1. 1 Data analysis

2. 2 Turning data into information

3. How do we process it? How do we present it? How do we use it? Reliable Information Information Cycle What do we collect?  Stages  Tools  Outputs data sources & tools Timely Quality data Data quality checks, Data analysis Information

4. 4 Data analysis what, why and how? turns raw data into useful information is the process of producing indicators – most important step in data analysis requires timely quality data – remember the 3 C’s

5. 5 Data analysis what, why and how? the improvement of coverage and quality of local health services - is facilitated by only collecting data that can be analyzed and used at the local level  allows comparisons  self assessment ( have I reached my target ? )  supports decision-making

6. 6 Data analysis what, why and how? calculate indicators use basic epidemiological concepts

7. 7 Indicators  measures of COVERAGE and QUALITY  variables used to measure CHANGE  monitor progress towards defined targets  describe situations  measure trends over time (temporal)  provide a yardstick whereby facilities / teams can compare themselves to others (spatial, organizational)

8. 8 Indicator calculation types

9. – Example: Maternal mortality rate – How is it defined? Millenium development goals have a set of proposed indicatorsindicators denominator indicator = numerator X 100 = %

10. 10 Atop the line – numerators (activities / interventions / events / observations / people) a count of the event being measured  How many occurrences are there: morbidity (health problem, disease) mortality (death) resources (manpower, funds, materials)  Generally raw data (numbers)

11. 11 (population at risk) Under the line - denominators (population at risk) size of target population at risk of the event What group do they belong to:  general population (total, catchment, target)  gender population (male / female)  age group population ( 18, 15-44 )  cases / events – per (live births, TB case)

12. 12 An ideal indicator RAVES !!!  

13. 13 Indicators RAVES RELIABLE gives the same result if used by different people APPROPRIATE fits with context, capacity, culture and the required decisions VALID truly measures what you want to measure EASY feasible to collect the data SENSITIVE immediately reflects changes in events being measured

14. Essential indicators: determines the essential data set at each level

15. Indicator Operationalization Defining the sources of the data – both numerator & denominator (how is it to be collected?) Determining the frequency of collection and processing of the indicator (How often should it be collected, reported, analyzed?) Determining appropriate levels of aggregation (To where should it be reported and analyzed/broken down?) Setting levels of thresholds and target What will be the nature of the action (decision) once the indicator reaches the threshold?

16. 16 Epidemiological questions

17. 17

18. 18 Epidemiology : who, where, when?

19. 19 Epidemiology: what, why and how? WHAT ? study of the distribution, frequency and determinants of health problems and disease in human populations WHY ? obtain, interpret and use health information to promote health and reduce disease HOW ? uses indicators to answer basic epidemiological questions

20. How do we process it? How do we present it? How do we use it? Reliable Information Information Cycle What do we collect?  Stages  Tools  Outputs data sources & tools Timely Quality data Data quality checks, Data analysis Information

21. Having a plan Operationalization of organizational goals Settings targets

22. 22 Targets state exactly what has to be achieved, by whom and by when a realistic point at which to aim to reach a goal turning the organizational goal into numbers

23. 23 Targets should be SMART S PECIFIC measurable based on changes in situation concerned M EASURABLE able to be easily quantified A PPROPRIATE fit in to local needs, capacities and culture R EALISTIC can be reached with available resources T IME BOUND to be achieved by a certain time

24. Example Targets

25. Chiefdom/ Facility league table Immunization Deliveries Antenatal Malaria Data Quality Nutrition