Abstract
AbstractObjectiveTo develop a clinical informatics approach to identify patients with a history of sexual assault and to characterize the clinical risk factors and comorbidities of this population in a sex-stratified manner.MethodsWe developed and applied a keyword-based approach to clinical notes to identify patients with a history of sexual assault in the Vanderbilt University Medical Center (VUMC) electronic health record from 1989 to 2021. Using a phenome-wide association study (PheWAS), we then examined diagnoses that co-occurred with evidence of sexual assault. We also examined whether sex assigned at birth modified any of these associations.ResultsOur keyword-based algorithm achieved a positive predictive value of 90.4%, as confirmed by manual patient chart review. Out of 1,703 diagnoses tested across all subgroup analyses, we identified a total of 465 associated with sexual assault, many of which have been previously observed in the literature. Interaction analysis revealed 55 sex-differential phenotypic associations.ConclusionsIn a large hospital setting, disclosures of sexual assault were associated with increased rates of hundreds of health conditions.
Publisher
Cold Spring Harbor Laboratory
Reference27 articles.
1. Smith SG , Zhang X , Basile KC , et al. The National Intimate Partner and Sexual Violence Survey (NISVS): 2015 Data Brief – Updated Release. National Center for Injury Prevention and Control, Centers for Disease Control and Prevention; 2018. Accessed August 30, 2020. https://www.cdc.gov/violenceprevention/datasources/nisvs/2015NISVSdatabrief.html
2. Health consequences of sexual violence against women
3. Sexual Abuse and Lifetime Diagnosis of Psychiatric Disorders: Systematic Review and Meta-analysis
4. Sexual Abuse and Lifetime Diagnosis of Somatic Disorders
5. Sexual violence against women: The scope of the problem