Data Presentation, Interpretation and Use

1. Data Presentation, Interpretation and Use

2. Learning objectives Participants will be able to: • Understand different ways of summarizing data • Choose the right table/graph for the right data and audience • Ensure that graphics are self-explanatory • Create graphs and tables that are attractive

3. Do you present yourself like this?

4. So why would you present your data like this?

5. Or this?

6. This is Better! Use of ITNs in Zambia

7. Effective presentation • Clear • Concise • Actionable • Attractive

8. Effective presentation • For all communication formats it is important to ensure that there is: • Consistency • Font, Colors, Punctuation, Terminology, Line/ Paragraph Spacing • An appropriate amount of information • Less is more • Appropriate content and format for audience • Scientific community, Journalist, Politicians

9. Summarizing data • Tables • Simplest way to summarize data • Data is presented as absolute numbers or percentages • Charts and graphs • Visual representation of data • Usually data is presented using percentages

10. Points to remember • Ensure graphic has a title • Label the components of your graphic • Indicate source of data with date • Provide number of observations (n=xx) as a reference point • Add footnote if more information is needed

11. Tips for Presenting Data in PowerPoint • All text should be readable • Use sans serif fonts • Gill Sans (sans serif) • Times New Roman (serif) • Use graphs or charts, not tables • Keep slides simple • Limit animations and special effects • Use high contrast text and backgrounds

12. Choosing a Title • A title should express • Who • What • When • Where

13. Tables: Frequency distribution

14. Tables: Relative frequency Percent contribution of reported malaria cases by year between 2000 and 2007, Kenya Source: WHO, World Malaria Report 2009

15. Use the right type of graphic • Charts and graphs • Bar chart: comparisons, categories of data • Histogram: represents relative frequency of continuous data • Line graph: display trends over time, continuous data (ex. cases per month) • Pie chart: show percentages or proportional share

16. Bar chart

17. Bar Chart Source: Quarterly Country Summaries, 2008

18. Stacked bar chart % Children <5 with Fever who Took Specific Antimalarial, 2007-2008

19. Histogram

20. Bar Chart v. Histogram Data fabricated for illustration

21. Bar Chart v. Histogram (cont.) Data fabricated for illustration

22. Population Pyramid: Country Z, 2008

23. Line graph Number of Clinicians* Working in Each Clinic During Years 1-4, Country Y *Includes doctors and nurses.

24. Caution: Line Graph Number of Clinicians* Working in Each Clinic During Years 1-4, Country Y *Includes doctors and nurses.

25. Pie chart

26. Pie chart Percentage of all confirmed malaria cases treated by quarter, Country X, 2011 N=257

27. How should you present… • Prevalence of malaria in 3 countries over a 30 year period? • Data comparing prevalence of malaria in 10 different countries? • Data on reasons why individuals not using ITNs (out of all individuals surveyed who own an ITN and are not using it)? • Distribution of patients tested for malaria by parasite density

28. Summary • Make sure that you present your data in a consistent format • Use the right graph for the right data and the right audience • Label the components of your graphic (title, axis) • Indicate source of data and number of observations (n=xx) • Add footnote for more explanation

29. Creating Graphs

30. Learning objectives • Understand basic chart terminology • Create charts in PowerPoint using data in Excel • Give a description of the data presented in each chart

31. Pie Chart Source: MEASURE Evaluation, Retention, Use and Achievement of “Universal Access” Following the Distribution of Long Lasting Insecticide Treated Nets in Kano State, Nigeria, 2009

32. Individual Work: Bar Chart Source: Tanzania HIV and Malaria Indicator Survey, 2008

33. Secondary Axis

34. Data Interpretation

35. Analysis vs. Interpretation • Analysis: describing data with tables, graphs, or narrative; transforming data into information • Interpretation: adding meaning to information by making connections and comparisons and by exploring causes and consequences

36. Has the Program Met its Goal?

37. Interpreting Data • Does the indicator meet the target? • What is the programmatic relevance of the finding? • What are the potential reasons for the finding? • How does it compare? (trends, group differences) • What other data should be reviewed to understand the finding (triangulation)? • Conduct further analysis

38. Practical • Question: • Are ANC clinics in country X reaching their coverage targets for IPTp? • Data Source: • Routine health information

39. Data Source General ANC Registers • Which of these variables are relevant to answer your question? • Which elements will be included in your numerator and which in your denominator? • Answers: • 1) New ANC clients, IPTp-1 • 2) New ANC clients =Denominator, • IPTp-1 and IPTp-2= Numerator

40. IPTp Coverage-Facility Performance Number of ANC clients receiving IPTp • Question: • Among the five facilities, which one performed better? • Answer: • Cannot tell because we don’t know the denominators

41. IPTp Coverage-Facility Performance Number of ANC clients receiving IPTp Question: Now, you have the denominators, which of these facility performed better? Response: Facility 5

42. Are facilities reaching coverage targets? Target-80% * National coverage target for pregnant women receiving IPTp-2 is 80%.

43. Additional Questions • Which facility is performing better/worse than expected? • What is the trend over time for these facilities? • How would you assess each facility’s performance based on the data? • What other data or information should you consider in providing recommendations or guidance to the facilities?

44. Data Dissemination

45. Learning Objectives By the end of this session, participants will be able to identify: • The purpose of dissemination • Dissemination issues and concerns • Strengths and weaknesses of different communication formats • The main components of a dissemination plan

46. Dissemination Framework Source: MEASURE DHS

47. Purpose of Dissemination • Disseminating data can help potential users: • Understand current health status • Reach decisions based on quality data • Make changes to existing health programs and policies • Take other actions to improve health outcomes

48. Plan Materials Carefully • Use different formats if possible, including: • Print materials • HIS Reports, Success story, Posters, Key findings, Fact Sheet, Press Report • PowerPoint presentations • CD-ROMS with datasets • Videos • Online media

49. Focus on a Specific Audience • Create different materials for different users: • Meet the audience’s needs • Translate materials into local languages • Produce reports on specific topics • Impact • LLINs • Case Management • IPTp • Match the medium to the audience

50. Make Sense of the Data • Help users make sense of the data: • Add policy recommendations and conclusions • Highlight key points • Break down findings by categories of interest • Province • Education • Wealth • Use maps and graphics to convey information