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Seven steps for Use Routine Information to Improve HIV/AIDS Program_Snyder_5.3.12
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
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?
27.
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
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
Notas del editor
This presentation will introduce a stepwise approach – called the Seven Steps to Use Routine Information to Improve HIV/AIDS Programs. The approach will help us: (READ SLIDE)
(READ SLIDE)Throughout the rest of this workshop, the facilitators will refer to the steps within the Seven Steps approach. Small group work will help us to practice implementing each step along the way.
We are all aware of the challenges involved in providing quality health services in the contexts where we work. In many countries health programs are facing a high disease burden, a growing population, inadequate numbers and poor distribution of qualified health workers, and inadequate health systems to support the distribution of services. It is in this situation that it becomes extremely important for to make the best use of their limited resources. The need to develop strategies, policies, and interventions that are based on quality data and information is urgent.
You may recall that earlier in the workshop/training I read a quote from a national-level policymaker in Nigeria. MEASURE Evaluation also interviewed professionals at the facility level. The situation described by the Head of an ART facility in Nigeria is what happens when information is not shared. Unfortunately, this is common to many facilities, programs, and countries.Note to facilitator: Read slide.
Not reporting or disseminationREVIEWING & DISCUSSING
When we talk about improving the use of and demand for data in decision making we talk about it as a cycle – not a one-time event. The idea of a cycle of evidence-based decision making is the framework on the slide. It starts with basic M&E systems and the collection of information – including ensuring that the information is available and in a format that is easily understood by relevant stakeholders so that the information can be interpreted and used to improve policies and programs. The cycle supports the assumption that the more positive experiences a decision maker has in using information to support a decision, the stronger the commitment will be to improving data collection systems and continuing to use the information they generate. This leads to repeated data use. You will note that this cycle is supported by coordination and collaboration. This coordination is among data users and data producers as well as between management systems and other organizational supports that facilitate and support data informed decision making. Lastly, the cycle is supported by improving capacity to ensure that individuals are equipped with the skills to collect and use data. All of these supports are critical to ensure that the cycle continues functioning to create a culture of data use. Yet, we all know that cycles that rely on multiple inputs, activities and systems to function effectively – often don’t. In the best designed M&E systems you often find lackluster data use. Data is not being used as often as it should be.
Existence of good data does not always translate to regular use of dataMultiple people, processes and systems are involved in DDUHIV context constantly evolves as the epidemic changes and health systems improve
Existence of good data does not always translate to regular use of dataMultiple people, processes and systems are involved in DDUHIV context constantly evolves as the epidemic changes and health systems improve
Collaborating with AIDSRelief on trainings, etc., and they informed us that…
Note curricula that exist around these topicsPackaging and refining
Total - 21 respondents out of 35 trained (60% response rate)1) Question: Since attending the workshop, are you familiar with any instances of staff at your LPTF using information provided to them through the monthly reports or other information requests?85% or 17 out of 20 said yes2) Question: As a result of your participation in the M&E Forum Data Use Training workshop, have you been able to explain to the LPTF staff the meaning of indicators and their relevance to the delivery of services?20 out of 21 said yes (95%)3) Question part a: As a result of your participation in the M&E Forum Data Use Training workshop, have you been able to identify barriers to data use in your LPTF?17 out of 21 identified barriers (81%)Question part b: If yes, were you able to identify solutions to overcome the barriers to data use?14 out of 17 identified solutions (82%)Question part c: If yes, were you able to implement solutions to overcome the barriers to data use in your LPTF?12 out of 14 implemented solutions (86%)4) Question: As a result of your participation in the M&E Forum Data Use Training workshop, have you assisted decision makers with data interpretation?16 out of 21 (76%) said yes5) Question: As a result of your participation in the M&E Forum Data Use Training workshop, have you presented information in different ways (graphically, etc.)?11 out of 20 said yes (55%)
Why should you use the 7 step approach?Because it provides concrete steps that lead to data-informed decision making.The approach encourages more strategic and effective use of data.And finally, it ensures the involvement of both data users and producers.The 7 Step approach provides concrete steps to a process that is often ill defined. Yesterday we talked about the decision making process and the 3 elements of data-informed decision making that needs to be in place for that process to function. Today we will discuss the concrete steps that you can follow once you sit down with your stakeholders and your data to address your decision making needs.
NOTE to facilitator:READ SLIDE
MEASURE Evaluation has identified seven steps to facilitate use of information.NOTE to facilitator: READ SLIDE
With all these data, it may be tempting to “fish out” whatever data are readily available and try to figure out how to use them. This is not the most effective way to strengthen data use. Instead, it is more productive and valuable to answer questions that are of real interest at the facility/program/community/organization level.
As I mentioned, rather than embarking on a fishing expedition, a team at a facility or within an organization can use its time more efficiently by identifying and then prioritizing key questions of interest.A vital part of implementing the seven steps is to start out with a strong team of stakeholders – data users and data producers. These data users and data producers may play a variety of different roles, may have different interests and perspectives, and may have different resources available to themselves and to their team. On the first morning of this workshop you brainstormed and analyzed these stakeholders.In these participatory groups, programmatic questions of interest can be identified by: (READ SLIDE)When we break into groups in a few minutes, each team will have the opportunity to discuss indicators of program success.
Facilitator should read slide.
You can consider these questions as you brainstorm a list of questions of interest.
After generating a list of potential questions of interest, it is important to prioritize the questions to ensure that you are addressing the most important issues and problems first. To prioritize these questions, a team must consider specific criteria and discuss each question in depth.Programmatic relevance: Is the question programmatically relevant and/or of a public health interest? Are others in the community interested in the information?Answerable: Is it possible to answer this question or measure performance with existing data or data that could be collected?Actionable: Does your organization have the authority to act upon the answers to the key question? That is, if data indicate a need for a change in the current course of action, can your organization make the required changes? If not, can your organization influence those with the authority or ability to effect change?Timeliness of the question: Is there a timeline for answering this question or making a decision about the issue at hand? Can some questions be tabled for discussion later to allow the group time to focus on questions that must be addressed more quickly?
Teams can use a matrix, such as this one, to guide and document the process of prioritizing each question. In this matrix, the team can score each question by each criterion.
Once the group has prioritized and refined the questions of interest, it is time to bring data into the picture. Finding the answer to a question may require one indicator or it may require the triangulation of several different performance indicators from multiple data sources.The following must be considered in the process of identifying and focusing on specific data needs and sources:• How frequently or at what intervals do we need this information?• Do the data already exist and are they readily available?• Are the data of sufficient quality?
This figure provides a visual guide of the first three steps in the Seven Step process with a focus on the third step.Note to facilitator: guide audience through the flowchart.
Once specific data sources have been identified and obtained to answer your question of interest (as we saw in Step 3), the data can be transformed into information to facilitate decision making and action. Transforming data into information involves:Isolating the required indicators and data elements; Reviewing and examining data and transforming them into useful information.- Depicting data in an image –a graph, chart, table.
It is important to note that, while the terms data and information often are used interchangeably, there is a distinction. Data refers to raw, unprocessed numbers, measurements, or text. Information refers to data that are processed, organized, structured, or presented in a specific context. The process of transforming data into information is data analysis.NOTE to facilitator: Read slide.
With regard to DDU, we talk a lot about answering programmatic questions. Let’s take a minute to discuss what that means.Suppose you need to know if your program is on track – you probably would look at your program targets and compare them to the actual program performance. This is analysis. Interpretation is using the analysis to further explore your findings and understand the implications for your program. In many cases, this means using additional information, such as vital statistics, population-based surveys, and qualitative data, to supplement the routine service statistics. We will talk more about this later in the workshop.NOTE to facilitator: Read slide.
The terms and concepts of analysis and interpretation are sometimes considered synonymous and are often combined into one process. In the Seven Steps, these processes are separated into distinct steps (Steps 4 and 5) because analysis can be conducted effectively by one person or by a team of people with different backgrounds, but interpretation is most productive when a group is involved. Step 5 involves interpreting information and drawing conclusions about this information through group discussion. Groups should review graphs, tables and information, and then discuss the meaning of these analyses for their organization, project, or program.
When interpreting data and seeking the relevance of our findings, we may ask these questions: 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?Asking these questions will help you to put the data in the context of your program.
ENGAGE PARTICIPANTS:Ask participants, “Given this data, what more would you want to know?” Give an opportunity for a few participants to briefly give their responses. Note their responses on Flip Chart paper.
Step 6 entails convening a meeting with relevant data users and data producers to:• use the conclusions identified in the previous step to brainstorm potential solutions;• further specify, craft, and prioritize these solutions to respond to the problem; and• develop an action plan for implementing each of these solutions.
Teams can use a matrix, such as the one on this slide to document their action plan for implementing a response to address problems identified through the Seven Steps process.
Your program may choose to analyze and interpret data once and take action, or your program or site may need to monitor several indicators over time to develop, test, and validate solutions. The course you choose will depend on a variety of factors, including the size of the program or facility, the nature of the priority questions of interest, and whether or not any problem was highlighted during the process of interpretation (Step 5). Many programs have developed their own framework for improving the quality of their program or service and have designed tools, suchas spreadsheets and dashboards, to monitor their efforts at program implementation and program improvement.A basic table or graph can be used to monitor an indicator over time.
A tool for monitoring can take many forms, and teams should consider the audience and different formats that could be used.NOTE to facilitator: READ SLIDE
The Framework for Linking Data with Action is a management tool—a combination of template and process—that can help to document the Seven Steps process and serves three key purposes:1) Creates a time-bound plan for data-informed decision making by setting dates by which data should be reviewed in relation to key programmatic questions and upcoming decisions. 2) Encourages greater use of existing information byidentifying existing data resources and linking that information with the programmatic questions that need answers to support evidence-based decision making.Last, it provides you with a data-informed decision-making ‘record’ so that you can— 3) Monitor the use of information in decision making—Providesa timeline for conducting analyses and making decisions.
Here is the template for the Framework for Linking Data with Action.Note to facilitator: Mention each column
Remember to:NOTE: Read slide
Finally, please consider joining Data Use Net, a community of practice for professionals interested in increasing their demand for and use of data in decision making.
Now that we’ve talked about who your stakeholders are, it is important to think about how to engage them in your activity. Remember to plan to engage stakeholders throughout the activity, not just at the beginning or end. On the program side at either the national or subnational levels, one can engage users and producers in many ways. Examples include opportunities at quarterly meetings, either for interpretation of program or RHIS data.In M&E system improvement, the involvement is usually at the national level but still involves both users and producers. Often opportunities center around national indicators or data systems.Here we’ve listed a few ideas, but can you think of others?NOTE to facilitator: Ask participants to brainstorm other ways of engaging stakeholders.For those interested in research, here are some other examples:Dissemination meetings, design, implementation, application – involve beyond dissemination of results – formulate questions, use data/research, disseminate data for program improvement.