Measuring Injury Using the National Health Interview Survey

1. Measuring Injury Using the National Health Interview Survey Margaret Warner, PhD Lois A. Fingerhut, MA Pat Barnes, MA

2. Location of injury and poisoning data • Injury Episode file • Injury Verbatim file • Poison Episode file • Person file

3. Injury episode file • For each person: • Up to 4 injury episodes • For each episode: • Up to 4 ICD-9-CM diagnosis codes • Up to 3 ICD-9-CM external cause codes

4. Available data in the Injury Episode file • External cause (ICD-9-CM) • Injury diagnoses (ICD-9-CM) • Place of occurrence • Activity • Resulting limitations • Detail on certain causes (e.g. mv crashes, falls)

5. Injury episode file ICD-9-CM diagnosis codes and E-codes are based on information supplied by respondents, not medically trained personnel.

6. Poisoning episode file • Contains no ICD-9-CM codes or E-codes • Contains 47 episodes coded as “Allergic/adverse reaction to medical or other substance” or “Something else – not poisoning”

7. Available data in the Poisoning Episode file • Cause of poisoning • Call to poison control center

8. Available data in both injury and poisoning files • Date of episode • Hospitalization • Days out of school • Days out of work • Time elapsed between episode and interview

9. Injury section–Person file • Contains summary information about injury and poisoning episodes • Annual estimates can only be made on variables INJCT and POICT

10. How do I put the data together?

11. Injury and poisoning episode, and injury verbatim files • Contain only injury or poisoning information and unique identifiers • Must be linked to the person file to obtain sociodemographic variables, design variables, etc.

12. Episode and person based files Episode based: A person will appear in these files as many times as he/she has a unique episodes Person based: A person will appear in this file only once

13. Concatenating injury and poisoning episode files + Injury Poisoning Injury Poisoning = Missing data, questions not found in both files

14. Merging injury/poisoning episode file and person file + Injury Person Poisoning = Missing data, questions not found in both files

15. Merged injury/poisoning episode file and person file Injury Poisoning Person = Missing data, questions not found in both files

16. Episodes and Conditions • Episode = Event that caused the condition (e.g. fall down stairs) • Conditions = physical harm resulting from the injury episode (e.g. broken leg, bruised arm)

17. Creating condition filesInjury Injury Episode with ICD9_1 ICD9_2 ICD9_3 ICD9_4 ICD9_1 ICD9_2 ICD9_3 ICD9_4

18. Creating condition filesPoisoning Poisoning episode Poisoning condition =

19. Concatenating injury and poisoning condition files + Injury conditions Poisoning Injury conditions Poisoning conditions = Missing data, questions not found in both files

20. What Can I Do With the Data?

21. Handout • Using SAS to manipulate the injury and poisoning data • Example SAS programs for concatenating and merging the files

22. Analyzing the injury and poisoning data • Estimates of frequency • Percent distributions • Rates • Standard errors

23. Calculating annual estimates • Annual est = (variable)(4)(WTFA) • Annual estimates of episodes and conditions can be calculated. • Annual estimates of the number of persons injured cannot be calculated due to the 3 month reference period.

24. Standard Errors (SE) • SE of the injury/poisoning rate for males and females • SE of the injury/poisoning rate for specified racial groups

25. Estimates of frequencyExamples • Number of episodes resulting from specific causes • Number of injury/poisoning episodes by sex • Number of injury/poisoning episodes by mechanism

26. Results

27. RatesExamples • Annual injury/poisoning rates for males and females • Annual injury/poisoning rates by mechanism • Annual rate of falls for females over 65 years of age

28. Injury and poisoning episode rates Age in years 95% CI Episodes per 1,000 population

29. Episodes per 1,000 persons Age adjusted injury episode rates by mechanism of injury

30. Age adjusted condition rates by type of injury, 1997

31. PercentagesExamples • Percent of episodes resulting from specific causes • Percent of poisoning episodes in which a poison control center was called • Percent of injury episodes that occurred in the home

32. Percent of injury episodes by place of injury, 1997 Percent of episodes Persons could indicate up to two places per episode.

33. Work-related injuries • Injury episode file: • Activity at the time of injury= • Working at a paid job • Sample person file: • Occupation and industry

34. Percent of injury episodes by activity, 1997 Percent of episodes Persons could indicate up to two places per episode.

35. Injury verbatim file • Responses recorded by the interviewer: • How the injury occurred • Body part injured • Nature of injury • Text file linkable to other files

36. Available data in injury verbatim • How the injury occurred (up to 336 characters) • Up to 4 body parts injured (up to 34 characters each) • Up to 4 nature of injuries (up to 44 characters each)

37. Injury verbatim file • Edited only for confidentiality • Grammatical and/or spelling errors were not corrected

38. Uses of injury verbatim • NCHS used to code ICD-9-CM diagnoses and external causes • Code according to other classification schemes (e.g. BLS, ICECI, etc) • Text search for words of interest • In-depth analysis of ICD-9-CM categories

39. Check sample size Analysts should be cautioned against making estimates based on small numbers of observations.

40. Cause of injury: . Part of body: Type of injury: “While <in-line skating>, fell on thumb.” “Right thumb” “Broken” Verbatim textExample

41. Examples of verbatimMachinery related injuries (E919) • “He was at home working on his table saw and accidentally ran his left thumb through the machine lengthwise.” (table saw, n=8) • “Forklift extension came loose dropping on right foot at work” (forklift, n=3)

42. Contact for questions related to injury data or injury classification issues:MWarner@cdc.gov