PARTICIPANT WORKBOOK
Putting Data to WorkEvidence-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
http://www.cdc.gov/globalhealth/SMDP/
Putting Data to Work
CONTENTS
PARTICIPANT WORKBOOK
Putting Data to Work
Introduction
Sustainable Management Development Program ii
Acknowledgements ii
Putting Data to Work
About this Course iii
Target Audience iii
Learning Objectives iii
Icon Glossary iv
Introduction to Putting Data to Work
How Do You Use Data? 1
Kinds of Data 4
Types of Data 5
Data Collection 6
Interpreting Data 8
Summarizing Data 12
Conclusion
Summary 23
What’s Next? 24
Appendices
Resources 26
Glossary of Terms 27
Course Evaluation Form 31
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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 http://www.cdc.gov/globalhealth/SMDP/.
Acknowledgements
Dr. Nicholas Ayebazibwe, African Field Epidemiology NetworkNorthwest Center for Public Health Practice
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Putting Data to Work
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 you complete this course you 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
· Make recommendations and decisions based on data
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Icon Glossary
The following icons are used in this workbook:/ EXERCISE
/ TIP: SUPPLEMENTAL INFORMATION TO HELP PERFORM A TASK MORE EASILY
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Introduction to Putting Data to Work
How Do You Use Data?
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.
How do you use data to make your decisions?
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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.
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/ Exercise 1: Is There a Problem?Review the graph above. Discuss the following questions with the group.
1. What is the graph telling you about fuel usage?
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2. Is there a problem with usage?
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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.
Besides fuel usage, what else would you want to keep track of as a program manager?
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Kinds of Data
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 precious 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.
Health data 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 concerned with population-based data which tell us about the overall “health” of that population. Analyzing these data inform policy and help guide public health programs. If data indicate that there are fewer residents in our community wearing motorcycle helmets than in other communities, we can consider interventions to increase helmet use.
Management
Program and operation data are 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.
What data are available to you today?
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Types of Data
IntroductionQuantitative data provide the what, who, when, and where of health-related events. 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 can be used to explain the why and the how of health-related events. Qualitative data involve observing people in selected places and listening to discover how they feel and why they might feel that way. A focus group of teenage girls could provide valuable insights concerning why they do or do not use contraceptives. A visit to a local clinic might indicate how people feel as they enter the waiting area.
This course focuses on quantitative data.
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Data collection
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 had 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. Counts are commonly used for program planning and monitoring.
It is important to note that 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.
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.
The check sheet on the following page shows the number of appointments that were missed at 5 clinics over a 7 week period. Each tally represents one missed appointment. For example, in week 1 there was 1 missed appointment at clinic D.
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Location / Missed AppointmentsWeek 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
/ Exercise 2: Using a Check Sheet
1. 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.
2. Use the counts from each clinic to add up the total number of missed appointments over the 7 week period.
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Interpreting Data
Measuring the frequency of events, such as disease or health events, is at the heart of public health surveillance and resource allocation. And measuring results is at the heart of good leadership and management.The most commonly used measures for assessing frequency are ratios, proportions, percents and rates.
Ratios, Proportions, Percents and Rates
(Adapted from “Data Interpretation for Public Health Professionals, Northwest Center for Public Health Practice”)
A ratio is a comparison of two different things; it is a numerical expression that indicates the relationship between two or more things. The two numbers are generally separated by a colon, but can also be expressed as a fraction. For example, the ratio of missed appointments between Clinic A (8) and Clinic B (16), is 8:16 or 8/16. We can reduce this to 1:2. So for every missed appointment at Clinic A, there are 2 at Clinic B.
A proportion is a ratio in which the numerator is included in the denominator; it is a numerical expression where a part is compared to the whole. A proportion can be expressed as a fraction or a decimal. For example, we can express the relationship of Clinic A to the total number of missed appointments as a proportion. The proportion of missed appointments in Clinic A compared to the group is 8 divided by 54 or 0.15.
Clinic A 8
= = 0.15
Total Missed 54
To be more easily interpreted proportions are often multiplied by 100, 1000 or 100,000, so we can also express this fraction as 15 per 100. When multiplied by 100, proportions can also be reported as percentages, so we can say that the percentage of missed appointments in Clinic A is 15%.
As you can see, proportions and percents are essentially the same measure.
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RatesA rate is often a proportion, with the added dimension of time. Rates measure the frequency at which a health event occurs over a period of time. In health, a rate represents the burden of disease or other health related outcome during a specific time period. In management, a rate might represent the number of times a pharmacy runs out of medicine or a vehicle breaks down. The general formula for calculating rates is shown below:
Number of persons
experiencing the event
Number of persons “at risk” of x K
experiencing the event at a
specified time period
K = A standard unit of the population (per 100, 1000, or 100,000)
Both the numerator and denominator must represent the same time and place.
Rates measure events in relation to the size of the population in which they occurred at a specific time and place, or in other words, the population at risk. Rates allow us to compare the risk of health events across different groups of people, places, and times. They also help us to describe the burden of disease or other health events in a population over time.
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/ How do you decide what to use as your K? Look at what you are comparing to. For example, if national data are described in terms of ‘per 100,000’, use this as your unit, for easier comparison.The table below shows the number of deaths from HIV/AIDS among women from Guatemala and Panama in 2002.
Country / HIV/AIDS Deaths / Female Population
Panama / 114 / 1,573,289
Guatemala / 167 / 6,342,703
World Health Organization www.who.int/entity/healthinfo/statistics/bodgbddeathdalyestimates.xls
Let’s use this table to calculate the rates of death from HIV/AIDS in these populations, also called the mortality rate.
1. What is the mortality rate from HIV/AIDS per 100,000 women in Panama?
2. What is the mortality rate from HIV/AIDS per 100,000 women in Guatemala?
3. Based on the rates we have calculated which country has a higher rate of women dying from the disease?
4. Which country has the higher number of women dying from HIV/AIDS?
Why Use Rates?
You can also use rates for managing operations and resources. For example, you can calculate the rate of employee turnover or the vaccination coverage rates across provinces in your country. You can also calculate rates for hospital admissions to determine whether rates are increasing or decreasing for certain diseases. Rates can help play an important role in improving organizational performance across key indicators.
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