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Module 4: Data presentation & interpretation

Module 4: Data presentation & interpretation. Module 4: Learning objectives. Understand different ways to best summarize data Choose the right table/graph for the right data Interpret data to consider the programmatic relevance. Summarizing data. Tables Simplest way to summarize data

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Module 4: Data presentation & interpretation

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  1. Module 4: Data presentation & interpretation

  2. Module 4: Learning objectives • Understand different ways to best summarize data • Choose the right table/graph for the right data • Interpret data to consider the programmatic relevance

  3. Summarizing data • Tables • Simplest way to summarize data • Data are presented as absolute numbers or percentages • Charts and graphs • Visual representation of data • Data are presented as absolute numbers or percentages

  4. Basic guidance when summarizing data • 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

  5. Tables: Frequency distribution Set of categories with numerical counts Number of Births in Ouallam, Niger, 1900–1902 Data source: Pagano, M. Vital Events Survey in Northern Niger. Studies in Demographics, 1993. Vol. 27, pp. 32–37.

  6. Tables: Relative frequency number of values within an interval total number of values in the table x 100

  7. Tables Percentage of births by decade between 1900 and 1929 Source: U.S. Census data; 1900-1929.

  8. Charts and graphs • Charts and graphs are used to portray: • Trends, relationships, and comparisons • The most informative are simple and self-explanatory

  9. Use the right type of graphic • Charts and graphs • Bar charts: comparisons, categories of data • Line graphs: display trends over time • Pie charts: show percentages or proportional share

  10. Bar chartComparing categories

  11. Percentage of new enrollees tested for HIV at each site, by quarter Q1 Jan-Mar Q2 Apr-June Q3 July-Sept Q4 Oct-Dec Data Source: Program records, AIDSRelief, January 2009 – December 2009.rce: Quarterly Country Summary: Nigeria, 2008

  12. Has the program met its goal? Percentage of new enrollees tested for HIV at each site, by quarter Target Data Source - Program records, AIDS Relief January 2009 – December 2009rce: Quarterly Country Summary: Nigeria, 2008

  13. Stacked bar chartRepresents components of whole & compares wholes Number of Months Female and Male Patients Have Been Enrolled in HIV Care, by Age Group Number of months patients have been enrolled in HIV care Data source: AIDSRelief program records January 2009 - 20011

  14. Line graph Displays trends over time Number of Clinicians Working in Each Clinic During Years 1–4* *Includes doctors and nurses

  15. Line graph Number of Clinicians Working in Each Clinic During Years 1–4* Y4 1998 Y1 1995 Y2 1996 Y3 1997 Zambia Service Provision Assessment, 2007. *Includes doctors and nurses

  16. Pie chartContribution to the total = 100% N=150

  17. Interpreting data

  18. Interpreting data • Adding meaning to information by making connections and comparisons and by exploring causes and consequences

  19. Interpretation – relevance of finding • Adding meaning to information by making connections and comparisons and by exploring causes and consequences

  20. Interpretation – relevance of finding • Does the indicator meet the target? • How far from the target is it? • How does it compare (to other time periods, other facilities)? • Are there any extreme highs and lows in the data?

  21. Interpretation – Possible causes? • Supplement with expert opinion • Others with knowledge of the program or target population

  22. Interpretation – Consider other data • Use routine service data to clarify questions • Calculate nurse-to-client ratio, review commodities data against client load, etc. • Use other data sources

  23. Interpretation – Other data sources • Situation analyses • Demographic and health surveys • Surveillance data • Performance improvement data

  24. Interpretation – conduct further research • Data gap conduct further research • Methodology depends on questions being asked and resources available

  25. Key messages • Use the right graph for the right data • Tables – can display a large amount of data • Graphs/charts – visual, easier to detect patterns • Label the components of your graphic • Interpretingdata adds meaning by making connections and comparisons to program • Service data are good at tracking progress & identifying concerns – do not show causality

  26. Group Work 2: Calculating coverage and efficiency

  27. Learning objectives • Use basic statistics to measure coverage and efficiency • Develop graphs that display performance measures (utilization, trends) • Interpret performance measures for programmatic decision making

  28. Small group activity • Form groups of 4–6 • Each group reviews 2 worksheets from Excel file and answers the questions (1 hour 45 min) • Each group presents 2 findings from each worksheet, focusing on the programmatic relevance of the findings (10 min per group) • Audience provides feedback on analysis and interpretation (notes errors, additional interpretations) (10 min per group)

  29. Group Work 2: Report back • Each group will have 10 minutes to present its completed Framework • Group discussion – Are there other data sources that might have been used in this decision? Were there other stakeholders that should have been considered? (10 min)

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