Basic Epidemiology for Community Health Assessment

1. Basic Epidemiology for Community Health Assessment Nelson Adekoya, DrPH Centers for Disease Control and Prevention

2. Outline Definitions Fundamentals of Epidemiology Data Death Certificate Determine the Leading Causes of Death Data Presentation Tips Questions & Self Quiz 2

3. Define Health • Define Public Health • Define Epidemiology • What are the goals of Public Health? 3

4. Public health is the science of preventing diseases, prolonging life, and promoting health thru organized community effort 4

5. Goals of Public Health? • Prevent or control disease, disability and injury • Improve quality of life for residents of state or community 5

6. Define Epidemiology (write down your definition, check against definition in Part 2) 6

7. Part I Epidemiology and Data are inseparable. So, why do we need data? ..…write down your answers 7

8. Why are Data Needed? • to determine major health problems (needs assessment, program development) • to identify where to focus efforts and resources (asset mapping) • to determine progress in solving health problems (measuring health indicators, outcomes, or Healthy People Objectives) • to conduct research and grant applications 8

9. Succinctly, data are needed ► to assess the health of a community or population; ► to search for causes of disease, injury and disability; ► to plan programs to meet community needs; and ► to measure progress in prevention and control efforts. 9

10. According to the National Center of Vital Health Statistics: Data is required for “a process that involves the community in identifying problems, setting priorities, developing an action plan, measuring progress, deciding whether the actions are effective, modifying the actions if necessary, and reevaluating the community's problems and priorities”. 10

11. Types of Data Needed • Depend on: • What is the program of interest? • What is the focus of the program? • What is the purpose of the program? 11

12. Primary data(data collected directly by the organization). • Secondary data (data collected by someone outside their own program or agency, to measure the outcomes of interest). 12

13. Locating and Accessing Secondary Data • Online Secondary Data access available by such links from the New Hampshire Health Data Inventory (HDI) at www.nhhealthdata.org • Some web sites provide data tables that can be used to perform calculations or create charts. • Other web sites allow users to obtain raw data files, which can be used to create aggregate tables, generate statistics, and perform calculations. 13

14. Web Sites for Secondary Data Sources • CDC WONDER (http://wonder.cdc.gov/) has access to a variety of public health information, including links to environmental and disease-specific data. • CDC WISQARS™ (http://www.cdc.gov/ncipc/wisqars/default.htm): “WISQARSTM (Web-based Injury Statistics Query and Reporting System) is an interactive database system that provides customized reports of injury-related data.” • US Census (www.census.gov) makes some of its data about the US population available for download. 14

15. What is NM website address to access health data? 15

16. Importance of Data Quality • Relevance • Accuracy • Timeliness • Accessibility • Interpretability • Coherence 16

17. Relevance • The relevance of statistical information reflects the degree to which it meets the real needs of clients. 17

18. Accuracy • The accuracy of statistical information is the degree to which the information correctly describes the phenomena it was designed to measure. • It may also be described in terms of the major sources of error that potentially cause inaccuracy (e.g., coverage, sampling, non-response, response). 18

19. Timeliness • The timeliness of statistical information refers to the delay between the reference point (or the end of the reference period) to which the information pertains, and the date on which the information becomes available. 19

20. Accessibility • The accessibility of statistical information refers to the ease with which it can be obtained from the Agency. 20

21. Interpretability • The interpretability of statistical information reflects the availability of the supplementary information and metadata necessary to interpret and use it appropriately. This information normally includes the methodology of data collection and processing, and indications or measures of the accuracy of the statistical information. 21

22. Coherence • The coherence of statistical information reflects the degree to which it can be successfully brought together with other statistical information within a broad analytic framework and over time. 22

23. Other aspects of data quality to consider • Able to drive decision-making and behavior • Can the outcome be monitored over time? 23

24. Part I1 Fundamentals of Epidemiology 24

25. Definition of Epidemiology • The study of the distribution and determinants of health-related states or events in specified populations in a specified time period, and the application of findings to control of health problems. 25

26. Purpose of Epidemiology ► To provide a basis for developing disease control and prevention measures for groups at risk. 26

27. Descriptive Epidemiology •  Examine the distribution of disease in a population • and observe the basic features of its distribution. • Answer questions about what, who, when and where people get ill, injured, or disabled. 27

28. Analytic Epidemiology •  Test a hypothesis about the cause of disease by • studying how exposures relate to the disease. • Answer questions about how and why people get ill, injured, or disabled. 28

29. Uses of Epidemiology  Determine the primary agent or causative factors  Determine the characteristics of the agent  Define the mode of transmission, and contributing factors  Identify geographic patterns  Describe the natural course of disease, disability, injury and death •  Help planning and developing health services and programs •  Provide administrative and planning data 29

30. Epidemiologists look For…… ◈ Person ◈ Time ◈ Place • To answer questions about what, who, when and where, how and why people get ill, injured, or disabled. 30

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32. Place Geographic place Urban, suburban, rural Climate Geology Population density Economic development Cultural norm Medical practice Nutritional practices 32

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37. DATA Part III 38

38. ►Quantitative Data ►Qualitative Data 39

39. Quantitative Health DATA can focus on: • individuals, or • entire populations. 40

40. Population-based Data versus Individualized Data ►Example of individualized data is a patient’s medical record. ►Each record is devoted exclusively to one person and contains information about his or her unique illnesses, injuries, behaviors, etc. ►The data are used primarily to improve the health of that one individual. 41

41. Population-based Data versus Individualized Data (cont) ►In public health, our focus is primarily on populations (e.g. communities, cities, counties, states). ►Population-based data tells us about the overall “health” of that population. 42

42. Major Types of Health Data available for analysis  Health outcome / Health Status Data  Risk factor Data  Resource Data  Demographic Data 43

43. Quantitative DATA ► Measurable and tangible; ► Provides answer regarding what, who, when, and where of health-related events. 44

44. Simply, what we are doing in Quantitative DATA are: ► Counting of people, behaviors, conditions, or other discrete events; ► Classifying those events into categories; ► Using math and statistics to answer questions. 45

45. Quantitative DATA Examples (cont) ►Using numbers of deaths to identify leading causes of death (What); ►Using numbers of smokers and nonsmokers by gender to determine whether men are more likely to smoke than women (Who); ►Keeping track of the number of people with flu can identify the beginning of the flu season (When); 46

46. Quantitative DATA Example (cont) ►Comparing the proportion of women who began prenatal care after the first trimester in various counties will provide an indication of where access to prenatal services may be a problem. 47

47. Qualitative DATA ►Qualitative data can be used to explain the whyand the howof health-related events. ►Qualitative data involve observing people in selected places and listening to discover how they feel and whythey might feel that way. 47

48. Examples of Qualitative DATA ► A focus group of teenage girls could provide valuable insights concerning why they do or don’t use contraceptives. ► A visit to a local clinic might indicate how people might feel as they enter the waiting area. 48

49. What Analysis to Request for Quantitative Data? • Measures of central tendency: ● Mean is the arithmetic average of the values in the data ● Median is the middle value ● Mode is the most commonly occurring value 49

50. Any Questions??? 50