Intimate partner violence (IPV) is a serious problem with devastating health consequences. Screening procedures may overlook relationships between IPV and negative health effects. To identify IPV-associated women's health issues, we mined national, aggregated de-identified electronic health record data and compared female health issues of domestic abuse (DA) versus non-DA records, identifying terms significantly more frequent for the DA group. After coding these terms into 28 broad categories, we developed a network map to determine strength of relationships between categories in the context of DA, finding that acute conditions are strongly connected to cardiovascular, gastrointestinal, gynecological, and neurological conditions among victims.

Background It is estimated that a majority of intimate partner violence (IPV) victims suffer from blunt force to the head, neck and the face area. Injuries to head and neck are among the major causes for traumatic brain injury (TBI). Methods In this interdisciplinary study, we aimed to characterize the key associations between IPV and TBI by mining de-identified electronic health records data with more than 12 M records between 1999 to 2017 from the IBM Explorys platform. For this purpose, we formulated a data-driven analytical framework to identify significant health correlates among IPV, TBI and six control cohorts. Using this framework, we assessed the co-morbidity, shared prevalence, and synergy between pairs of conditions. Results Our findings suggested that health effects attributed to malnutrition, acquired thrombocytopenia, post-traumatic wound infection, local infection of wound, poisoning by cardiovascular drug, alcoholic cirrhosis, alcoholic fatty liver, and drug-induced cirrhosis were highly significant at the joint presence of IPV and TBI. Conclusion To develop a better understanding of how IPV is related to negative health effects, it is potentially useful to determine the interactions and relationships between symptom categories. Our results can potentially improve the accuracy and confidence of existing clinical screening techniques on determining IPV-induced TBI diagnoses.