Putting Data to Work
Evidence-Based Health Program Planning and Management
SUSTAINABLE MANAGEMENT DEVELOPMENT PROGRAM
Sustainable Management Development Program
Division of Public Health Systems and Workforce Development
Center for Global Health
U.S. Centers for Disease Control and Prevention
PUTTING DATA TO WORK
Putting Data to Work
Contents
Introduction
Sustainable Management Development Program
Acknowledgements......
Course Overview
About this Course......
Target Audience......
Learning Objectives......
Materials and Equipment......
Workshop Schedule
Class Preparation Checklist......
Classroom Setup......
Instuctor Notes...... viii
Icon glossary......
Course Instruction
Introduction to Putting Data to Work...... 1
How Do You Use Data?...... 2
Data
Kinds of Data...... 5
Types of Data...... 7
Data Collection...... 9
Interpreting Data
Ratios...... 12
Proportions and Percentages...... 13
Rates...... 15
Why Use Rates?...... 19
Summarizing Data
Summmarizing Data...... 21
Tables...... 2
Graphs...... 25
Bar Charts...... 32
Pie Charts...... 37
Maps...... 39
Stratification...... 43
Conclusion
Summary...... 47
What's Next...... 48
Resources...... 49
Appendices...... 50
AppendiX A: Summarizing Data Scenarios...... 51
AppendiX B: Glossary of Terms...... 57
AppendiX c: Course Evaluation Form...... 60
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Introduction
Sustainable Management Development Program
SMDP works with ministries of health, educational institutions, nongovernmental organizations, and other partners to strengthen leadership and management skills and systems to improve public health in low resource countries.
Program Strategy
SMDP strengthens leadership and management skills and systems through:
- Integration with country public health priorities
- Strategic partnerships
- Technical assistance and training
- Policy and systems development
- Advocacy and education
- Evaluation
For more information, visit
acknowledgements
Dr. Nicholas Ayebazibwe, African Field Epidemiology Network
Northwest Center for Public Health Practice
Course Overview
About this Course
The goal of this course is to enable participants to use data to make decisions and recommendations. Data can be used for planning and decision making regarding public health needs, organizational performance and monitoring and tracking evaluations.
This course will focus on quantitative data.
Target Audience
This course is designed for leaders and managers of health organizations, programs and operations.
Learning Objectives
When participants complete this course they will be able to:
- Describe how data are used in health organizations and programs
- Identify methods for summarizing data
- Explain how data analysis and interpretation can improve decisions
- Prepare and apply tables, graphs, and charts such as line graphs, bar charts, pie charts, and spot (dot) maps, for summarizing data
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materials and equipment
MATERIALS / EQUIPMENTFor the Instructor:
- PowerPoint® Slides
- Participant Workbooks
- Summarizing Data Scenarios
- Course Evaluation Form
- Extra Pens and Pencils
- Calculators
- Flip charts
- Laptop
- LCD Projector
- Tape
Copies of the PowerPoint slides should not be handed out to course participants.
WORKSHOP SCHEDULE
Tasks / Expected TimeInstruction to Putting Data to Work:
- Introduction
- How do you Use Data?
- Exercise 1: Is there a Problem?
5 minutes
10 minutes
10 minutes
Data:
- Kinds of Data
- Types of Data
- Data Collection
- Exercise 2: Using a Check Sheet
10 minutes
10 minutes
5 minutes
10 minutes
Interpreting Data:
- Ratios
- Proportions and Percentages
- Rates
- Rates Example
- Why use Rates?
- Exercise 3: Calculate Ratios and Rates
5 minutes
10 minutes
15 minutes
15 minutes
5 minutes
10 minutes
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Summarizing Data:- Summarizing Data
- Tables
- Graphs
- Line Graphs
- Creating Line Graphs
- Bar Charts
- Exercise 4: Which Method do you Use?
- Pie Charts
- Maps
- Stratification
- Exercise 5: Summarizing data
5 minutes
10 minutes
5 minutes
5 minutes
15 minutes
10 minutes
10 minutes
10 minutes
15 minutes
10 minutes
60 minutes
Conclusion:
- Summary
- What’s Next
5 minutes
5 minutes
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The listed times are approximates and should be verified during classroom preparation. Be sure to allot time for breaks.
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Class Preparation Checklist
Task / Obtain and test LCD projector and personal computer
Obtain flip charts and markers: 1 for every 4-5 participants
Copy participant materials. For each participant:
- Participant Workbook
- Workshop evaluation form
- Appendix A: Summarizing Data Exercise
- Answer sheet for Summarizing Data Exercise
Obtain and test PowerPoint file (PDW-PPT)
Prepare flip charts
Put slide #12 on a flip chart to reference during that section
Classroom Setup
Arrive early to setup the classroom.
- Arrange tables for groups of 6.
- Provide a flip chart and easel for each table of 6 participants.
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Instruction Notes
The following notes refer to slides in the PowerPoint presentation: “PDW-PPT.” Suggested actions and script for the instructor are located in the Script/Key Points section of each slide. Also included are references to the slide number and page number in the participant workbook, as well as instructions on when and how to use the exercises. Use these materials as you prepare for your session to the guide you during the workshop. Be sure to refer participants to the appropriate page number in their workbook throughout the session.
Script for the facilitator to SAY is written like this.Instructions for the facilitator to DO are written like this.
Possible answers are written like this.
icon glossary
/ SPECIFIC SLIDE FOR USE DURING THE EXPLANATION/ FLIPCHART USE
/ SUPPLEMENTAL INFORMATION TO HELP PERFORM A TASK MORE EASILY
/ SMALL GROUP EXERCISE
/ QUESTIONS FOR FACILITATOR TO ASK PARTICIPANTS
/ VIDEO PRESENTATION
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Course Instruction
Introduction to putting data to work
Expected Time: 25 minutes
______
IntroductionWORKBOOK CLOSED / 5 minutes
SCRIPT/KEY POINTS
- Welcome the participants and introduce yourself
- Introduce dignitaries (allow them to speak)
- Explain housekeeping items, such as break times, restroom locations, etc.
- Explain the workbook and how they will use it to complete exercises and take notes.
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How Do You Use Data?Workbook Page 1 / 10 minutes
SCRIPT/KEY POINTS
- Think about the many decisions that health managers make in a day.
- Some of them are simple and straightforward, and some of them are not as simple as they may appear!
- And then there are decisions that managers know will have significant impact on the population they serve, on their workforce or on the way work gets done.
- As a manager concerned with the health of your community and the population your program serves, as well as the performance of your organization, timely and accurate analysis of data can inform technical as well as administrative decisions.
- Ask the participants, can you think of any ways that you use data to make your decisions?
- As a large group, ask the participants to share their answers.
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Exercise 1: Is There A Problem?Workbook Page 2 / 10 minutes
SCRIPT/KEY POINTS
- Let’s go through a scenario. Imagine that you are a medical director of a district hospital and part of your job is to manage resources. Each month your employees submit receipts for their fuel usage.
- Instead of just approving the bills, you can study the data they provide.
- Collecting and analyzing these simple data will allow you to better track and understand trends in fuel usage.
- Consider the following graph which tracks fuel usage over a year for all employees of the district hospital.
- As a large group discussion, ask the participants the following questions. Write their responses on a flip chart to possibly use later during the stratification portion of this session.
–What is the graph telling you about fuel usage?
Answer: Fuel usage was lowest between April and June. It reached its highest peaks in February, July and September. There was a sharp decline in fuel use between February and April and also between September and December. Fuel use continuously declined after the high peak in September.
–Is there a problem with usage?
Answer: We cannot tell if there is a problem with fuel usage because there is not enough information to answer that question. The graph shows fluctuation in fuel use but it doesn’t indicate that something is wrong. We won’t know anything unless we continue to monitor the trends and ask questions to find out what is going on.
- Without data, you can only guess what is not working, how to correct it and whether your efforts at change were effective.
- While your guesses may be informed by your experience, this approach is not likely to be successful, especially in the long term.
- Only data can provide the guidance you will need. But collecting the data is only one component of program management and planning.
- Accurately analyzing and interpreting data over time will help you identify areas that need your attention and assist to prioritize health problems.
- Ask the participants, as themedical director of this district hospital, what are some other things you would want to keep track ofbesides fuel usage?
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Data
KINDS OF DATA | 5
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Expected Time: 35 minutes
______
Kinds of DataWorkbook Page 4 / 10 minutes
SCRIPT/KEY POINTS
- You probably have access to more data than you realize.
- If you work in a hospital or clinic, the patient admissions and medical records can provide valuable information to help you manage your programs.
- Similarly, data that is collected about employees may be useful for managing human resources.
- Just as in our example of fuel usage, something as simple as an invoice can provide you valuable data for program management and planning.
- There are different kinds of data. Health data, for example, can focus on individuals or entire populations.
Individual:
- A classic example of individualized data is a patient’s medical record.
- Each record is devoted exclusively to one person and contains information about his or her unique illnesses, injuries, behaviors, etc.
- The data are used primarily to improve the health of that one individual.
Population:
- In public health the focus is primarily on populations (communities, cities, districts, provincials).
- We are mostly concerned with population-based data because it will tell us about the overall health of that population.
- Analyzing these data can inform policy and help guide public health programs and recommendations.
- For example, if data indicated that there are fewer residents in our community wearing motorcycle helmets than in other communities, we can consider interventions to increase helmet use.
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Management:- Then there are program and operation data, which are also valuable for making decisions and recommendations.
- These data enable you to monitor and evaluate the use and distribution of resources, such as staff, supplies, and equipment.
- Examples of management data include the fuel usage example mentioned earlier, as well as human resources and budget information.
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Types of DataWorkbook Page 5 / 10 minutes
SCRIPT/KEY POINTS
Generally, there are two types of data: quantitative and qualitative.
Quantitative Data:
- Quantitative data provide the what, who, when, and where. They are measurable and tangible.
- Quantitative data involves the counting of people, behaviors, conditions, or other discrete events; classifying those events into categories; and using math and statistics to answer questions.
What Numbers of deaths can be used to identify leading causes of death
Who Numbers of smokers and nonsmokers by gender can be used to determine whether men are more likely to smoke than women
When Keeping track of hospital admissions can identify when more staff may be needed
Where Comparing the proportion of women who began prenatal care after the first trimester in various districts will provide an indication of where access to prenatal services may be a problem
Qualitative Data:
- Qualitative data, on the other hand, can be used to explain the why and the how.
- Qualitative data involve observing people in selected places and listening to discover how they feel and why they might feel that way.
- For example, a focus group of teenage girls could provide valuable insights concerning why they do or do not use contraceptives.
- Interviews in a local clinic might indicate how people feel about the clinic’s services.
- Quantitative data and qualitative data often interact and complement each other. Using both types of data can give you a better picture of the situation.
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- Quantitative data will typically give you the numbers or measurable details (size of population, staff turnover rates, etc.), while qualitative data will help you understand why something is happening.
- For example, quantitative data can tell us that clinic wait times are higher in one district as compared another. However, it is through qualitative data that we can get a better understanding of why the wait times are higher.
- Perhaps the clinic has very few staff serving a large population, it double books appointments or patients are typically running late so they miss the appointment time and have to wait even longer. This detail is not typically found through quantitative data.
- In this course, we will focus almost entirely on quantitative data.
- Ask the participants to think about that data that crosses your path each day, i.e. fuel usage, hospital admissions, etc.
- Can you think about any data that crosses your path each day? What data are available to you?
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Data CollectionWorkbook Page 6 / 5 minutes
SCRIPT/KEY POINTS
- There are many ways to collect useful data.
- You may already be collecting data formally through a surveillance system or with a management system such as financial management or human resources information system.
- You can start your own data collection with a simple tool.
Counts:
- Counts are the simplest measure of occurrence.
- A count is just the actual number of events in the population of interest, such as identifying how many individuals have a specific illness such as HIV.
- You can use counts in management as well, such as counting the number of times an employee calls in sick to work each month.
- Counts are commonly used for program planning and monitoring.
- Having a count by itself is helpful in planning things like the amount of vaccines or other medications to order, but counts alone do not provide context.
- Counting events or cases does not give any indication of the problem in relation to the size of the population.
- For example, 76 cases of guinea worm in the capital city of Gaborone would be very different from 76 cases in a small rural village in Botswana.
Check Sheet:
- One way to organize counts is through the use of a check sheet. A check sheet is a table or form that is used to systematically register data as it is collected.
- Check sheets can be used to indicate how often an event occurs.
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Exercise 2: Using A Check SheetWorkbook Page 7 / 10 minutes
SCRIPT/KEY POINTS
- The check sheet on page 7 in your workbook shows the number of appointments that were missed at 5 different clinics over a 7 week period. Each tally represents one missed appointment.
- Click to show: For example, in week 1 there was 1 missed appointment at clinic D.
Location / Missed Appointments
Week 1 / Week 2 / Week 3 / Week 4 / Week 5 / Week 6 / Week 7 / Totals
Clinic A / /
Clinic B /
Clinic C / / / / /
Clinic D / / / /
Clinic E / /
Totals # people who missed appointments / 6 / 2 / 26 / 5 / 6 / 5
Total # appointments booked for week / 50 / 65 / 45 / 52 / 61 / 49 / 60 / 382
Percent missed / 12.0 / 3.1 / 57.8 / 9.6 / 9.8 / 10.2
- Ask the participants to turn to page 7 in their workbook to complete the following task.
- Using the check sheet, fill in the missing data for week 7 using the following information: 3 people from Clinic C missed appointments and 1 from Clinic D.
- Use the counts from each clinic to add up the total number of missed appointments over the 7 week period.
Location / Missed Appointments
Week 1 / Week 2 / Week 3 / Week 4 / Week 5 / Week 6 / Week 7 / Totals
Clinic A / / / 8
Clinic B / / 7
Clinic C / / / / / / / 16
Clinic D / / / / / / 12
Clinic E / / / 11
Totals # people who missed appointments / 6 / 2 / 26 / 5 / 6 / 5 / 4 / 54
Total # appointments booked for week / 50 / 65 / 45 / 52 / 61 / 49 / 60 / 382
Percent missed / 12.0 / 3.1 / 57.8 / 9.6 / 9.8 / 10.2
Interpreting Data