1. Bruce A. Lawrence, Ted R. Miller, Harold B. Weiss
Estimating the Intent of Nonfatal Poisonings in State Hospital Discharge Data
Bruce A. Lawrence, Ted R. Miller, Harold B. Weiss

2. Background
In 10% of poisoning cases in state hospital discharge data, the intent could not be determined from the hospital record. In 1997, the share of cases with undetermined or missing intent ranged from 4% in California and 5% in Rhode Island to 18% in Michigan and South Carolina and 19% in Maine.

3. Suicide attempts account for a majority of nonfatal hospital-admitted poisonings. Conversely, a majority of nonfatal suicide attempts (ca. 70%) involve poisoning. Therefore, the inability to determine the intent of so many poisonings might result in an undercount of suicide attempts.

4. Objectives
To model the intent of nonfatal, hospital-admitted poisonings whose intent cannot be determined from an E code on the hospital record.
To use this model to estimate the likely magnitude of the undercount of nonfatal, hospital-admitted, self-inflicted poisonings.

5. Data 1997 hospital discharge data from 19 states:
Began with 17,798,484 hospital discharges
Narrowed to 1,129,994 acute injuries (6.35% of hospital discharges)
Selected 124,073 nonfatal poisoning-involved cases (10.98% of acute injuries)

6. Sex
Female 71,270 (57.44%)
Male 52,767 (42.53%)
Unknown ( 0.03%)

7. Age
,441 ( 4.29%)
,204 (10.64%)
,072 (12.15%)
,556 (37.52%)
,319 (22.82%)
,269 ( 6.66%)
,203 ( 5.81%)
Unknown ( 0.02%)

8. States AZ 3,902 ( 3.14%) CA 25,462 (20.52%) FL 15,031 (12.11%)
MA 5,272 ( 4.25%)
MD 4,741 ( 3.82%)
ME 1,149 ( 0.93%)
MI 8,729 ( 7.04%)
NE ( 0.78%)
NH 1,132 ( 0.91%)
NJ 7,334 ( 5.91%)
NY 15,676 (12.63%)
PA 13,441 (10.83%)
RI ( 0.71%)
SC 2,639 ( 2.13%)
UT 1,618 ( 1.30%)
VA 6,308 ( 5.08%)
VT ( 0.38%)
WA 3,891 ( 3.14%)
WI 5,437 ( 4.38%)

9. Intent
Self-Inflicted 68,590 (55.28%)
Unintentional 43,034 (34.68%)
Assault ( 0.26%)
Legal/Military ( 0.02%)
Undetermined 6,670 ( 5.38%)
Missing 5,442 ( 4.39%)

10. Methods
We selected the 106,795 cases with known intent, known age greater than 4, and known sex. We modeled the probability of self-inflicted intent (versus other known intent, including unintentional, assault, and legal/military) by logistic regression, using the CATMOD procedure in SAS.

11. The final specification involved 90 terms:
Age (6 age groups covering known ages >4)
Sex, conditioned on age
Admission sources and discharge destinations (4 variables)
Payers (5 variables, 2 conditioned on age)
Psychiatric procedures (4 values based on ICD‑9‑CM procedure code 94.xx)
Counts of diagnoses, causes, and substances (plus substances squared)

12. (Continued)
Length of stay (plus length of stay squared)
State suicide rate
Dummy variables for 5 substance classes, plus 10 two-way and 3 three-way interactions
Dummy variables for 10 diagnosis categories, plus 2 interactions with diagnosis-related drugs
Dummy variables for 40 substance categories, 4 conditioned on age

13. The estimated model was then applied to the 11,999 cases with undetermined intent (E980s) or unknown intent (missing E code). For each case, the model generated a probability that the poisoning was self-inflicted.

14. Performance of Model
If we use a 50% probability cut-off as the standard for identifying a poisoning as self-inflicted, the model successfully identifies self-inflicted poisonings 90% of the time. However, it identifies non-self-inflicted poisonings correctly in just 70% of cases. Perhaps more important, it overestimates the number of self-inflicted poisonings by 4,823 (4.5%).

15. Estimated vs. Actual Intent with 50% Probability Cut-Off
Probability ‚ ‚Other ‚
Self‑ ‚Self‑ ‚Known ‚
Inflicted ‚Inflicted‚Intent ‚
ƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆ
00‑49% ‚ ‚ ‚ 33422
‚ (9.97) ‚ (69.51) ‚
50‑100% ‚ ‚ ‚ 73373
‚ (90.03) ‚ (30.49) ‚
Total
(100.00) (100.00)

16. Tightening the probability cut-off to 55% reduces the overestimate of self-inflicted poisonings, and tightening it to 60% over-corrects slightly, resulting in an underestimate of 1,423 (1.3%). As the probability cut-off is tightened, the total share of cases whose intent is identified correctly falls from 82.7% to 82.3% to 81.6%.

17. Estimated vs. Actual Intent with 55% Probability Cut-Off
Probability ‚ ‚Other ‚
Self‑ ‚Self‑ ‚Known ‚
Inflicted ‚Inflicted‚Intent ‚
ƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆ
00‑54% ‚ ‚ ‚ 36431
‚ (12.46) ‚ (72.92) ‚
55‑100% ‚ ‚ ‚ 70364
‚ (87.54) ‚ (27.08) ‚
Total
(100.00) (100.00)

18. Estimated vs. Actual Intent with 60% Probability Cut-Off
Probability ‚ ‚Other ‚
Self‑ ‚Self‑ ‚Known ‚
Inflicted ‚Inflicted‚Intent ‚
ƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆ
00‑59% ‚ ‚ ‚ 39668
‚ (15.34) ‚ (76.22) ‚
60‑100% ‚ ‚ ‚ 67127
‚ (84.66) ‚ (23.78) ‚
Total
(100.00) (100.00)

19. Validation
We tested the model on a second multi-state hospital discharge dataset similar to the one on which it was estimated:
81,615 cases from 1998 from 15 states. The results were quite similar to those from the 1997 data.

20. Performance of Model on 1998 Data
from 15 States
Percent Predicted Correctly
Probability Other
Cut-Off Self- Known
Level Overall Inflicted Intent
50% % 88.7% 72.3%
55% % 86.1% 75.5%
60% % 83.1% 78.6%

21. The model actually performs slightly better on the non-self-inflicted cases for 1998 than for The small differences between the two years can be attributed to the different mix of states, along with the smaller proportion of self-inflicted cases (61% in 1998 vs. 64% in 1997). The model as estimated on the 1997 data can be expected to perform with similar results on similar data.

22. Results
Having tested and validated the model on cases of known intent, we next applied the model to the cases of undetermined (E980s) and missing (not E coded) intent. To provide for a conservative estimate of the number of self-inflicted cases among these, we chose a 60% cut-off probability.

23. Estimating the Number of Uncoded Self-Inflicted
Poisonings Using a 60% Probability Cut-Off
Coded Intent
Estimated ˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆ
Probability ‚ ‚ ‚
Self‑ ‚Unde‑ ‚ ‚
Inflicted ‚termined ‚Missing ‚
ƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆ
00‑59% ‚ ‚ ‚ 5986
‚ (50.02) ‚ (51.61) ‚(50.72)
60‑100% ‚ ‚ ‚ 5815
‚ (49.98) ‚ (48.39) ‚(49.28)
Total
(100.00) (100.00)

24. We estimate that an additional 5,815 cases (4
We estimate that an additional 5,815 cases (4.7% of all poisonings) were self-inflicted. This would raise the total number of self-inflicted poisonings in the 19-state dataset to 74,405 (60.0% of all poisonings). It would also raise the total number of nonfatal self-inflicted injuries in the 19-state dataset from 81,442 to 87,257 (a 7.1% increase).

25. Note that the estimated share of self-inflicted cases among those coded as undetermined or missing intent (49%) is lower than among cases of known intent (64%). If one were simply to allocate the intent of unknown-intent cases in proportion to the intent of known-intent cases, it would result in an overestimate of the number of self-inflicted poisonings.

26. The impact of our additional estimated self-inflicted poisoning cases varied widely from state to state. For most states, our estimate of self-inflicted poisonings is only 3%–8% higher than the number E coded as such. For seven states, however, our estimate is even greater:
Vermont %
New Jersey 10.1%
Virginia 12.3%
Florida 14.2%
Michigan 15.2%
Maine 21.2%
South Carolina 22.3%

27. In four of these states (FL, ME, MI, VA), the problem is a low overall rate of E coding. In each of these states, poisonings are actually more likely to be E coded than other injuries. As these states improve their overall E‑coding rates, it can be expected to address this problem.

28. In three other states, it appears that there might be a reluctance to code self-inflicted poisonings as such. Two states (NJ, VT) rely heavily on undetermined intent (E980s) E codes, while a third (SC) tends to omit E codes entirely on likely self-inflicted poisonings.

29. Our model's high rate of false positives (when poisonings coded as unintentional are modeled as self-inflicted) raises the question of whether some self-inflicted poisonings might be falsely coded as unintentional. Overall, our model identifies 23.7% of unintentional-coded poisonings as self-inflicted. But this share varies widely by state. For two states (CA, NY), the rate is well under 20%. For 10 others, it is 29% or higher, with NH at 34%. This suggests that there might be more self-inflicted poisonings hidden as unintentional, in addition to the ones among the undetermined- and missing-intent cases.