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

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

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



                                      3
Why Improve Data-informed
    Decision Making?
 Pressing need to develop health
     policies, strategies, and
           interventions
“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
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.
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
Data-informed Decision Making Cycle
Why Improve Data Demand & Use?
       Decision Making Context




                     P
                     Questions
                     P
How do you and your
organization use data and
information?
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
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
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
Seven Steps to Use Routine
Information to Improve HIV/AIDS
Programs
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
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
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
No need to go fishing…

Instead…answer questions that
  respond to true need and interest.
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.
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
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?
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
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?
Step 2 – Prioritize Key Questions
            of Interest
   Programmatic relevance
   Answerable
   Actionable
   Timeliness of the question
   Others?
       Ensure question is specific
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.
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?
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
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
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
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
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
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?
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
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
Program Action Plan
Step 7 – Continue to Monitor Key
           Indicators

 Monitor implementation of action plan
 Consider frequency and duration of monitoring
 Develop tool for monitoring
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
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
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)
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
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
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

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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

  1. 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)
  2. (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.
  3. 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.
  4. 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.
  5. Not reporting or disseminationREVIEWING & DISCUSSING
  6. 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.
  7. 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
  8. 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
  9. Collaborating with AIDSRelief on trainings, etc., and they informed us that…
  10. Note curricula that exist around these topicsPackaging and refining
  11. 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%)
  12. 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.
  13. NOTE to facilitator:READ SLIDE
  14. MEASURE Evaluation has identified seven steps to facilitate use of information.NOTE to facilitator: READ SLIDE
  15. 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.
  16. 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.
  17. Facilitator should read slide.
  18. You can consider these questions as you brainstorm a list of questions of interest.
  19. 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?
  20. 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.
  21. 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?
  22. 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.
  23. 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.
  24. 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.
  25. 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.
  26. 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.
  27. 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.
  28. 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.
  29. 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.
  30. 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.
  31. 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.
  32. 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
  33. 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.
  34. Here is the template for the Framework for Linking Data with Action.Note to facilitator: Mention each column
  35. Remember to:NOTE: Read slide
  36. 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.
  37. 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.