HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS REGISTER		Author Keyword(s) Vol Page [Advanced]

This Article Full Text Full Text (PDF) Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Services Email this link to a friend Similar articles in this journal Similar articles in PubMed Add article to my folders Download to citation manager Request Permissions Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Weiss, H B Articles by Miller, T R Search for Related Content PubMed PubMed Citation Articles by Weiss, H B Articles by Miller, T R

Incomplete and biased perpetrator coding among hospitalized assaults for women in the United States

¹ Center for Injury Research and Control, University of Pittsburgh, Pittsburgh, Pennsylvania
² Graduate School of Public Health, Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania
³ Pacific Institute for Research and Evaluation, Calverton, Maryland

Correspondence to:
Dr Harold Weiss
Center for Injury Research and Control, University of Pittsburgh, 200 Lothrop St, Suite B400, Pittsburgh, PA 15213, USA; hw{at}injurycontrol.com

ABSTRACT
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.

Keywords: hospital discharge data; intimate partner violence; violence

Abbreviations: CI, confidence interval; ICD-9-CM, International Classification of Diseases, 9th revision, clinical modification