1. Putting Data to Work Evidence-based health programming and management Sustainable Management Development Program

2. Learning Objectives Describe how data are used in health organizations and programs Identify methods for summarizing data Explain how data analysis and interpretation can improve decisions Prepare and apply tables, graphs, and charts such as line graphs, bar charts, pie charts, and spot (dot) maps

3. How do you use data? Simple vs. complicated decisions Decisions can significantly impact a community Use of timely & accurate data analysis

4. Scenario Imagine that you are a medical superintendent of a district hospital and part of your job is to manage resources. Each month your employees submit a receipt for their fuel usage. Instead of just approving the bills, you can study the data they provide. Collecting and analyzing these simple data will allow you to better track and understand trends in fuel usage. Consider the following graph.

5. Exercise 1: Is there a problem?

6. Why use data? Data provides evidence and guidance for successful programming and resource management Collecting data is only one step Accurate data analysis, interpretation and application is also an important step As the medical director of this hospital, what else would you want to keep track of besides fuel usage?

7. Kinds of Data Individual - focus on one person’s health issues, e.g. patient’s medical record Population - focus on communities, districts, etc.,to obtain an overall picture of health Management- focus on tracking, monitoring and evaluating the use and distribution of resources

8. Types of Data Quantitative ◦ Who ◦ What ◦ When ◦ Where Qualitative ◦ Why ◦ How Can you think of data that crosses your path? What data are available to you?

9. Data Collection- Counts Actual number of events (in a specific population, place and time) Used for: ◦ Program planning and monitoring: Describe the magnitude of the problem Limitations ◦ No indication of problem in relation to size of population ◦ No information on risks

10. Exercise 2: Using a check sheet

12. Interpreting Data Most commonly used measures of frequency ◦ Counts ◦ Ratios 1:2 ◦ Proportions 1/2 ◦ Percents 15 % ◦ Rates 33.3 per 100,000

13. Ratios A ratio is a comparison of two dissimilar things 8:16 or 1:2

14. Two types of ratios: Proportion and Percents A proportion or a percentage = special kind of ratio ◦ A part is compared to the whole ◦ Multiply by 100, 1,000 or 100,000 ◦ Proportions and percentages are essentially the same measure 8 54 = 0.15 Proportion: 15 per 100 Percent: 15%

15. Percents Standardize data and make comparable Remember to report numbers or counts to put the percentage in context Clinic % pregnant women whose partner gets tested # of pregnant women whose partner gets tested A50%3 out of 6 B21%38 out of 181 C17%121 out of 712

16. Rates Rate: often a proportion, with an added dimension of time Measures the frequency at which a health event occurs over a period of time

17. Risk and Persons at Risk Risk = the probability or likelihood that an event will occur All people to whom the event could have happened Everyone in the geographic area during the time period of interest Rates compare the risk of health events across different groups of people, places, and time periods

18. Rates K = A standard unit of the population (per100, 1,000, or 100,000) Remember both numerator and denominator must represent the same time and place Number of persons experiencing the event Number of persons “at risk” of experiencing the event over a specified time period x K

19. Rates Example K = 100,000 Cases Total population # cases Total pop. Rate 20 ÷ 1,000 0.02 2,000 per 100,000 20 ÷ 1,000,000 0.00002 2 per 100,000

20. Rates Exercise What is the mortality rate from HIV/AIDS per 100,000 women in Panama? What is the mortality rate from HIV/AIDS per 100,000 women in Guatemala? Based on the rates we have calculated which country has a higher rate of women dying from the disease? Which country has the higher number of women dying from HIV/AIDS? CountryHIV/AIDS Deaths Female Population Panama1141,573,289 Guatemala1676,342,703

21. Why Use Rates? Describe the frequency of a health event or health status relative to the size of a population To target interventions To manage resources ◦ Employee turnover rate ◦ Vaccination coverage rate ◦ Hospital admissions

22. Exercise 3: Calculate Ratios and Rates Use the counts from the check sheet on page 7 to answer the questions below. 1. What is the ratio of total missed appointments between Clinic C and Clinic D? 2. What is the proportion of missed appointments in Week 5 for Clinic E? 3. What is the rate of missed appointments over the 7 week period?

23. Summarizing Data To analyze data To explore patterns and trends, and identify variations from trends To provide a useful way of communicating information to others

24. Basic Methods for Organizing and Presenting Data Data can be organized through creation of: ◦ Tables ◦ Graphs ◦ Charts ◦ Maps

25. Tables DeceasedLivingTotal Diabetics 10089189 Non diabetics 8112,3403,151 Total 9112,4293,340 Follow-up status of a group of men with and without diabetes, Medical examination survey follow-up study, 2005-2010 Clear, concise labels Totals to accompany rows Quantitative data Column (vertical) Row (horizontal) Totals to accompany columns Footnote: Used to explain codes, abbreviations, symbols, exclusions or data sources used.

26. Continuous vs. Discrete Data Continuous data can be assigned an infinite number of values between whole numbers - weight, height, time Discrete data is data that can be counted. - gender, race

27. Graphs Y-axis Frequency measure A set of coordinates (i.e. year, # of cases) make up a data point Method of classification X-axis

28. Creating Line Graphs Show patterns or trends over some variable, usually time Good for comparing 2 or more sets of data Example: ◦ Number of staff members hired to worked at district health facilities from 1975 to 2010

29. Tip 1 Mark off each axis at equal intervals Y-axis X-axis (vertical) (horizontal)

30. Tip 2 Match x-axis scale to intervals used during data collection Time period shown on X-axis 19751980198519901995200020052010 YEAR

31. 19751980198519901995200020052010 Tip 3 Make the x-axis longer than the y-axis Always start y-axis with 0 X-axis longer than Y-axis YEAR 0 cases

32. 19751980198519901995200020052010 Tip 4 Select interval size for y-axis that will provide enough intervals to illustrate data in adequate detail Determine range of values on y-axis by identifying the largest value Number of staff members shown on Y-axis Time period shown on X-axis YEAR 9000 S TAFF M EMBERS 8000 7000 6000 5000 4000 3000 2000 1000

33. Completed Line Graph

34. Bar Charts Method of organizing and illustrating data using only one coordinate Quick way to show big differences in data Bar charts are used to compare data and show relationships Best used for comparing data with discrete categories ◦ Gender, race, marital status and trained and untrained

35. Example: Horizontal Bar Chart Example: Horizontal Bar Chart

36. Creating a Simple Bar Chart Bar Characteristics: ◦ May be horizontal or vertical ◦ Bars are all equal width and are separated ◦ Each bar represents one value of the variable ◦ Length or height of each bar is proportional to frequency of the event in that category

37. Example: Vertical Bar Chart

38. Exercise 4: which method for displaying data would you use? Sub districtsNumber of trips Dodowa5 Prampram 3 Osudoku 2 Ningo 1 Number of Mobile Clinic Trips 0 1 2 3 4 5 6 DodowaPrampramOsudokuNingo Sub-districts Number of trips

39. Pie Charts Pie charts show how part of something relates to the whole. A circle with slices that represent percentages of the different categories of the variable. Pie charts are a way to effectively present percentages in which the “slices” of the pie add up to 100%.

40. Pie Chart

41. Maps A visual display of geographical or spatial patterns Powerful tool for looking at clusters of disease or events Can be used for management purposes Types include ◦ Spot or dot maps ◦ Area maps ◦ Geographic information systems

42. Creating a Spot Map Use dots or other symbols to show geographic distribution of an event or a disease/condition Famous spot map- John Snow tracking cholera deaths in London Spot maps can be used to track operations information

43. Example: Spot Map DO NOT take into account size of population at risk

44. Example: Dot Maps Key: Dengue fever - Malaria - Chagas - Source: http://www.worldmapsonline.com/images/OutlineMaps/Guatemala.jpghttp://www.worldmapsonline.com/images/OutlineMaps/Guatemala.jpg

45. Example: Area Map Countries at risk of yellow fever and countries that have reported at least one outbreak of yellow fever, 1985-1999 http://www.who.int/csr/resources/publications/yellowfev/CSR_ISR_2000_1/en/

46. Stratification Breakdown results into smaller groups ◦ Age ◦ Gender ◦ Place ◦ Time ◦ Geographic location

47. Stratification

48. Stratification

49. Summary The purpose of organizing and presenting data is to analyze it, to explore patterns and trends, and to communicate information to others. Data can be organized through the creation of tables, graphs, charts, and maps. Tables can illustrate the number of people who share a certain

50. Summary Line graphs are useful for showing patterns or trends over some variable, usually time. Bar charts are used to display countable or discrete data, such as race or gender, and make it easy to see differences among the categories. Pie charts are useful for showing the component parts of a single group or variable.

51. Summary Maps are an excellent way to display geographic information, and make it easier to identify geographical patterns in data. Spot (dot) maps use dots or other symbols to show geographic distribution of an event or a disease/condition.

52. Exercise 5: Summarizing Data What method would you use?

53. Conclusion Know how to read, understand and interpret data These processes can help with decision making for health programming and management Frequent data analysis helps to detect problems Data can be organized through tables, graphs, charts, and maps.

54. What’s next? Think about how data can help you make stronger management and public health policy decisions Practice data analysis and presentation and share your reports with colleagues.