1. Presenting information

2. Appropriate Information & Feedback Reports, tables & graphs
Information Cycle
Stages
Tools
Outputs
What do we collect?
Timely Quality data
data sources & tools
How do we process it?
How do we use it?
Reliable Information
Data quality checks, Data analysis
The Inf Cycle enables one to see the links between the different stages of information. What are these stages or phases? As you can see through this diagram, phases of information handling include the process of data capturing, through observation of real events (collecting), processing data (process means ensuring data quality by auditing data (3Cs), collating (aggregating) data… so that one can analyse it and turn it into information. The information is then presented, interpreted and used for decision-making.
Appropriate Information & Feedback
Information
How do we present it?
Reports, tables & graphs

3. Preparing for Presentation essential prerequisites
Correct
Complete
submission by all (most) reporting facilities
Consistent
data within normal ranges
clear definitions / standards
Timely
Review – reinforce importance of data that complies with 3 C’s

4. Presenting Information
Tabular: frequency distribution table
Graphs: Histogram, Line diagrams, Scatter plot, Bar chart, Pie chart, population pyramids
Numerical:
 Measures of Typicality or Center: mode, median, mean
 Measures of Variability (or Spread): range, variance, standard deviation
 Measures of Shape: skewness, kurtosis
Proportions, rates, ratios
Maps: geographical representation (GIS)

5. Qualitative (Characteristics)
Types of data
Data
Quantitative
(Numbers)
Qualitative (Characteristics)
Discrete
Continuous
Discrete
categories/
kinds
counts
measures

6. Numerical Data Continuous – they are measurable
Examples:
Age of patients in years or months
Weight of newborn in grams
Discrete – they are counted (possible values are distinct or separate)
The size of a family expressed as the number of children
The number of days since the begining of a disease
units of measurement

7. Non-numerical Data
qualitative description of categories of a characteristic
Examples:
The gender of a patient is recorded as “male” or “female”;
The list of diagnoses in a health center

8. Mark with  in the blank spaces
Data
Quantitative
Qualitative
Discrete
Continuous
Number of beds per HC
Bed ocupation
Addresses of patients
Number of children
Patient temperature in ºC
Cost of a drug presciption
Population of a village
Age of patients in years
Number of broken vials

9. Tables Number of children per family in Maputo, 2005
Source: Statistics & Planning Directorate, 2005

10. Tables easy to produce – difficult to use Ideally should contain:
Beware information overload:
easy to produce – difficult to use
Ideally should contain:
Few rows
Few categories/columns
Useful for:
assess quality
trends over time
make comparisons
identify outliers, gaps
Explore the advantages & disadvantages of using tables

11. GRAPHS (a visual representation of data)
Advantages:
Information is instantly conveyed
Data are presented clearly and simply
Can expose relationships and patterns
Detect trends over time
Can be used to emphasise information

12. Graph Elements
Title – descriptive clinic name, what is graphed and the time period
Y axis – must ALWAYS be labeled
Y axis label
X axis – label if appropriate
Key or legend – used if more than one element graphed Y X
Review all graph elements – labels, axis etc.
Emphasize the importance of the Y-axis
Source: Notes:
Scale – be appropriate

13. Five rules for graphs
Never put too much information in the graph. KEEP IT SIMPLE.
Be careful about mixing different activities: stick to one group of people or diseases or services.
Label your graph: always have a clear heading, easily read labels on the axes, and a legend which explains each of the lines or bars.
Select scales that fit the entire graph on both axes.
Where possible, draw a target line or reference point to show where you are aiming at.

14. Type of graphs Continuous data Discrete Data histograms line Graphs
scatter Graphs
Discrete Data
bar graphs
pie charts

15. Line graph
Graph 2: PHC headcount under 5 years old, Manyara Clinic, 2001
Explore line graphs - selection & use
Explore the advantages & disadvantages
accurate, can show minute changes in the relationships between 2 major variables
displays trends over time
can be useful if more than one data item is used

16. Bar graph versus Line graph
which one is best?

17. Line graph, with two dependent variables

18. Line graph, for cumulative coverage
Explore cumulative coverage graphs - selection & use
Explore the advantages & disadvantages

19. Line graph, for cumulative coverage
Simple and effective monitoring tool
Used when targets are set for a year i.e. immunization, antenatal coverage, etc.
Each month, data is graphed individually and also added to the previous month
A target is set, a target line is drawn and progress is monitored with respect to the target line
Explore cumulative coverage graphs - selection & use
Explore the advantages & disadvantages

20. Graphs for sets of discrete data
pie charts
bar graphs

21. Pie chart
Explore pie graphs - selection & use
Explore the advantages & disadvantages
best type of graph for showing the relative proportions of different categories to each other and to the whole
can be used when exact quantities are less important than the relative sizes of the parts
Works best with large discrepancies
Only for data that adds up to a total (100%)

22. Bar graph, simple
** Slides 4 – 8 explore the differences between the various graph types & the rationale for selection & use of each type as well as advantages & disadvantages of each type
Explore bar graphs - selection & use
Explore the advantages & disadvantages
displays data over time or can compare 2 or more different facilities / districts / regions / years

23. Bar graph, stacked
** Slides 4 – 8 explore the differences between the various graph types & the rationale for selection & use of each type as well as advantages & disadvantages of each type
Explore bar graphs - selection & use
Explore the advantages & disadvantages
it displays the quantities, but it also shows the relative proportions of the categories to each other and to the whole
BUT hard to estimate the value of the variables at the top

24. Common faults with graphs
No title
No labels for the variables
No units of measurement (or incorrect units!)
No scale markings (or just too many!)
Inappropriate scale choice – data points should be evenly represented
Incorrect choice of independent (x-axis) and dependent (y-axis) variables
No legends when needed
Too high ink-to-data ratio (e.g. 3D graphs)
Don’t trust the computer!

25. Graphs- population pyramids
Explore population pyramid graphs - selection & use
Explore the advantages & disadvantages
they highlight the differences in age distribution between males and females as well as proportional age categories

26. BAD GRAPHS YOU SHOULD NOT BUILD!

28. Where do the lines cross?

29. …gone fishing…

31. and finally, some inspiration…
GapMinder