Incomplete and biased perpetrator coding among hospitalized assaults for women in the United States.
BACKGROUND
Since 1997, hospital discharge data have included external cause of injury (E codes) for designating perpetrator relationship in assaults. For intentional injuries, guidelines require using two E codes; one for the injury mechanism and another (E967.n) identifying perpetrator relationship. Completeness and characteristics of the use of these codes have not been studied on a multistate level among states with complete E coding.


METHODS
Hospital discharge data for 1997 were solicited from states with good E coding completeness. Data were received from 19 states (51.9% of women in the United States, ages 15-49). For assaulted women, a regression model was constructed to identify factors associated with perpetrator code assignment using age, payment source, pregnancy status, race, and severity as covariates.


RESULTS
Among 137 887 injured hospitalized women age 15-49, there were 7402 assaults (5.4%). Among all assaults to women, perpetrator coding was poor (8.8%). Among those that were perpetrator coded, 83.7% were spouse/partner related. Age was positively associated with probability of having a perpetrator code (p<0.001). Those paid by a private source were 42.9% more likely to have a perpetrator code (p = 0.007). Pregnant women were seven times more likely to have a perpetrator code (p<0.001). Non-white women were 66.8% less likely to have a perpetrator code (p<0.001) than white women.


CONCLUSIONS
The poor use of perpetrator codes in hospital discharge data minimizes their usefulness for surveillance of serious injury from intimate partner violence. An implication of this research is the need to understand the gaps and strengthen the completeness of perpetrator documentation and coding. The findings suggest caution when interpreting the results from existing hospital discharge data based intimate partner violence surveillance systems.
Weiss
H B
HB
Center for Injury Research and Control, University of Pittsburgh, Pittsburgh, Pennsylvania 15213, USA. hw@injurycontrol.com
Ismailov
R M
RM
Lawrence
B A
BA
Miller
T R
TR
D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D018585:Battered Women; D015982:Bias; D019548:Crime Victims / Q000706:statistics & numerical data; D005260:Female; D005381:Financing, Organized / Q000191:economics; D005568:Forms and Records Control / Q000592:standards; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D008499:Medical Records / Q000592:standards*; D008875:Middle Aged; D010351:Patient Discharge / Q000706:statistics & numerical data; D011247:Pregnancy; D014481:United States / Q000453:epidemiology; D014754:Violence / Q000145:classification* / Q000208:ethnology; D014947:Wounds and Injuries / Q000453:epidemiology / Q000209:etiology