitoring data to strengthen HIV/AIDS programs and policies.

1. Seven Steps to Use Routine
Information to Improve HIV/AIDS
Programs
Presented by
Elizabeth Snyder
Futures Group, MEASURE Evaluation
May 3, 2012

2. Session Objectives
 Introduce a stepwise approach to
 link data with pressing questions of interest
 facilitate use of information in decision making

3. Session Overview
 Overview of Data Demand and Use
Concepts
 Why use the Seven Steps Approach?
 What are the Seven Steps?
 Small group work
3

4. Why Improve Data-informed
Decision Making?
Pressing need to develop health
policies, strategies, and
interventions

5. “We are always giving patient forms and data to
our M&E Unit, who then gives data to donors and
the government. I am the head doctor and I
never have the chance to look through the data
before they go up. We just keep giving data up
and up, and we never hear back about it…”
Head of ART facility, Nigeria

6. Purposes of Monitoring and
Evaluation
 Determine whether a plan or program is on
schedule with planned activities
 Assess whether a policy, plan or program has
produced desired impacts
 Generate knowledge:
• Identify factors (individual, community, programmatic)
that influence health outcomes
 Help inform policy, planning or program
decisions: new services, resource allocation,
corrections, etc.

7. Definitions
 Data Demand - decision makers specify what kind of
information they want & seek it out
 Data use – Using data in the decision making
process
 monitor a program
 create or revise a program or strategic plan
 develop or revise a policy
 advocate for a policy or program
 allocate resources

8. Data-informed Decision Making Cycle

9. Why Improve Data Demand & Use?
Decision Making Context
P
Questions
P

10. How do you and your
organization use data and
information?

11. We can use information to…
 Inform policies and plans
 Raise additional resources
 Strengthen programs and improve results
 Ensure accountability and reporting
 Improve quality of services provided
 Contribute to global lessons learned

12. Examples of data use
 Adherence counselors and community teams
using information to track losses
 Increasing numbers of counselors and uptake
classes to respond to growing waiting list
 Revising standards of care and national
guidelines based on operations research
 Forecasting commodity needs
 Revising targets and funding based on utilization
rates

13. Barriers to Data Use
 Organizational structures
 Lack of a ―data culture‖ among decision makers
 Lack of technical skills and technology,
particularly at local levels
 Training often ad hoc and not sustainable
 Structural constraints– roads, telecommunication
 Poor funding for M&E
 Political interference

14. Seven Steps to Use Routine
Information to Improve HIV/AIDS
Programs

15. Why Use the 7 Step Approach
 Provides concrete steps to data-informed
decision making
 Encourages more strategic and effective use of
data
 Ensures involvement of data users & producers

16. Stepwise guidance helps to…
 Identify and understand trends and needs;
 More effectively plan and set priorities;
 Support changes in program and service delivery;
 Support requests for additional resources;
 Justify changes in policies affecting service delivery;
 Provide evidence-based clinical decision making;
 Facilitate accountability for expended resources;
 Communicate importance of HIV/AIDS services to the
community.
25

17. Seven Steps Approach
 Step 1 - Identify questions of interest
 Step 2 - Prioritize key questions of interest
 Step 3 - Identify data needs and potential sources
 Step 4 - Transform data into information
 Step 5 - Interpret information and draw
conclusions
 Step 6 - Craft solutions and take action
 Step 7 - Continue to monitor key indicators

18. No need to go fishing…
Instead…answer questions that
respond to true need and interest.

19. Core Data Demand and Use
Principle
Data users and data producers can work
together to identify key programmatic questions
and concerns and to link these questions to the
data available in their respective settings.

20. Step 1 - Identify questions of
interest
 Discussion of indicators of program success;
 Mapping how clients flow through the service
 Generating new questions through data analysis
 Brainstorming what different staff are interested in
knowing about the program;
 Feedback from clients
 External factors: audits, program evaluations, donor
questions

21. Programmatic Questions
 What percentage of HIV+ pregnant women in
care actually are delivering in health
facilities?
 What percentage of clients starting ART are
lost to follow-up?
 Are the number of family planning clients
decreasing?
 What percentage of pregnant patients who
are HIV+ actually are receiving ART?

22. Small Group Work – Step 1
1. Convene in small groups and choose
note taker
2. Brainstorm a list of questions of
interest to your organization (10 min.)
3. Be prepared to call out questions in
plenary

23. Defining Program Success -
Questions to Consider
 What do you want or need to know in order to
say your program is working?
 How do you know that your program or service is
working?
 Is your program or service improving client‘s
health?
 How do you know if there are problems or that
your program is not achieving its pre-determined
objectives?

24. Step 2 – Prioritize Key Questions
of Interest
 Programmatic relevance
 Answerable
 Actionable
 Timeliness of the question
 Others?
Ensure question is specific

25. Prioritizing Questions
PROJECT/ORGANIZATION
POTENTIAL SOLUTIONS PROGRAMMATIC ANSWERABLE ACTIONABLE TIMELINESS OF THE TOTAL
RELEVANCE QUESTION
Please list your proposed Highly relevant=4 Easy to answer=4 Highly actionable=4 Immediate=4
Somewhat=3 Feasible with routine Potential barriers=3 Next quarter =3
solutions, and rank them
Little Relevance =2 data=3 Low chance of Next month =2
according to each criterion. None=1 May require non routine action=2 Distant future =1
data=2 Little to no chance of
Significant data action=1
collection=1
1.
2.
3.

26. Step 3 – Identify Data Needs and
Potential Sources
 Enlist M&E Officer
 How frequently or at what intervals do we need
this information?
 Do the data already exist and are they available?
 Are the data of sufficient quality?

28. Step 4 – Transform Data into
Information
 Isolate required indicators and/or data
elements
 Analyze the data and calculate the
indicator
 Depict data in an image
(graph, chart, table)
2.0%
% of ANC Clients Testing Positive for HIV
1.8%
1.6% 1.5% 1.5%
1.4%
Percentage
1.2%
1.1%
1.0%
0.8%
0.6%
0.4%
0.2%
0.0%
2004 2005 Jan - Jun 2006
Year

29. Data Analysis
 Turning raw data into useful information
 Purpose is to provide answers to questions being
asked at a program site or research questions
 Even the greatest amount and best quality data
mean nothing if not properly analyzed—or if not
analyzed at all
38

30. Data Analysis
 Analysis does not mean using computer software
package
 Analysis is looking at the data in light of the
questions you need to answer:
 How would you analyze data to determine: ―Is
my program meeting its objectives?‖
39

31. Answering Programmatic
Questions
 Question: Is my program meeting its objectives?
 Analysis: Compare program targets and actual
program performance to learn how far you are from
target.
 Interpretation: Why you have or have not achieved
the target and what this means for your program.
 May require more information.
40

32. Step 5 – Interpret Information and
Draw Conclusions
 Convene group or team
 Review graphs, tables, and information
 Adding meaning to information by making
connections and comparisons and exploring
causes and consequences
 M&E Officers and service providers often helpful
in understanding meaning of analyses

33. Interpretation: Relevance of Finding
 Is there anything that surprises you in the data?
 Are there any highs and lows in the data?
 How does the indicator compare to other time
periods, other facilities?
 How does the indicator compare to the target/ideal?
 How far from the target/ideal is it?

34. The Findings
 About 10% of men & women did not know using condoms
can reduce the risk of HIV
 85% women, 75% men knew that limiting sex to 1 uninfected
partner can reduce the risk of HIV
 79% women, 74% men knew that using condoms and
limiting sex to 1 uninfected partner can reduce the risk of HIV
 Of the 4.2% of men with >2 partners, 25% didn‘t use
condoms at last sex
 Of the 0.6% of women with >2 partners, 28.9% didn‘t use
condoms at last sex

35. Step 6 – Craft Solutions and Take
Action
 Engage variety of stakeholders to craft solutions
– ensure ownership
 Discuss conclusions from interpretation
 Brainstorm potential solutions
 Further specify, craft and prioritize these
solutions
 Develop an action plan

36. Program Action Plan

37. Step 7 – Continue to Monitor Key
Indicators
 Monitor implementation of action plan
 Consider frequency and duration of monitoring
 Develop tool for monitoring

38. Developing a Tool for Monitoring
 Who needs to know about progress and
improvement in performance?
 Spreadsheets and dashboards
 Wall charts and graphs
 Staff meetings to discuss

39. Framework for Linking Data with
Action
 Documents the overall Seven Steps process
 Creates a time-bound plan for information-
informed decision making
 Encourages greater use of existing information
 Monitors the use of information in decision
making

40. Framework for Linking Data with
Action
Decision Program/ Decision Indicator Data Timeline Commu-
/ Action Policy Maker /Data Source (Analysis) nication
Question (DM), (Decision) Channel
Other
Stakehold-
ers (OS)

41. Data Use Guiding Principles
 Involve data users and data producers
 Start with clear, specific questions
 Present data in easy to understand formats
 Collaborative interpretation
 Take action based on data
 Continuous monitoring to ensure improvement
 Building data use into your work takes planning
and dedicated time

42. Join Data Use Net
 Send an email to listserv@unc.edu. Leave the
subject field blank and in the body of the
message type ‗subscribe DataUseNet.‘ For
example:
To: listserv@unc.edu
Subject: Subscribe DataUseNet

43. Small Group Discussion
What can you do to strengthen
use of information?
 Generate a list of actions that you, your
colleagues and your organization could take to
strengthen data use.
 Identify at least two or three of these actions that
could be taken immediately