The ICD-10 injury diagnosis matrix: Grouping S and T codes by body region and nature of injury |
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1 | The ICD-10 injury diagnosis matrix: | 10 | effects. |
Grouping S and T codes by body region and | 11 | Top 10 Injury Diagnosis Categories as | |
nature of injury. Paul R. Jones and Bruce | a function of Nature of Injury and Body | ||
A. Lawrence Pacific Institute for Research | Region. 9.1. | ||
and Evaluation Lois A. Fingerhut National | 12 | Incidence of Most Common Fatal Injury | |
Center for Health Statistics November, | Diagnoses by Age and Sex. . 1. 2. 3. 4. | ||
2004. | 5. 6. 7. 8. 9. 10. 11. 12. . 50 or | ||
2 | Background. ICD-10, like its | younger. 50 or younger. 50 or younger. | |
predecessor ICD-9, contains so many | Older than 50. Older than 50. Older than | ||
detailed codes that it is often difficult | 50. All ages. All ages. All ages. . | ||
to see the forest for the trees. | Female. Male. Total. Female. Male. Total. | ||
Researchers, epidemiologists, and public | Female. Male. Total. Poisoning. 20.4%. | ||
health administrators, therefore, often | 14.8%. 16.2%. 4.9%. 4.6%. 4.8%. 11.0%. | ||
rely on various methods for grouping codes | 10.9%. 10.9%. Other external effects @. | ||
into more manageable categories. For | 10.4%. 12.8%. 12.2%. 4.1%. 6.8%. 5.6%. | ||
injury research, one of the most useful | 6.5%. 10.5%. 9.1%. Unspecified injury of | ||
tools has been the Barell Matrix (Barell | head. 10.8%. 9.9%. 10.1%. 5.3%. 7.7%. | ||
et al., 2001), which categorizes ICD-9-CM | 6.6%. 7.4%. 9.0%. 8.5%. Unspecified injury | ||
injury morbidity codes by body region and | of multiple regions. 12.2%. 10.2%. 10.7%. | ||
nature of injury. Since 1999, mortality | 5.1%. 6.5%. 5.9%. 7.8%. 8.8%. 8.5%. | ||
data have been coded in ICD-10. A | Foreign body in trunk, other #. 2.5%. | ||
successor to the Barell Matrix for use | 1.4%. 1.7%. 17.5%. 14.1%. 15.7%. 11.7%. | ||
with ICD-10 injury mortality diagnosis | 6.3%. 8.1%. Open wound of head. 6.2%. | ||
codes would be a new tool to aid | 10.7%. 9.6%. 1.6%. 9.0%. 5.7%. 3.4%. | ||
researchers and policymakers. | 10.0%. 7.8%. Hip fracture. 0.1%. 0.0%. | ||
3 | Background. Body Sites. Body Sites. | 0.0%. 22.1%. 10.1%. 15.6%. 13.6%. 3.9%. | |
Body Sites. Body Sites. Body Sites. Body | 7.2%. Internal injury of head & 3.6%. | ||
Sites. Body Sites. Nature of Injury. | 3.7%. 3.7%. 7.6%. 8.4%. 8.1%. 6.1%. 5.5%. | ||
Nature of Injury. 1. Amputation. 2. Burn. | 5.7%. Unspecified injury of unspecified | ||
3. Blood Vessel. 4. Crush. 5. Dislocation. | region. 6.4%. 5.4%. 5.6%. 3.6%. 4.6%. | ||
6. Foreign Body. 7. Fracture. 8. Internal | 4.2%. 4.7%. 5.1%. 5.0%. Toxic effects. | ||
Injury. 9. Multiple. 10. Muscle/Tendon. | 4.6%. 4.0%. 4.2%. 2.1%. 3.0%. 2.6%. 3.1%. | ||
11. Nerve. 12. Open Wound. 13. Other Ext | 3.6%. 3.4%. Open wound of thorax. 2.4%. | ||
Eff. 14. Other Spec. 15. Poisoning. 16. | 4.4%. 3.9%. 0.5%. 2.0%. 1.3%. 1.2%. 3.5%. | ||
Sprain/strain. 17. Super/cont. 18. Toxic | 2.7%. Unspecified injury of thorax. 2.4%. | ||
effect. 19. Unspecified. 1. 1. Head. 20. | 2.5%. 2.4%. 1.7%. 2.4%. 2.1%. 1.9%. 2.4%. | ||
Abd+ low bk + pelv. 39. Lower ext other. | 2.3%. Other. 18.1%. 20.3%. 19.8%. 23.8%. | ||
Lower ext other. 2. 2. Face. 21. Trunk | 20.6%. 22.1%. 21.6%. 20.4%. 20.8%. Total. | ||
other. 40. Unspecified. Unspecified. 3. 3. | 100.0%. 100.0%. 100.0%. 100.0%. 100.0%. | ||
Eye. 22. Shouldr/upp arm. 41. Multi | 100.0%. 100.0%. 100.0%. 100.0%. @. Mostly | ||
regions. Multi regions. 4. 4. Neck. 23. | asphyxiation and drowning. #. Mostly | ||
Elbow. 42. Systemic. Systemic. 5. 5. | associated with choking. & Brain | ||
Head+Neck. 24. Forearm. Forearm. Forearm. | injury. | ||
Forearm. 6. 6. SC-neck. 25. Wrist/hand. | 13 | Some injury categories were | |
Wrist/hand. Wrist/hand. Wrist/hand. 7. 7. | concentrated in people over 50: Fractures | ||
SC-upper back. 26. Fingers. Fingers. | of the hip were especially prevalent among | ||
Fingers. Fingers. 8. 8. SC-lower back. 27. | women over 50, accounting for 22.1% of all | ||
Upper ext mult. Upper ext mult. Upper ext | injury-related deaths - the highest | ||
mult. Upper ext mult. 9. 9. SC-other. 28. | ranking category for this demographic | ||
Upper ext other. Upper ext other. Upper | group. For men over 50, hip fractures | ||
ext other. Upper ext other. 10. 10. | accounted for 10.2% of injury deaths. For | ||
SC-Multiple. 29. Hip. Hip. Hip. 11. 11. | people under 50, however, hip fracture | ||
VC-neck. 30. Thigh. Thigh. Thigh. 12. 12. | deaths were almost nonexistent. Foreign | ||
VC-upper back. 31. Hip + thigh. Hip + | body in the trunk accounted for 15.7% of | ||
thigh. Hip + thigh. Hip + thigh. 13. 13. | all injury deaths of people over 50, but | ||
VC-lower back. 32. Upp leg + thigh. Upp | only 1.7% for those 50 or under. These are | ||
leg + thigh. Upp leg + thigh. Upp leg + | mostly choking deaths. Internal injuries | ||
thigh. 14. 14. VC-lower back + pelv. 33. | of the head (brain injuries) accounted for | ||
Knee. Knee. Knee. 15. 15. VC-other. 34. | 8.1% of injury deaths of people over 50, | ||
Lower leg. Lower leg. Lower leg. Lower | but only 3.7% for ages 50 and under. | ||
leg. 16. 16. Thorax. 35. Foot. Foot. Foot. | 14 | Other fatal injury categories were | |
17. 17. Abdomen. 36. Ankle. Ankle. Ankle. | more common among people 50 and under: | ||
18. 18. Pelvis. 37. Ankle + foot. Ankle + | Among people age 50 or less, the biggest | ||
foot. Ankle + foot. Ankle + foot. 19. 19. | fatal injury category was poisoning, | ||
Lower back + pelv. 38. Toes. Toes. Toes. | which, together with toxic effects, | ||
4 | Coding and Validating the Algorithm. A | accounted for 20.3% of all injury deaths. | |
draft of the ICD-10 injury diagnosis | Poisoning and toxic effects were more | ||
matrix was first provided by Lois A. | prevalent among women (25.0%) than among | ||
Fingerhut (NCHS). That draft was based on | men (18.8%). They were less common among | ||
earlier work by Richard Hockey in | people over 50 (7.4%). Other external | ||
Australia. The matrix classifies all | effects (mostly drowning and asphyxiation) | ||
injury ‘S’ and ‘T’ codes by body region | accounted for 12.2% of injury deaths among | ||
and nature of injury. With 19 | those 50 or under, but only 5.6% among | ||
nature-of-injury categories and 42 | those over 50. Unspecified injuries of | ||
body-region categories, it is somewhat | multiple regions accounted for 10.7% of | ||
more detailed than the original Barell | injury deaths among those 50 or less, but | ||
Matrix. Like the original, it also | only 5.9% among those over 50. | ||
provides for collapsing the body regions | 15 | Other fatal injury categories were | |
into broader categories. PIRE translated | more common among people 50 and under | ||
the matrix into a SAS algorithm, which can | (continued): Unspecified head injuries | ||
operate on any valid ICD-10 S or T code. | accounted for 10.1% of injury deaths among | ||
5 | In order to validate the algorithm, we | those 50 or less, but only 6.6% among | |
first tested it against the ICD-10 coded | those over 50. Open wounds were more | ||
Multiple Cause of Death (MCOD) data for | common among males than females. Open | ||
2000. For records containing an injury | wounds of the head accounted for 10.0% of | ||
diagnosis (i.e., an S or T code), we | injury deaths among men and 3.4% among | ||
selected the injury diagnosis from the | women. Open wounds of the thorax accounted | ||
entity axis assigned by the death | for 3.5% of injury deaths among men and | ||
certificate as the earliest injury | 1.2% among women. | ||
diagnosis in the chain of causes leading | 16 | 5.4% of injury death certificates | |
to death. We ran this classifying | lacked any injury diagnoses. Some coroners | ||
diagnosis (Dx0) through our algorithm. The | and MEs follow the convention (which is | ||
algorithm successfully assigned | permitted by coding rules) of letting a | ||
nature-of-injury and body-region codes to | cause code represent the injury without | ||
each case. | any accompanying injury diagnosis code. Of | ||
6 | Data & Methods. We next applied | the cases with at least one injury | |
the algorithm to the 1999-2001 MCOD data. | diagnosis code (the sub-sample used | ||
We selected all cases with at least one | elsewhere in this study), 70.3% had a | ||
injury diagnosis on the record axis. This | single injury diagnosis 19.6% had two | ||
gave us 540,748 cases, which broke down by | injury diagnoses 6.4% had three injury | ||
age and sex as follows: AGE. AGE. SEX. | diagnoses, and 3.6% had four or more | ||
SEX. SEX. Female. Male. Total. 50 or | injury diagnoses. Internal organ injuries | ||
younger. 71,959 (13.3%). 218,909 (40.5%). | of the head (i.e., brain injuries) and | ||
290,868 (53.8%). Over 50. 113,097 (20.9%). | unspecified injuries of the thorax were | ||
136,783 (25.3%). 249,880 (46.2%). Total. | especially likely to be accompanied by at | ||
185,056 (34.2%). 355,692 (65.8%). 540,748 | least one other injury diagnosis (51.1% | ||
(100.0%). | and 56.5%, respectively). | ||
7 | For every injury death, we applied the | 17 | Discussion. This exercise gave a |
algorithm to each injury diagnosis on the | clearer picture of a known weakness of | ||
record axis (except superficial injuries, | ICD-10 coded data - the heavy reliance on | ||
which were judged to be unlikely to cause | “multiple” and “unspecified” categories | ||
death). In order to avoid double counting | that are of little use to researchers. In | ||
deaths with multiple injury diagnoses, we | our injury-coded data, 31.5% of deaths | ||
gave each diagnosis a weight equal to the | with injury diagnoses have a multiple or | ||
reciprocal of the number of injury | unspecified code for either the nature of | ||
diagnoses on the record. Example: a death | injury or the body region, and 13.6% have | ||
that involved a head fracture and a | both. | ||
crushed thorax would be counted as half a | 18 | Conclusion. The SAS algorithm | |
death from head fracture and half a death | successfully assigned body region and | ||
from crushed thorax. By diagnosis matrix | nature of injury classifications to a | ||
cell, we then computed the weighted | multi-year ICD-10 coded mortality dataset. | ||
numbers of cases across all injury deaths. | This new injury diagnosis matrix and the | ||
8 | Results. Top 5 Nature of Injury | SAS algorithm that embodies it will | |
Categories Top 5 Body Region Categories | constitute a useful tool for the | ||
Top 10 Injury Diagnosis Categories as a | description and analysis of fatal injury | ||
function of Nature of Injury and Body | data. The matrix will serve as an initial | ||
Region. | injury classification benchmark for ICD-10 | ||
9 | Top 5 Nature of Injury Categories. | (and, later, during the transition to | |
Remaining Categories 24.3%. Unspecified | ICD-10-CM coding for medical data). | ||
Injury 26.1%. Other External Effects1 | 19 | The algorithm proved robust against a | |
9.1%. Open Wound 15.8%. Poisoning 10.9%. | large mortality dataset that could | ||
Fracture 13.8%. Note. 1 = E.g., | reasonably be expected to provide a | ||
asphyxiation, drowning. | sufficient test, but it should be | ||
10 | Top 5 Body Region Categories. Multiple | validated against other datasets before | |
Regions 10.2%. Remaining Categories 24.9%. | being widely circulated. The heavy use of | ||
Systemic1 23.5%. Unspecified Region 8.3%. | “multiple” and “unspecified” diagnoses | ||
Head 23.7%. Trunk, Other 9.4%. Note. 1 = | will be a challenge to those using these | ||
E.g., foreign body, poisoning, external | ICD-10 coded data for injury research. | ||
The ICD-10 injury diagnosis matrix: Grouping S and T codes by body region and nature of injury.ppt |
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