1. Using Information for Health Management; Part II - Health Information Systems Strengthening

2. 3 Learning objectives –the information cycle; tools and processes for turning data into action –the relationship between data use and data quality –hierarchy of standards / essential data set –common reasons for compromised data quality, and various counter measures –different information products for communicating different meanings

3. Information cycle; from data to action 4 CollectionProcessingPresentationAction

4. Presentation What do you want to communicate? Different information products for different data & meanings 5 CollectionProcessingPresentationAction

5. Preparing for Presentation essential prerequisites Correct Complete  submission by all (most) reporting facilities / units Consistent  data within normal ranges  clear definitions / standards  Timely CollectionProcessingPresentationAction

6. 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) CollectionProcessingPresentationAction

7. Beware information overload: easy to produce – difficult to use Ideally should contain: Few rows Few categories/columns Uses: assess quality trends over time make comparisons pick up outliers, gaps Tables CollectionProcessingPresentationAction

8. A nice table 9 Number of children per family in Maputo, 2005 Source: Statistics & Planning Directorate, 2005 CollectionProcessingPresentationAction

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

10. Graph Elements X Y 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 Scale – must be appropriate Source:Notes: CollectionProcessingPresentationAction

11. Five rules for graphs 1.Never put too much information in the graph. KEEP IT SIMPLE 2.Be careful about mixing different activities: stick to one group of people, diseases or service 3.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 4.Select scales that fit the entire graph on both axes 5.Where possible, draw a target line or reference point to show where you are aiming at CollectionProcessingPresentationAction

12. Type of graphs Continuous data –histograms –line graphs –scatter graphs Discrete Data –bar graphs –pie charts CollectionProcessingPresentationAction

13. Line graph  accurate, can show changes in the relationships between two variables  displays trends over time  useful if more than one data item is used PHC headcount under 5 years old, Manyara Clinic, 2001 CollectionProcessingPresentationAction

14. Bar graph versus Line graph which one is best? CollectionProcessingPresentationAction

15. Line graph, with two dependent variables CollectionProcessingPresentationAction

16. Line graph, for cumulative coverage CollectionProcessingPresentationAction

17. 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 CollectionProcessingPresentationAction

18. Pie chart good to show relative proportions 19 Only for data that adds up to a total (100%) CollectionProcessingPresentationAction

19. Bar graph, simple displays data over time or can compare 2 or more different facilities / districts / regions / years CollectionProcessingPresentationAction

20. Bar graph, stacked 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 CollectionProcessingPresentationAction

21. Population pyramids highlight the differences in age distribution between males and females as well as proportional age categories CollectionProcessingPresentationAction

22. 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! CollectionProcessingPresentationAction

23. BAD GRAPHS! CollectionProcessingPresentationAction

24. CollectionProcessingPresentationAction

25. …gone fishing… CollectionProcessingPresentationAction

27. GapMinder some inspiration… CollectionProcessingPresentationAction Hans Rosling's 200 Countries, 200 Years, 4 Minutes

28. Action Interpreting the information –Take into account data quality bias Plan action and interventions –Prioritze resources –Set well-defined targets –How is the action going to be evaluated? 29 CollectionProcessingPresentationAction

29. Interpret information to find causes 30 Low PHU Deliveries TBAs holding on clients Low community sensitization High fees for deliveries Staff attitude Can’t afford fees Men not involved No proper orientation Low educational level Staff shortage Staff not motivated Problem with sharing of fees Cultural beliefs Family trust in the TBAs Community norms Bye laws not instituted Patients refusal to go to PHU Long distance Irregular supervision Difficult terrain Can’t afford travel CollectionProcessingPresentationAction

30. Data quality bias? 1 st Dose VS Population <1yr CollectionProcessingPresentationAction

31. Correlating two data sources 32 CollectionProcessingPresentationAction

32. Take action: Underweight children Public campaign: ”You must weigh your child every month to make sure it grows properly” 33 CollectionProcessingPresentationAction

33. 34 state exactly what has to be achieved, by whom and by when a realistic point at which to aim to reach a goal turning organizational goals into operational numbers Targets CollectionProcessingPresentationAction

34. Example Targets CollectionProcessingPresentationAction

35. 36 Targets should be SMART Specific capturing changes in situation concerned Measurable able to be easily quantified Appropriate fit to local needs, capacities and culture Realistic can be reached with available resources Time bound to be achieved by a certain time CollectionProcessingPresentationAction

36. Summary -Data quality is an issue at all steps of the information cycle -The best way to improve data quality is to use the data -Indicators (rates, ratios) are much more useful than raw data -Indicatros can be compared across time and space -Different information products serve different needs -Targets should be set for all action 37 CollectionProcessingPresentationAction